Citation
Solvatochromic solvent polarity measurements, retention, and selectivity in reversed phase liquid chromatography

Material Information

Title:
Solvatochromic solvent polarity measurements, retention, and selectivity in reversed phase liquid chromatography
Creator:
Johnson, Bruce Philip, 1958-
Publication Date:
Language:
English
Physical Description:
xiv, 212 leaves : ill. ; 28 cm.

Subjects

Subjects / Keywords:
Carbon ( jstor )
Charge separation ( jstor )
Correlations ( jstor )
Fractions ( jstor )
Geomagnetic polarity time scale ( jstor )
Interfacial tension ( jstor )
Liquid chromatography ( jstor )
Solutes ( jstor )
Solvents ( jstor )
Steepest descent method ( jstor )
Chemistry thesis Ph. D
Dissertations, Academic -- Chemistry -- UF
Liquid chromatography ( lcsh )
Genre:
bibliography ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (Ph. D.)--University of Florida, 1986.
Bibliography:
Bibliography: leaves 201-211.
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Bruce Philip Johnson.

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
030394641 ( ALEPH )
16952117 ( OCLC )
AER3622 ( NOTIS )
AA00004863_00001 ( sobekcm )

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Full Text


SOLVATOCHROMIC SOLVENT POLARITY MEASUREMENTS,
RETENTION, AND SELECTIVITY
IN REVERSED PHASE LIQUID CHROMATOGRAPHY
BY
BRUCE PHILIP JOHNSON
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1986


This dissertation is dedicated
to my son, Garrett Chase, whose
arrival coincided with the
completion of this work.


ACKNOWLEDGMENTS
There are many people that I wish to acknowledge; in
his or her own way, each has contributed to my educational
progression. I would like to begin with my parents, Stan
and Connie Johnson, who constantly encouraged me to explore
my world and who instilled in me an unquenchable thirst for
knowledge. There are not many children who are fortunate
enough to grow up with a laboratory and a photographic
darkroom in their own basement!
My deepest gratitude is extended to Prof. Dr.
Christian Reichardt of Phillips-Universitat (Marburg, West
Germany), who so generously provided my advisor with
samples of the ET-30 dye, as well as providing helpful
comments during the preparation of two manuscripts.
I must also express my gratitude to the Eastman Kodak
Company, who funded 3 years of my graduate education
through the Kodak Fellow program, with no strings attached.
My advisor, Dr. John G. Dorsey, has been one of the
most enjoyable aspects of my graduate education. The many
hours we spent talking about everything from chromatography
to congealed desserts will always be treasured. He should
also be thanked for initiating my addiction to the
iii


Wall Street Journal, though he was unable to turn me into
an oenophile.
I also want to acknowledge my fellow group members,
who, along with their superb sense of humor, have made
graduate school an experience I shall always cherish.
Lastly, without the love, patience, and support of my
wife, Bonnie, and her parents, Phil and Sylvia Reinstein,
the completion of this work would not have been possible;
this was especially so after the arrival of our son,
Garrett Chase, whose timely (?) arrival coincided with the
completion of this tome.


TABLE OF CONTENTS
ACKNOWLEDGMENTS iii
LIST OF TABLES vii
LIST OF FIGURES ix
ABSTRACT xiii
CHAPTERS
I INTRODUCTION 1
Mobile Phase Effects 3
Stationary Phase Effects 7
Empirical Measures of Solvent Polarity .17
Analytical Application of the ET-30 Dye 26
II SOLVATOCHROMIC SOLVENT POLARITY MEASUREMENTS ... 34
Experimental 34
Results 42
Relationship Between Snyder's P' Polarity
Values and the ET(30) Scale 59
III CORRELATIONS BETWEEN CHROMATOGRAPHIC
RETENTION AND MOBILE PHASE POLARITY 65
Experimental 65
Results 67
Comparison with the "Carr Approach" 99
IV CORRELATIONS BETWEEN CHROMATOGRAPHIC
SELECTIVITY AND MOBILE PHASE POLARITY 104
Experimental 104
Introduction 105
Results 108
V DISCUSSION AND CONCLUSIONS 136
Stationary Phase Effects 150
Application of These Results 156
v


Interfacial Tension Effects....
Suggestions for Future Research
160
166
APPENDICES
A CHROMATOGRAPHIC RETENTION AND SELECTIVITY
DATA 175
B MODIFICATION OF CURVE FITTER PROGRAM TO
ALLOW CALCULATION OF CONFIDENCE INTERVALS 196
C MODIFICATION OF CURVE FITTER PROGRAM
TO INTERPOLATE SPECTRAL PEAK POSITIONS 197
D SOLVATOCHROMIC SOLVENT POLARITY
MEASUREMENTS 198
REFERENCES 201
BIOGRAPHICAL SKETCH 212
vi


LIST OF TABLES
Table Page
2-1
Effect of varying ET-30 concentration on
X and absorbance in 45/35/20 (v/v/v)
Me0H/ACN/H20
. .36
3-1
Linear regression results for correlations
between log k' and either percent organic
modifier or ET(30) polarity
. .73
3-2
p
Mean and median r^ values for correlations
shown in Table 3-1 -
.. .95
3-3
Multiple linear regression between log k'
values and a, 8, and ,
4-1
Squared correlation coefficients (r2) for
log a data with respect to percent organic
modifier (0M), mole fraction 0M, and ET(30)
polarity
4-2
Comparison of log a values as measured by
nitroalkanes and alkylbenzenes for a
Hamilton PRP-1 column
. .125
4-3
Correlations between log a and percent
organic modifier (0M), mole fraction organic
modifier (MF 0M), or ET(30) polarity for
a Hamilton PRP-1 polymeric column
. .126
5-1
Effect of increasing solute size upon
sensitivity to changes in E for alkylbenzenes
. .139
5-2
Effect of increasing solute size upon
sensitivity to changes in Efj>(30) polarity
for halobenzenes
5-3
Comparison of slope and y-intercept values
for log k' versus ET(30) polarity for
phenanthrene
. .145
vii


5-4 Comparison of slope and y-intercept values
for log k' versus ET(30) polarity for
ethylbenzene 145
5-5 Correlations between enthalpy of transfer
(aH) and 5^(50) polarity values 147
5-6 Ratio of slopes for a given solute and column
with methanol and acetonitrile as organic
modifiers 150
5-7 Intersection points for log k' versus Erj(30)
for alkylbenzenes 154
viii


LIST OF FIGURES
Figure Page
1-1 Structure of the ET-30 dye molecule,
2,6-Diphenyl-4-(2,4,6-triphenyl-N-
pyridino)phenolate in the ground and
excited states 24
2-1 Beer's law plot for ET-30 dissolved in
45/30/10 raethanol/acetonitrile/water (v/v/v)....37
2-2 Thermochromism of 4-nitroanisole in
33.3/33.3/33.4 methanol/water/acetonitrile
(v/v/v) 40
2-3 Thermochromism of 4-nitroanisole in
33.3/33.3/33.4 methanol/water/acetonitrile
(v/v/v) 41
2-4 Representative UV/VIS absorbance spectrum of
4-nitroanisole in methanol 43
2-5 Measurements of n* dipolarity/polarizability
for methanol/water mixtures with respect to
percent methanol 45
2-6 Measurements of tt* dipolarity/polarizability
for methanol/water mixtures with respect to
mole fraction of methanol 46
2-7 Measurements of tt* dipolarity/polarizability
for acetonitrile/water mixtures with respect
to percent acetonitrile 47
2-8 Measurements of it* dipolarity/polarizability
for acetonitrile/water mixtures with respect
to mole fraction acetonitrile 48
2-9 Representative UV/VIS absorption spectrum
of the ET-30 dye dissolved in methanol 51
IX


2-10 Measurements of Em(30) polarity for methanol/
water mixtures with respect to percent
methanol 52
2-11 Measurements of E^(30) polarity for methanol/
water mixtures with respect to mole fraction
of methanol 53
2-12 Measurements of E,j(30) polarity for
acetonitrile/water mixtures with respect to
percent acetonitrile 54
2-13 Measurements of E^OO) polarity for
acetonitrile/water mixtures with respect to
mole fraction of acetonitrile 55
2-14 Comparison between Snyder's P' and Dimroth-
Reichardt's E^(30) polarity values for pure
solvents 61
2-15 Comparison between Eqi(30) polarity values
predicted by equation 2-3 and actual
E'p(30) polarity values reported by Reichardt
and Harbusch-Gornert (1983) 64
3-1 Retention data for 4-nitrophenol plotted with
respect to percent acetonitrile 71
3-2 Variation in mole fraction of methanol as
a function of volume percent 72
3-3 Variation in mole fraction of acetonitrile as
a function of volume percent 73
3-4 Retention data for 4-nitrophenol plotted with
respect to mole fraction of acetonitrile 74
3-5 Retention data for 4-nitrophenol plotted with
respect to tt* dipolarity/polarizability for
the same solvent mixtures 75
3-6 Retention data for 4-nitrophenol plotted with
respect to the E-j(30) polarity for the same
solvent mixtures 76
3-7 Histogram of r values for the 332 retention
data sets plotted with respect to percent
organic modifier 90
x


p
3-8 Histogram of r values for the 332 retention
data sets plotted with respect to E.^(30)
polarity 91
P
3-9 Modified histogram of r values for the
332 retention data sets plotted with respect
to percent organic modifier 92
p
3-10 Modified histogram of r^ values for the
332 retention data sets plotted with respect
to Erp(30) polarity 93
4-1 Chromatographic selectivity measurements as a
function of percent methanol 110
4-2 Chromatographic selectivity measurements as a
function of mole fraction of methanol 111
4-3 Chromatographic selectivity measurements as a
function of E>p(30) polarity of methanol/
water mixtures 112
4-4 Chromatographic selectivity measurements as a
function of percent acetonitrile 113
4-5 Chromatographic selectivity measurements as a
function of mole fraction of acetonitrile 114
4-6 Chromatographic selectivity measurements as a
function of ET(30) polarity of acetonitrile/
water mixtures 115
4-7 Comparison between r^ values for plotting
methylene selectivity data with respect to
either percent organic modifier or E^(30)
polarity 119
4-8 Comparison between methylene selectivity
results obtained with either 1-nitroalkanes
or alkylbenzenes as the homologous series 124
4-9 Example of the measurement of methylene
selectivity with nitroalkanes as the
homologous series 128
4-10 Chromatographic selectivity measurements as
a function of percent methanol 129
4-11 Chromatographic selectivity measurements as
a function of mole fraction of methanol 130
xi


4-12 Chromatographic selectivity measurements as
a function of E^(30) polarity of methanol/
water mixtures 131
4-13 Chromatographic selectivity measurements as
a function of percent acetonitrile 132
4-14 Chromatographic selectivity measurements as
a function of mole fraction of acetonitrile.... 133
4-15 Chromatographic selectivity measurements as
a function of Em(30) polarity of
acetonitrile/wafer mixtures 134
5-1 Slope of log k' versus E^(30) polarity as a
function of carbon number for methanol/
water mixtures 142
5-2 Slope of log k' versus Eip(30) polarity as a
function of carbon number for acetonitrile/
water mixtures 143
5-3 Variation in surface tension as a function
of percent methanol 161
5-4 Variation in surface tension as a function
of mole fraction of methanol 162
5-5 Variation in surface tension as a function
of percent acetonitrile ....163
5-6 Variation in surface tension as a function
of mole fraction of acetonitrile 164
5-7 Comparison between surface tension and
E 5-8 Comparison between surface tension and
E-p(30) polarity for acetonitrile/water
mixtures 168
xii


Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
SOLVATOCHROMIC SOLVENT POLARITY MEASUREMENTS,
RETENTION, AND SELECTIVITY
IN REVERSED PHASE LIQUID CHROMATOGRAPHY
BY
BRUCE PHILIP JOHNSON
August, 1986
Chairman: John G. Dorsey
Major Department: Chemistry
The E>j(30) polarity and n* dipolarity/polarizability
of binary acetonitrile/water and methanol/water mobile
phases used in reversed-phase liquid chromatography were
measured and compared with chromatographic retention and
selectivity. For the retention data, plots of log k*
versus the Em(30) polarity were generally found to be
better descriptors of retention than the more commonly used
plots of log k versus percent organic modifier. A total
of 332 sets of retention data were examined, and the
overall average r^ values obtained for simple linear
regression of log k' versus either percent organic modifier
or Et(30) values were 0.9783 and 0.9910, respectively.
The slope and y-intercepts of plots of log k' versus
E^(30) polarity were found to be dependent on the solute
xiii


size, solvent system, and the column. Also, for a given
column and solute, the slope for the two solvent systems
examined was found to vary in systematic matter, with that
of raethanol/water mixtures 1.43 times greater (on the
average) than that for acetonitrile/water mixtures. This
variation in slope is evidence of differential solvation of
the bonded phase alkyl chains by the two organic modifiers.
In addition, the variation in methylene selectivity as
a function of either percent organic modifier or Erp(30)
polarity has been examined for various bonded phases, as
well as for a polymer-based column.
Solvatochromic solvent polarity measurements offer a
unique view of the retention process, by providing a means
of determining mobile phase polarity that is independent of
the chromatographic system, thus allowing de-convolution of
subtle stationary phase solvent effects, as well as the
prediction of chromatographic retention.
xiv


CHAPTER I
INTRODUCTION
The actual mechanism of retention in reversed phase
liquid chromatography (RPLC) has been the subject of much
controversy and debate since the first bonded phases for
chromatography became commercially available in the early
1970s. Despite its name, reversed phase liquid
chromatography is actually a more "popular" technique than
normal phase liquid chromatography (NPLC). Stationary
phases used in RPLC typically consist of a silica-based
supporting material to which nonpolar carbon chains are
bonded. These carbon chains are most commonly straight
chains of length 8 or 18 carbons (hence the terms "octyl,"
"octadecyl," C-8, C-18, etc. to describe the type of bonded
phase). The carbon chains are attached through a bonding
reaction in which the surface hydroxyl groups present on
the silica (silanols) are reacted with the appropriate
chlorosilane, leading to an Si-O-Si-C bond. For example,
to produce an octadecyl bonded phase, one could react
dimethyloctadecylchlorosilane with silica. The bonding
reaction is not exhaustive, however, so in a second step
trimethylchlorosilane or hexamethyldisilazine is typically
added in order to "endcap" the residual silanols that may
1


2
not be accessible to the larger, more sterically hindered
silane used in the first bonding reaction.
An ideal bonded phase would have no residual silanols
and would possess univariate pore and particle size
distributions. Practically speaking, no bonded phase can
be said to be free of residual silanol groups; one of the
major differences between competing commercial stationary
phases is in the degree of endcapping.
The presence of residual silanols is highly
undesirable since it leads to a second mechanism of
retention. Polar compounds and/or ones possessing hydrogen
bond donor/acceptor ability can interact with these
silanols (silanophilic solutes), leading to distorted peak
shape and/or greatly increased retention (Bij et al., 1981;
Nahum and Horvath, 1981). This problem was recently
reviewed, and the effects of both silanophilic and
metallophilic interactions were compared (Sadek et al.,
1985a). It was found that stainless steel inlet frits
commonly employed in LC columns also cause losses in
efficiency, due to both mechanical and chemical
interactions. Silanophilic interactions were found to be
the major factor in affecting the retention of basic amine
compounds.
While the mechanism of normal phase liquid
chromatography (NPLC) can be said to be fairly well
characterized in terms of adsorption at active sites upon


3
the silica or alumina surface, that of RPLC remains
controversial. In general, one can distinguish two broad
areas of study of this mechanism. These two areas are
referred to as "mobile phase effects" and "stationary phase
effects."
Mobile Phase Effects
In the first of these ("mobile phase effects"), one
observes or calculates the effects of changing mobile phase
composition on chromatographic retention. Typical mobile
phases used in RPLC consist of water to which an organic
modifier has been added. The most frequently used organic
modifiers are methanol, acetonitrile, and tetrahydrofuran.
One example of the approaches classified as "mobile
phase effects" is that of solubility parameter theory.
Hildebrand's solubility parameter has been shown to be
useful in the prediction of many solution properties and is
defined by
6 = (E/V)1/"2
(1-1 )
where E is the molar heat of vaporization of the solvent
and V is its molar volume. When applied to chromatography,
retention is viewed in terms of the relative solubility
parameters of the solute, mobile phase, and the stationary
phase (Xarger et al., 1978; Schoenmakers et al., 1982).
1978; Schoenmakers et al.,


4
Capacity factors can then be considered to be related to
these parameters, as shown in the following equation:
In k' = (v/RT)(5m + 6s 26.)(6m 5s)
+ In (n /n ) (1-2)
s m
where v is the molar volume of the solute and <5m, 6g, and
are the solubility parameters of the mobile phase,
stationary phase, and solute, respectively. The (ng/nm)
terra is the ratio of moles of the stationary and mobile
phases, respectively. If the solubility parameter for a
solvent mixture is approximated by assuming linear
additivity of volume fractions, the dependence of retention
on the volume fraction of one of the components becomes
In k' = A ()2 + B (4>) + C (1-3)
where A, B, and C are constants. Assuming linear
additivity of solubility parameters is questionable,
however. Particularly for aqueous mixtures, where hydrogen
bond forces have a very large effect on the heat of
vaporization, the solubility parameter is likely to be
complex function of the volume fraction of the
components. This equation also results from assuming that
the stationary phase solubility parameter is a constant,


5
regardless of the mobile phase composition, which is also a
questionable assumption (see discussion of stationary phase
solvation in the latter part of this section). Moreover,
it is impossible to measure the solubility parameter of
either the binary/ternary solvent mixtures used in RPLC, or
the alkyl chains of the stationary phase. While the theory
enables qualitative predictions to be made on the basis of
relative polarity of the solute and phases, quantitative
calculations are not possible.
Hafkenscheid and Tomlinson (1983) have recently re
cast solubility parameter theory for RPLC. Semi-empirical
relationships were derived in order to allow more accurate
predictions of retention. Other workers have subdivided
the solubility parameter into individual contributions due
to dispersive forces, proton transfer, polar interactions,
etc., in an attempt to predict retention with greater
accuracy. An example of this approach would be the work of
Tjissen et al. (1976). Unfortunately, as the accuracy of
prediction increases the practicality of applying such
complex equations also decreases in an inverse fashion.
One of the most well-known approaches to
chromatographic retention is the hydrophobic theory of
Sinanoglu (1968), as applied by Horvath and Melander
(1977). This model (also referred to as the solvophobic
model) describes retention in terras of repellent forces
between the relatively nonpolar solute and the highly polar


6
aqueous mobile phase. This results in the formation of a
complex between the stationary phase ligands and the
relatively hydrophobic solute. Here the stationary phase
acts as a passive receptor to hydrophobic molecules that
are repelled by the aqueous mobile phase (cavity effect).
The stationary phase is treated as a constant, and specific
interactions between residual silanols and polar groups on
the solute molecules are not treated. Various mathematical
expressions were derived relating retention to solute
properties such as the hydrocarbonaceous surface area (HSA)
and solvent properties such as the dielectric constant or
surface tension.
Recently, Antle et al. (1985) compared various RPLC
columns with respect to solvophobic selectivity. Retention
differences seen among columns were ascribed to three
effects: differences in phase ratio, the polarity of the
bonded phase, and the dispersion solubility parameter of
the stationary phase.
Martire and Boehm (1980, 1983) have applied
statistical-mechanical theory to the description of
chromatographic retention. Using a lattice model,
predictions were made about the effects of either changing
mobile phase composition or length of alkyl bonded
groups. Though these derivations are quite rigorous,
practical application of the results is somewhat


7
difficult. Furthermore, because of several assumptions
made, again only qualitative predictions are possible.
Interaction indices (empirical measurement of I values
based on solute retention) have also been used by Jandera
et al. (1982) to predict retention. Here it is assumed
that the empirical interaction index of a solvent mixture
is a linear sum of the volume fraction contributions of the
solvents and again only qualitative predictions are
possible.
Stationary Phase Effects
In the second broad area of study ("stationary phase
effects"), the nature of the stationary phase is studied
through either direct physical measurement or through the
effects of changing the type of bonded phase (i.e., C-2,
C-8, etc.) on chromatographic retention. Direct physical
measurements of the stationary phase involve either
spectroscopic methods or actual chemical dissolution.
The most basic chemical analysis of a stationary phase
is the determination of percent carbon. The percentage of
carbon loading provides information about the extent of the
bonding reaction, as well as the degree of surface coverage
(assuming the surface area has been determined). Of
course, this provides no information about the conformation
or spatial distribution of the alkyl chains. Other
dissolution methods have been used in an attempt to examine


8
the chemical form of the bonded alkyl chains. For example,
Lullraan et al. (1935) carried out studies in which bonded
phase packings were fused with potassium hydroxide. In
this manner, the alkyl ligands were cleaved from the silica
substrate, and subsequent 3C analysis of the fusion
products revealed the presence of hexaalkyldisiloxanes and
trialkylsilanols for monomeric bonded phases. Another
approach is to digest the stationary phase in hydrofluoric
acid and then to subject this digest to analysis by gas
chromatography (Fazio et al., 1935). Based on GC analysis
of these digests, it was possible to distinguish between
the various methods used to derivatize the silica (i.e.,
whether mono-, di-, or tri-chlorosilanes had been used).
While the stationary phase is often treated as a
passive or invariant entity, there is much evidence that
the solvation of the alkyl ligands themselves changes in
response to varying composition of the mobile phase. This
is best exemplified by the re-equilibration necessary after
an organic concentration gradient. That is, the alkyl
chains that comprise the stationary phase surface are
preferentially solvated by the organic component of the
mobile phase. Because of this, the interfacial region
between the bulk mobile phase and the surface of the silica
base has widely varying physical properties, so that
chromatographic retention reflects the statistical mean of
these varying physical properties. The organic modifier


9
content of
the
stationary
phase increases
with
the
concentration
of
modifier in
the mobile phase
(Yonker
et
al., 1932a, 1932b). Among the three most commonly used
organic modifiers, tetrahydrofuran has been shown to
solvate the stationary phase to the greatest extent,
followed by acetonitrile and methanol (Yonker et al.,
1982a, 1932b). Thus, while the mobile phase may consist of
a 50/50 mixture, the stationary phase will be solvated by a
mixture with a significantly higher proportion of the
organic modifier.
Lochmuller and Wilder (1979) compared the selectivity
of various bonded phases with that of equivalent 1iquid-
liquid systems. For chain lengths greater than
approximately 12 carbons, the selectivity was found to be
comparable to the liquid-liquid system. Also, Lochmuller
et al. (1981) prepared bonded phases with either n-heptyl,
cyclohexyl, or bicyclohepty1 alkyl chains. The n-heptyl
phase was found to have the highest selectivity and
capacity, though the cyclic phases were found to retain
cycloalkanes preferentially. Jinno and Okamato (1984)
prepared bonded phases with various aromatic moieties.
Capacity factors were measured for various polynuclear
aromatic hydrocarbons (PAHs). In this case, the pore size
of the silica matrix appeared to influence retention,
either because of its effect on the bonding reaction or


10
varying abilities of the PAHs to penetrate the interior
pores (steric effects).
One way to use a spectroscopic method in
characterizing the stationary phase is to sorb or
chemically bond a probe molecule to the surface and then
observe the electronic spectrum of the probe molecule.
Fluorescence spectroscopy lends itself to this type of
measurement, because of the type of sample and the inherent
lower detection limits possible. Since the sample is a
solid, it is very difficult to observe the adsorbed species
directly through absorption spectroscopy. That is, the
solid silica particles tend to scatter the incoming light
beam to a greater degree; using a lower amount of suspended
solid lowers the degree of light scattering at the expense
of lowered sensitivity to the presence of the probe
molecule. A secondary problem is the need to apply very
small amounts of the probe molecule to the stationary
phase. If too much is applied, more than a monolayer may
be formed, and thus the resultant information is of
questionable value. Also, one would not want to "overload"
the packing, i.e., operate at a concentration where the
sorption isotherm becomes nonlinear, which would also yield
results not applicable to the true conditions seen by the
stationary phase. For these reasons, fluorescence (for
UV/VIS) or diffuse reflectance (for infrared or UV/VIS)
spectroscopy are ideally suited to this type of


11
experiment. Of course, it is essential that for
fluorescence experiments, the excitation and emission
wavelengths be sufficiently separated to avoid interference
from the aforementioned scattered light.
In choosing a probe molecule to study the stationary
phase, the two most important criteria are spectral
response to changing solvent polarity and affinity for the
bonded alkyl chains. A probe molecule with insufficient
affinity (i.e., too low of a partitioning coefficient
between the mobile and stationary phases) will reside in
the mobile phase to such an extent that the fluorescence
cannot be attributed solely to that residing on the
stationary phase. For these reasons, the most commonly
used probe molecule has been pyrene, a 4-ring fused
aromatic compound. The fluorescence spectrum has vibronic
structure which is quite sensitive to the solvent environ
ment. In fact, this molecule has been used to establish
the Py scale of solvent polarity (Dong and Winnik, 1984;
empirical solvent polarity scales are discussed in detail
in the latter part of this chapter). The fluorescence
spectrum of pyrene contains five major vibronic bands,
labeled I to V, beginning with the 0-0 band. The ratio of
the intensities of bands I and III has been shown to be
highly responsive to changing solvent environment. Being a
large, hydrophobic molecule, it has a very large affinity
for the alkyl chains of the stationary phase. Two recent


12
papers have reported on the variation in stationary phase
polarity (as seen by pyrene sorbed onto the column packing)
as a function of the mobile phase composition (Carr and
Harris, 1986; Stahlberg and Almgren, 1985).
It is interesting to note that these two groups
obtained data for complementary organic modifier
concentration ranges, as a result of the experimental
conditions used. Stahlberg and Almgren (1985) measured the
surface polarity of C-2 and C-18 surfaces in the presence
of 0-30# methanol/water and acetonitrile/water mixtures.
This was done by using a suspension of 2-3 rag packing per
raL of solvent. Sodium tetradecylsulfate was also added
(0.5 mg/mL) to prevent flocculation of the particles. In
the 0-30# acetonitrile range, the surface polarity of the
C-18 packing was found to be greatest at the extremes,
while in methanol it decreased steadily as the
concentration increased. At higher concentrations of
organic modifier (>30# v/v), the concentration of pyrene in
the solvent mixture became too great and thus obscured the
fluorescence spectrum of the sorbed material. The
interpretation of these results is complicated, however,
because of the presence of added surfactant (0.5 mg/mL;
0.0015 M), which is also likely to sorb onto the bonded
chains and modify the surface polarity. Carr and Harris
(1936) studied both polymeric and monomeric C-13 phases in
a similar manner, except that the sample consisted of a


13
flow-cell packed with the solid, through which the solvent
mixture with pyrene was passed. In this case, the
investigators were limited to concentrations greater than
20, 25, and 50$ acetonitrile, tetrahydrofuran, and
methanol, respectively, because the entire packed particle
bed could not be fully equilibrated with pyrene. Here the
ratio of stationary phase to mobile phase volume was much
higher, leading to a much greater quantity of sorbed
pyrene.
This effect can be demonstrated quantitatively by the
following equation relating capacity factor (k1) to the
thermodynamic distribution coefficient (K) and phase ratio
U):
k' = k

The phase ratio, , is the ratio of the volumes of the
stationary and mobile phases. The capacity factor, k',
corresponds to the ratio of the moles of the sorbed
material present in the stationary and mobile phases at any
given instant. Thus, the packed bed used by Carr and
Harris (1986) has a much higher value than the slurry used
by Stahlberg and Almgren (1985), making the use of higher
organic modifier concentrations necessary (lower X
values). On the other hand, the upper limit of organic
modifier concentration is increased, since the higher value


14
compensates for the greatly decreased affinity of pyrene
for the stationary phase (lower K). Thus, Carr and Harris
(1986) were able to report surface polarities for up to 80,
45, and 70# methanol, tetrahydrofuran, or acetonitrile,
respectively. For a C-18 monomeric packing, the surface
polarity was found to increase with increasing organic
modifier concentration, with methanol systems having
consistently lower polarity than that of the acetonitrile
or tetrahydrofuran systems. This is a direct reflection of
the fact that much less methanol is absorbed by the alkyl
chains as the organic concentration is increased, so the
polarity remains closer to that of a pure alkane. On the
other hand, much greater amounts of acetonitrile and
tetrahydrofuran solvate these alkyl chains, leading to an
increase in apparent polarity (with respect to a pure
alkane). These results are fully consistent with those of
earlier workers who measured the adsorption isotherms of
organic modifiers onto various column packings. For
example, McCormick and Karger (1980a, 1980b) and Tanaka et
al. (1980) reported the organic modifier content of
reversed phase column packings under various
concentrations. Even at a concentration of 10# organic
modifier, acetonitrile was found to solvate the alkyl
chains to a much higher degree than methanol.
One way to get around the problem of lowered affinity
of the probe for the stationary phase at high organic


15
modifier concentration is to simply immobilize it by
bonding it to the stationary phase. Lochmuller et al.
(1985) measured the fluorescence of surface bonded
exciplexes (pyrene/N,N-dimethylaniline) to measure the
surface polarity after endcapping with either
trimethylchlorosilane (TMCS) or hexamethyldisilazine
(HMDS). Trimethylchlorosilane was found to yield a
stationary phase of lower polarity.
Another major area of spectroscopic examination of
stationary phases involves the use of nuclear magnetic
resonance (NMR). As with the sorbed probe fluorescence
experiments, the greatest wealth of information is derived
from those in which the packing is examined under "real"
conditions, i.e., in the presence of a mobile phase. Most
often, 13C is used in NMR experiments. One problem that
must be overcome is the low signal to noise ratio of 13q_
NMR, which is aggravated by the nature of the sample.
Also, alkyl chain C-atoras have nearly identical chemical
shifts, making it difficult to differentiate between
individual positions within the chain. Gilpin and Gangoda
(1984, 1985) have synthesized stationary phases in which
the terminal carbon atom is enriched with the isotope,
thus overcoming some of these difficulties. The spin-
lattice relaxation times (in either pure deuterated
chloroform or acetonitrile) were found to be fairly
constant for the various chain lengths studied. However,


16
at higher coverage densities, a decrease was noted. This
is evidence for the increasing interaction between the
neighboring alkyl chains. The effect of solvent viscosity
was also explored; an inverse relationship was found
between spin-lattice relaxation time and solvent
viscosity. Also, iNMR with magic angle spinning has
been used to differentiate between the various chemical
environments of the silicon atoms in dry samples of column
packings (Fyfe et al., 1985).
Fourier transform infrared spectroscopy (FTIR) has
been used to directly observe the stationary phase alkyl
chains. Again, experiments have been done with both dry
packings and in the presence of solvent mixtures. In this
case, a major difficulty arises from the strong infrared
absorption band of water and methanol (0-H stretching),
which tends to obscure the C-H stretching band of the
bonded alkyl chain. One solution to this problem is to use
deuterated solvents, as Sander et al. (1983) have done with
C-1 to C-22 column packings. The range of 70-100# methanol
was studied, and evidence of increasing chain order was
found at the higher organic concentrations. Also,
temperature studies were carried out on the dry packings,
and no phase transitions were observed at temperatures near
or below the corresponding alkanes. The degree of disorder
of the chains was found to be comparable to that of liquid
n-alkanes at room temperature; thus the surface of the


17
bonded phase behaves like silica with a thin oily
coating. Suffolk and Gilpin (1985) have made FTIR
measurements of a cyanoalkyl bonded phase. Here the
cyanoalkyl group could easily be observed with little
interefrence from the solvent. In hexane, there appeared
to be two distinct populations of bonded ligands (possibly
due to interaction with surface silanols), while in 1-
butanol ligand-solvent interaction was more apparent.
Other studies of the stationary phase have made use of
such diverse analytical techniques as differential scanning
calorimetry (Hansen and Callis, 1983), ESCA (Miller et al.,
1934), and photoacoustic spectroscopy (Lochmuller et al.,
1980; Miller et al., 1934). Recently, two general reviews
of stationary phase structural studies have been published
(Gilpin, 1984, 1985).
Despite the plethora of spectroscopic studies
published on the nature of the stationary phase, in no case
is a quantitative relationship derived between these
experimental results and actual chromatographic
retention. In all cases, the spectroscopic results are
interpreted in a qualitative manner.
Empirical Measures of Solvent Polarity
For any chemical process occurring in solution, the
polarity of the solvent plays a crucial role in determining
the outcome. While this has been known for many years,


18
only recently has the exact role of the solvent begun to be
clarified and quantitated. Solvent properties influence
not only the rates of chemical reactions, but also the
position of chemical equilibria. Many spectral properties
are affected by the nature of the solvent. It is well
known that both the intensity and absorption or emission
frequency of NMR, IR, UV/VIS, and luminescence spectra are
affected by the solvent. This is an example of
solvatochromism, in which the position, intensity, or shape
of a spectral peak is affected by the solvent. The
importance of solvatochromism is demonstrated quite clearly
by the Sadtler library of standard ultraviolet spectra
(Sadtler Research Laboratories, Philadelphia, PA), in which
the spectra are reported for solutes dissolved in methanol,
wherever solubility permits. In this way, peak positions
for different substances are easily compared, with no need
to correct for the effect of different solvents.
In the field of analytical chemistry, solvent effects
must be taken into account when developing a method of
analysis. Solvents will affect the position and intensity
of spectral peaks being measured in quantitative IR or
UV/VIS spectroscopy, the rates and extant of reactions used
in derivatization or titration, etc. Also, chemical
separations by liquid chromatography (either normal or
reversed phase), which are controlled primarily by the
nature of the solvent(s) used as the mobile phase, are a


19
direct result of the different polarities of the stationary
and mobile phases.
There are many ways to characterize the polarity of a
solvent. Bulk physical properties, such as dielectric
constant, viscosity, or refractive index represent the
simplest measures of solvent properties. However, no
single physical property can adequately characterize the
"polarity" of a solvent. The "polarity" of a solvent is
extremely difficult to define and represents the sum total
of all possible interactions that a solute may experience
when dissolved in a particular medium. Therefore, bulk or
macroscopic properties will only provide information about
the interaction between the solvent molecules themselves.
Interactions that a solute may experience include
dispersion, dipole-dipole, dipole-induced dipole, and
hydrogen-bond forces. Because of the difficulty of
characterizing the polarity of a solvent through bulk
physical properties, a number of empirical scales of
solvent polarity have been developed in the past 50
years. These empirical scales are based on the properties
of particular solutes dissolved in the solvent of
interest. In this way, specific, microscopic interactions
with the solvent are probed, since the test solute is able
to "see" these better than bulk, macroscopic properties
can. Extensive reviews of empirical measures of solvent


20
polarity have been published (Griffiths and Pugh, 1979;
Reichardt, 1979)
The earliest empirical scales of solvent polarity were
based on a kinetic measurement of some reaction carried out
in the solvent of interest. Perhaps the most well-known
scale of this type is the Y-scale, developed by Grunwald
and Winstein (1948). The Y-scale is based on the
solvolysis of t-butyl chloride. The rate constant for this
first order process is measured, and a Y-value is
calculated with the following equation:
log k log kQ = raY (1-5)
where k is the rate constant, kQ is the rate constant in
80# (aqueous) ethanol, and m is the sensitivity of the
substrate (m = 1 for t-butyl chloride, by definition).
There are also many empirical scales of solvent
polarity based on a spectroscopic measurement. The fact
that a solvent will influence the spectral properties of a
solute is used as a way of characterizing solvent
polarity. These measurements are quite simple and involve
nothing more than dissolving the test solute in the solvent
and recording the absorption or emission spectrum (either
IR, NMR, or UV/VIS). One example of this type of scale is
that of Xosower's Z-values (Kosower, 1958), which are based
on the interraolecular charge-transfer absorption of


21
1-methyl-4-carbomethoxypyridinium iodide. The Z-values are
defined by
Z = 28592/X (1-5)
max
where Amax Is the position of the charge transfer peak (in
nm). The constant in equation 1-6 is the product of
Avogadro's number, the speed of light, and Planck's
constant. The Z-values have been reported for more than 50
pure solvents and solvent mixtures (Kosower, 1953). For
mixtures with a high water content, the charge transfer
peak merges with that of the aromatic ring and is unable to
be located.
The it* scale of solvent polarity was developed by
Kamlet et al. (1977). Its name derives from the fact that
it is based on the positions of the it to tt* transitions of
a series of chroraophores. Rather than a single solute, it
is based on a series of aromatic solutes, in which the tt*
parameter was adjusted to give the most consistent
correlation among the various test solutes. The inventors
of this scale prefer to refer to it as the tt* scale of
solvent dipolarity/polarizability. In fact, in solvents
with no potential for hydrogen bonding, there is a linear
correlation between the molecular dipole moment and the
measured tt* value. Brady and Carr (1982, 1935) have
discussed this scale in terms of the Onsager reaction field


22
and Block and Walker dielectrically saturable reaction
field models. For a given solute, tt* values are calculated
with the following equation:
** = (v vQ)/s (1-7)
where s is the sensitivity of the solute to the it* scale,
and v and vq are the absorption maxima (X 10"^ cm-1) of the
solute in the solvent and cyclohexane, respectively. The
appropriate constants for this equation have been published
(Kamlet et al., 1977). In addition both a and B measures
of solvent hydrogen bond donor and acceptor ability have
been derived from these same solutes. These measures are
based on the enhanced solvatochromic shift of one indicator
relative to another in the presence of hydrogen bond
donor/acceptor solvents. For example, one way to measure
the 6 value is to compare the solvatochromism of 4-
nitroanisole with respect to 4-nitrophenol; solvents
capable of hydrogen bond acceptor interactions will cause
an enhanced solvatochromic shift for the 4-nitrophenol with
respect to 4-nitroanisole (Karalet and Taft, 1976). In a
similar manner, solvent a values can be derived from the
enhanced solvatochromic shift of ET-30 with respect to 4-
nitroanisole (vide infra).
The E-p(3o) scale of solvent polarity was developed in
the early 1960s by Dimroth et al. (1963a, 1963b) and


23
Reichardt (1979), who reported on the solvatochroraism of a
series of 42 pyridinium betaine dye molecules. In the
original paper, derivative #30 was found to have the
greatest sensitivity to changes in solvent polarity. Thus,
the Ef(30) scale was named as such because it is derived
from the molar energy of transition (ET) of the thirtieth
pyridinium betaine (30). The E^(30) scale of solvent
polarity is based on the intramolecular charge transfer
absorption of 2,6-Diphenyl-4-(2,4,6-triphenyl-N-pyridino)-
phenolate (structure shown in Figure 1-1). It possesses a
number of unique features, such as a 44-electron aromatic
ring system, a negatively charged phenoxide group and a
positively charged pyridine ring nitrogen atom. This
molecule undergoes one of the largest known shifts in Xmax,
amounting to some 357 nm in going from water (453 nm) to
diphenyl ether (310 nm). Since this dye absorbs within the
visible light region, it is possible to estimate visually
the polarity of a solvent. In methanol, the solution is
wine-red, while in acetonitrile the solution becomes deep
blue in color. Values of ET(30) polarity are calculated in
the same manner as are Z-values (equation 1-6) and have
been reported for over 200 solvents (Reichardt and
Harbusch-Gornert, 1983). Also, the range of the scale has
been expanded through the use of a more lipophilic betaine,
in which a t-butyl group is attached to each of the five


24
Figure 1-1. Structure of the ET-30 dye molecule, 2,6-
Diphenyl-4-(2,4,6-triphenyl-N-pyridino)-
phenolate in the ground and excited states.


25
phenyl groups (para position). Recently, a normalized
scale of Srj(30) polarity (E.j) has been defined by Reichardt
and Harbusch-Gornert (1983), in which the polarity of water
is defined to be 1.0, while that of tetramethylsilane (TMS)
is 0. These values are calculated by using the following
equation:
E (solvent) E (TMS)
N L
u Et(H20) Et(TMS) 1 ;
where E^(solvent) is the E^(30) polarity of the solvent in
question as calculated by equation 1-6, and Erptl^O) and
E.'j(TMS) have values of 63.1 and 30.7, respectively. The
normalized scale is used for convenience in expressing a
polarity relative to water or tetramethylsilane and has no
actual effect on the types of correlations discussed
herein. All E^(30) polarity values reported here are in
kcal/mole, as calculated from equation 1-6.
The Et(30) scale has been shown to be sensitive to
both solvent dipolarity/polarizability as well as solvent
hydrogen bond donor ability (HBD). Taft and Kamlet (1976)
calculated that 68$ of the shift in Xmax in going from
cyclohexane to n-butanol is due to HBD stabilization of the
ET-30. This stabilization is a direct result of the
presence of the negatively charged phenoxide group on the
ET-30 molecule. The phenoxide group acts as a hydrogen
bond acceptor, so that protic solvents may function as


26
suitable H-bond donors. In fact, Taft and Kamlet (1976)
have used the enhanced solvatochromic shift of ET-30 with
respect to 4-nitroanisole to measure the solvent hydrogen
bond donor
acidity
(a-scale).
In
both protonic
and
nonprotonic
solvents,
the E-j(30)
scale
can be related
to
the tt* and
a scales
by use of
the
following equation
(derived from equation
7 of Kamlet
et al
., 1976):
Et(30) =
30.31 + 14.
6 IT* +
16.53a (1
-9)
Analytical Applications of the ET-30 Dye
Owing to its extreme sensitivity to changes in overall
solvent polarity, ET-30 may be used to determine the
composition of binary solvent mixtures. However, ET-30 is
particularly sensitive to the presence of small amounts of
water in aprotic solvents. For protic solvents, the
presence of water has a smaller effect, as illustrated with
tert-butyl hydroperoxide. Langhals et al. (1980) have
reported that the presence of 5.2 moles/liter water changes
the apparent solution color from blue (xmax = 575 nm) to
red (Xmax = 532 nm). Thus, the color of the solution
serves as a visual indicator of the water content, and
measurement of Amax for ET-30 dissolved in a given solvent
can be a rapid and precise alternative to Karl-Fischer
water determinations. Of course, quantitation of the water


27
content for a given solvent requires that the E be known for each composition. Values of E^(30) polarity
for many binary solvent systems have been reported
(3alakrishnan and Easteal, 1931a, 1931b; De Vijlder, 1982;
Dimroth and Reichardt, 1965; Jouanne et al., 1973; Koppel
and Koppel, 1983a, 1983b; Krygowski et al., 1935;
Maksimovic et al., 1974). If the variation in ET-30 as a
function of composition is monotonic, i.e., no maxima or
minima occur, this determination is fairly
straightforward. On the other hand, if there are any
maxima or minima, this is not possible, since a given Amax
value will correspond to more than one concentration. This
would be the case, for example, for mixtures of
acetonitrile with isopropanol, as reported by Koppel and
Koppel (1983a). Langhals (1982a) has proposed the
following equation to follow changes in Erp(30) polarity
values in binary solvent mixtures:
Et(30) = Ed ln(Cp/C* + 1) + E(30) (1-10)
where Cp is the molar concentration of the most polar
component, Ed and C* are constants determined for each
binary system, and E-^(30) is the E^(30) polarity for the
least polar solvent. The appropriate constants for a total
of 46 binary solvent systems have been reported, as well as
for an organic co-polymer (Langhals, 1982a, 1982b). This


28
equation is discussed in further detail in Chapter III.
Alternatively, the change in absorbance of a solution of
ET-30 at a fixed wavelength has been used to determine
mixture composition. For example, Kumoi et al. (1970) have
reported that water concentrations of 60 yg/mL can be
detected in acetonitrile. In this case a major dis
advantage of the method is that the ET-30 concentrations
must be precisely controlled, and a calibration curve must
also be constructed for each determination.
In the examination of the polarity of aqueous micellar
media, ET-30 has also been shown to be useful. Use of
micellar solutions in analytical chemistry has increased in
recent years and has been reviewed by Cline-Love et al.
(1984). Since ET-30 is essentially insoluble in pure
water, the hydrophobic interior of aqueous micelles
provides an ideal site for solvation. Its insolubility in
water means that partitioning between the micelles and
surrounding water will not occur to a significant extent,
and thus interpretation of the spectral results is
simplified. Zachariasse et al. (1981) have reported the
use of ET-30 as a polarity probe for micelles,
microemulsions, and phospholipid bilayers. Changes in
micelle conformation (e.g., sphere-to-rod transition) were
easily detected by the discontinuity in measured E>p(30)
polarity as the concentration of sodium chloride was
increased. Also, Plieninger and Bauragartel (1983) have


29
studied the NMR spectrum of ET-30 in various surfactant
media to determine the position in which the molecule
resides in the micelles. In cationic micelles the
phenoxide group was found to be located in the rigid region
of the electrical double layer, while in anionic micelles
it is found in the diffuse layer, with the pyridinium
nitrogen atom in the rigid layer.
In addition to being used as a probe of micellar
environments, ET-30 also provides useful information about
the structure of binary solvent mixtures. For example,
Kohler et al. (1969) compared the NMR absorption spectrum
for the water proton in aqueous/organic mixtures with the
E^(30) polarity. Binary mixtures of water with either
acetone, dioxane, or tetrahydrofuran were studied, and a
linear relationship was found between the water proton
absorption peak and the measured Erp(30) polarity for the
same mixture. It must be noted, however, that the
concentration range examined was fairly small (50-95%
organic component by volume), so it is possible that
outside this range the relationship is not linear.
Balkrishnan and Easteal (1981b) have also discussed the
variation in Eij(30) polarity in binary acetonitrile/water
mixtures (see Chapter II).
Heats of solution at infinite dilution have been
correlated with the Ex(30) polarity scale by Ilic and
coworkers (1984). A linear relationship was found between


30
a solute's ET(30) polarity and its heat of solution.
Solutes that were studied included n-alkyl ketones, n-
alcohols, and di-n-alkyl ethers. The heats of solution of
these solutes were measured in solvents such as n-hexane,
carbon tetrachloride, benzene, etc. None of the solvents
were capable of hydrogen bonding with the solutes, however,
and thus the results cannot be generalized to include every
solute/solvent system. Also, heats of solution were
measured only in pure solvents, rather than mixtures. In
addition, this type of correlation would not be possible
for solid compounds, since it is not possible to measure
their Et(30) polarity. Of course, it might be possible to
estimate the Eij(30) polarity for solid compounds by using
heat of solution measurements, as Fuchs and Stephenson
(1983) have done for the n* dipolarity/polarizability of
solid compounds.
The Et(30) scale of solvent polarity has been applied
to chromatographic systems in a number of ways. The
applications discussed here include supercritical fluid
chromatography and normal phase liquid chromatography
(NPLC). These types of investigations can provide
information about either the mobile phase (solvent
polarity) or the stationary phase (surface polarity).
For example, the E^(30) polarity of a mobile phase
used in supercritical-fluid chromatography (3FC) has been
reported (Hyatt, 1984). Typical mobile phases used in SFC


31
are compressed gases such as carbon dioxide or ammonia, at
a temperature greater than their critical point. Hyatt
calculated the Ej>(30) polarity of both sub- and
supercritical carbon dioxide to be 33.8 kcal/mole, by using
the more lipophilic penta(tert-butyl) derivative of ET-30
(Reichardt and Harbusch-Gornert, 1983). It was necessary
to use the more lipophilic compound due to the low
solubility of ET-30 in supercritical CO2. An E^(30)
polarity of 33.8 kcal/mole is comparable to that of either
toluene or tetrachloroethylene. However, the strength of
the mobile phases used in SFC is controlled by the pressure
(and resultant density). The E supercritical CO2 was reported for only one pressure (1000
PSI) and temperature (42C), and thus it is likely that a
different polarity would result for different pressures
(densities). For example, Sigman et al. (1985) measured
the it* dipolarity/polarizability and B (hydrogen bonding
basicity) for supercritical CO2, which were found to be
highly dependent on the density. Since these measurements
are also based on the use of solvatochromic dyes, it is
likely that the ET(30) polarity would also be greatly
affected by a change in the CO2 pressure. Thus, useful
information would be provided by performing the same
experiments with the more lipophilic, t-butyl derivatized
betaine. Levy and Ritchey (1935) have reported on the
effects of adding small amounts of additives such as


32
methanol or acetonitrile to the mobile phase in SFC. In
theory, E-p(30) polarity of these binary mixtures could also
be measured.
The polarity of silica surfaces used in normal phase
liquid chromatography was examined (Lindley et al.,
1985). In this case, the diffuse reflectance spectrum of
the betaine adsorbed onto the silica was measured. The
peak corresponding to minimum reflectance was used, in
conjunction with that of 4-nitroanisole, to calculate a, a
measure of the acidity of the silica surface. The silica
surface was found to be a strong hydrogen bond donor. The
degree of the dye loading also influenced the measured
values, which decreased at higher levels, apparently as a
result of the formation of more than a monolayer of the
test solutes on the silica surface. None of these
experiments were done in the presence of a mobile phase,
however, most likely because the ST-30 is quite soluble in
typical mobile phases used in NPLC (such as those
containing dichlororaethane).
Another interesting application of E^(30) polarity
measurements involves Snyder's eluent strength parameters
for solvents used in normal phase liquid chromatography.
Krygowski et al. (1981) compared the ET(30) polarity of
various pure solvents with Snyder's eluent strength
parameter ( e)
In this case, it was necessary to


33
incorporate a second parameter, B^rp (Karalet/Taft basicity),
in order to predict the s values. Also, only pure
solvents were treated, rather than the binary or ternary
mixtures typically used in normal phase liquid
chromatography.
To date there have been no comparisons made between
empirical measurements of mobile phase polarity and
chromatographic retention or selectivity. In reversed
phase chromatographic experiments, it is often assumed that
the strength of the mobile phase varies linearly with the
percentage of organic modifier. In this dissertation, the
results of empirical solvent polarity measurements of the
most commonly used mobile phases are discussed, as well as
the correlation between these measurements and
chromatographic retention and selectivity.


CHAPTER II
SOLVATOCHROMIC SOLVENT
POLARITY MEASUREMENTS
Experimental
E^(3Q)-Value Measurements
A sample of the ET-30 was kindly provided by Professor
Christian Reichardt of Philipps-Universitat Marburg,
Federal Republic of Germany. The synthesis of ET-30, which
is not commercially available, is reported elsewhere
(Dimroth et al., 1963b). Binary solvent mixtures were
generated by a Spectra-Physics Model SP8700 ternary
proportioning LC system. Degassing was achieved by
sparging the solvents vigorously with helium. Both HPLC
grade methanol and acetonitrile (Fisher Scientific, Fair
Lawn, NJ) were used as received. Water was first purified
with a Barnstead Nanopure system (Boston, MA) and then
irradiated with UV light in a Photronix Model 816 H.P.L.C.
reservoir (Photronix Corp., Medway, MA) for at least 24
hours. The water was then filtered through a 0.45
micrometer Nylon-66 membrane filter (Rainin Instruments,
Woburn, MA) prior to use.
After collecting 3 mL of a given solvent mixture in a
1 cm path length quartz cell, approximately 0.3 rag of ET-30
34


35
was added, and a spectrum was obtained with a Hewlett-
Packard Model 8450A diode array spectrophotometer.
Wavelength accuracy of the instrument was checked with a
Holmiura Oxide interference filter. Spectra were acquired
at 252C. In pure methanol, the change in Xmax is 10 nm
for a temperature change from 25 to 55C (Diraroth et al.,
1963a). Thus, a 2 degree variation leads to an
uncertainty in E kcal/raole. The "peak-find" function of the instrument was
used to determine Xmax* For each solvent mixture, ten
spectra were acquired at one second integration time, and
the resultant X x values averaged. The pooled standard
deviation for 620 Xraax measurements was found to be
1.16 nm. Values of Erj,(30) polarity were calculated from
Xmax data by using equation 1-6.
As with many dye molecules, the possibility of
dimerization of the ST-30 exists. Since E zwitterionic form, dimerization would be favored through
interaction between oppositely aligned molecules.
Dimerization would lead to a dependence of *max upon its
concentration, as well as nonlinearity of a Beer's law
plot. It has been reported that Beer's law is obeyed for
concentrations in the range of 10-t^ to 10-0^ M (Diraroth
and Reichardt, 1966); all sample concentrations were in
this range. As a further check, the concentration of ST-30


36
in 45/35/10 MeOH/ACN/t^O was varied, and Amax and
absorbance at imax measured. These data are shown in Table
2-1 and are plotted in Figure 2-1. No dependence of imax
on ET-30 concentration was observed. Also, Beer's law was
obeyed over the concentration range studied.
Table 2-1.
Effect of varying ET-30 concentration on A and
absorbance in 45/35/20 (v/v/v) MeOH/ACN/l^O.
Cone. (mg/mL) *max Absorbance
0.13
508.5
0.2757
0.26
508.3
0.6901
0.33
508.3
1.111
0.52
509.5
1.498
0.65
508.4
1.914
Values of Erp(30) have been previously reported for
these same solvent mixtures (Dimroth and Reichardt, 1966;
Krygowski et al., 1985); however, in these cases mixtures
were prepared by adding water to the organic solvent to
attain a fixed total volume. In contrast, LC pumps
typically mix solvents on the basis of additive volume.
For example, 100 raL of 50/50 (v/v) mixture of
methanol/water (as delivered by an LC pump) is comprised of
50 mL methanol to which 50 mL water is added. Excess
volumes of mixing lead to slight differences in solvent
composition and resultant ET(30) polarity values, so these


37
Figure 2-1. Beer's law plot for ET-30 dissolved
45/30/10 methanol/acetonitrile/water (v/v/v)
in


38
measurements were made with solvent mixtures generated with
the LC pump system itself.
tt*-Value Measurements
Measurements of tt* values were made with 4-
nitroanisole (Aldrich Chemical Co., Milwaukee, 41) and
using the following equation from Kamlet et al. (1977):
TT
*
( V
max
vQ)/2.343
(2-1)
where vmax is the observed maximum in wavenumbers (X 10-0^
cra-^ ) and vq is the value for the solute in cyclohexane
(it* = 0 in cyclohexane, by definition). This reference
(Kamlet et al., 1977) lists a number of solutes (for
example, 4-ethylnitrobenzene) that can be used to measure
the tt* dipolarity/polarizability; 4-nitroanisole was chosen
because of its low sensitivity to hydrogen bond
donor/acceptor effects. In this case the 4-nitroanisole
was added to the water at a concentration of 5 Mg/mL, and
the resulting solvent mixture + solute was passed through a
0.25 mL Hellraa flow cell therraostatted at 400.1C with a
Haake Model D1 water bath (Haake, Saddle Brook, NJ). Flow
was stopped while acquiring spectra to equilibrate the
temperature of the mixture and reduce the effect of
refractive index variability in the sample.
Because of the very small wavelength shift observed
with this substance in going from pure organic to pure


39
water (*max of 9 nra between water and acetonitrile), the
following algorithm was used to evaluate *max* Spectra
were acquired, and the absorbance recorded at each
wavelength (1 nm readout resolution). Next the absorbance
data were fit with a 3rd degree polynomial using the
program "Curve Fitter" (see Appendix C; this algorithm was
suggested by Savitizky and Golay, 1964). The first
derivative (dy/dx) of the resultant polynomial was then
used to evaluate *max (by setting this equal to zero and
solving for Xraax with the quadratic formula). Repeated
calculations with either the entire data set (30 points;
30 nm wide) or only five points (Xraax-10, Xraax'5, Xmax,
*max+5 Xmax+^^ showed that only five were needed to
define the spectral peak accurately. By interpolating the
spectral peak position in this manner, the precision of
Vax measureraent was greatly improved. As an illustration
of the utility of this algorithm, in Table 2-2 and Figures
2-2 and 2-3, the effect of temperature on the peak position
of 4-nitroanisole in 33.3/33.3/33.4 (v/v/v) MeOH/ACN/^O is
shown. Data of Xmax provided directly by the instrument or
that from interpolation (of the same spectral data set) are
plotted in Figures 2-2 and 2-3, respectively. The data
clearly indicate that thermochroraism of 4-nitroanisole is
not observable without the use of this algorithm.


40
Absorbance
Maximum
(nm)
Figure 2-2.
Temperature (C)
Therraochroraism of 4-nitroanisole in
33.3/33.3/33.4 methanol/water/acetonitrile
(v/v/v). Wavelengths obtained directly from
the diode array spectrophotometer.


41
31 1 .4 -r
311.2 -
Interpolated
Absorbance
31 1 .0 -
Maximum
(nm)
310.8 -
310.6 -
30
Temperature (C)
Figure 2-3. Therraochroraism of 4-nitroanisole in
33.3/33.3/33.4 methanol/water/acetonitrile
(v/v/v). Wavelengths obtained by
interpolation of absorbance data from the
diode array spectrophotometer.
70


42
Table 2-2.
Thermochromism of 4-nitroanisole in
33.3/33.3/33.4 (v/v/v) Me0H/ACN/H20.
Temperature Vax Xmax
(C) directly (interpolated)
40.0
312
311.4
45.0
311
311.2
50.0
311
311.1
55.0
312
310.9
60.0
312
310.8
Spectra of 4-nitroethylbenzene and 4-nitrophenol were
also acquired in the same manner in raethanol/water and
acetonitrile/water mixtures, in connection with the
measurement of solvent a and 3 values (not utilized in the
present discussion; results tabulated in Appendix D).
Results
iT*-Values
While the primary purpose of this research was to
investigate the Eij(30) polarity scale in regard to
chromatographic retention, measurements were also done for
the it* scale of solvent dipolarity/polarizability in binary
hydro-organic mobile phases.
In Figure 2-4, a representative spectrum for 4-nitro
anisole in methanol is shown. One advantage of the use of
this scale is that the spectral peak of interest (due to
the nitro group) is widely separated from that of the


ABSORBANCE
43
WAVELENGTH (ni.)
Figure 2-4. Representative UV/VIS absorbance spectrum of
4-nitroanisole in methanol. Concentrations
for the two curves are top, 0.1 mg/mL; bottom,
0.02 mg/mL.


44
aromatic ^-electron system. As discussed in Chapter I,
overlap of peaks can be a problem, as best exemplified with
Z-values (Kosower, 1958), in which the charge transfer peak
merges with that of the pyridine ring in highly aqueous
mixtures.
The results of dipolarity/polarizability
measurements for binary methanol/water mixtures appear in
Figures 2-5 and 2-6. In terms of percentage methanol
(Figure 2-5), the ** values are seen to decrease steadily,
in a highly nonlinear fashion. However, when the data are
plotted versus mole fraction of methanol (Figure 2-6), a
nearly straight line results (r- = 0.9959, s = 0.0119).
In Figures 2-7 and 2-8, the corresponding measurements
for the acetonitrile/water solvent mixtures are depicted.
Here the variation is much more complex; this is especially
true when compared to percentage of acetonitrile (Figure
2-7), where there are at least two points of inflection at
approximately the 30 and 70% concentrations. In contrast
to methanol/water mixtures, the variation with respect to
mole fraction of acetonitrile (Figure 2-8) is seen to be
highly nonlinear.
The ** scale of solvent dipolarity/polarizability is
distinctly different from the E^(30) scale in that it is
specifically intended to exclude hydrogen bond
donor/acceptor effects. As such these results then show


45
% Methanol
Figure 2-5. Measurements of u* dipolarity/polarizability
for methanol/water mixtures with respect to
percent methanol.


46
Figure 2-6. Measurements of ir* dipolarity/polarizability
for methanol/water mixtures with respect to
mole fraction of methanol.


47
% Acetonitrile
Figure 2-7. Measurements of ir* dipolarity/polarizability
for acetonitrile/water mixtures with respect
to percent acetonitrile.


48
1.2
1.1
1 .0
JJ -X- 0.9
0.8
0.7
0.6
0.0 0.2 0.4 0.6 0.8 1.0
* Acetonitri le
Figure 2-8. Measurements of n* dipolarity/polarizability
for acetonitrile/water mixtures with respect
to mole fraction of acetonitrile.


49
the variation in polarity due only to dipole/dipole,
dipole/induced dipole, and dispersion interactions. Thus
it is not surprising that at 100# organic concentration,
methanol is actually less, polar than acetonitrile ("*
values of 0.57 and 0.67, respectively). This is a direct
reflection of the fact that the nitrile bond of
acetonitrile is much more dipolar in nature than either the
C-0 or 0-H bonds of methanol. Kamlet et al. (1983) have
reported it* values of 0.60 and 0.75 for methanol and
acetonitrile, respectively. These compare with the values
reported here of 0.57 and 0.67 for the cor responding
solvents. This discrepancy between the values reported by
Kamlet et al. and shown here is not significant, however.
In the present work, n* values were calculated from
measurements obtained with one solute (4-nitroanisole) ,
while those reported by Kamlet et al. (1983) are actually
the values that lead to the most consistent result from
several test solutes. In fact, in the original paper
describing the ir* scale, Kamlet et al. (1977) reported
values of 0.58 and 0.71 for methanol and acetonitrile,
respectively.
Based solely on the ir* scale, one would conclude that
methanol should be a stronger (less polar) organic modifier
for RPLC. However, this conclusion does not agree with the
known properties of the two organic modifiers, since
acetonitrile behaves as a more nonpolar, hence stronger,


50
solvent in RPLC. Also, one would expect (based on tt*
values) that methanol would solvate the stationary phase
alkyl chains to a greater extent, which, again, is simply
not consistent with the known properties of the two
modifiers (as discussed in Chapters I and V).
Erp( 30)-Values
A representative spectrum for ET-30 dissolved in pure
methanol is shown in Figure 2-9. The very large absorption
at wavelengths less than 400 nm is due to the aromatic ir-
electron system. In pure water, Araax decreases to 453 nm
(Dimroth et al., 1963a; a 10 cm path length cell was
used). It was not possible to obtain spectra of E pure water (due to its extremely low solubility; <10-0^ M),
so this
value has been
used
in the following figures.
In
Figures 2-10
and
2-11, the
Erji (30)-values
are
plotted
with respect
to
percent and
mole fraction
of
methanol
, respectively

In Figures 2
-12 and 2-13,
the
corresponding results
for
acetonitrile/water mixtures
are
shown.
With both organic modifiers, the ET(30) polarity is
clearly a nonlinear function of composition; this is not
surprising since none of the solvents form thermo
dynamically ideal solutions. For a thermodynamically ideal
binary solvent mixture, any bulk physical property, such a
dielectric constant or viscosity, is expected to be a


ABSORBANCE
51
Figure 2-9.
Representative UV/VIS absorption spectrum of
the ET-30 dye dissolved in methanol.


52
Et(30)
Measurements of Eij(30) polarity for methanol/
water mixtures with respect to percent
methanol.
Figure 2-10.


53
Et(30)
Figure 2-11.
Measurements of Ej.(30) polarity for methanol/
water mixtures with respect to mole fraction
of methanol.


54
Figure 2-12. Measurements of Erp(30) polarity for aceto
nitrile/water mixtures with respect to
percent acetonitrile.


55
Figure 2-13. Measurements of Erp(30) polarity for aceto
nitrile/water mixtures with respect to mole
fraction of acetonitrile.


55
linear function of the mole fraction of either component.
This is also the case for empirical solvent polarity
measurements. For example, this was reported to be true
for the Srp(30) polarity of binary mixtures of 1,2-
dibroraoethane and 1 ,2-dibromopropane, whose mixtures obey
Raoult's law, demonstrating ideal solution behavior
(Balakrishnan and Easteal, 1981a).
That raethanol/water and acetonitrile/water mixtures
are not ideal solutions is also evidenced by the nonlinear
variation in viscosity and dielectric constant (Horvath and
Melander, 1977). Thus, it is not surprising that the
measured E,j(30) polarity varies in a highly nonlinear
manner versus either percent or mole fraction of organic
component. The nonlinearity of these diverse properties
also illustrates the danger of assuming strictly additive
solvent properties, as is done in the derivation of both
liquid chromatographic retention models and gradient
elution schemes. It should also be pointed out here that
in gas chromatography, blending of stationary phase
materials can be done with this assumption in mind. This
is a reflection of the fact that these phases are almost
always nonpolar or weakly polar, nonhydrogen bonding
materials, and thus mixtures are nearly ideal in a
thermodynamic sense (Chien et al., 1980). Also, the mobile
phases used in gas chromatography are nearly inert gases


57
(hydrogen, helium, or nitrogen) and do not solvate the
stationary phase.
It is apparent that the variation in polarity of the
two systems is quite different. The different character of
these curves is a reflection of the differing hydrogen
bonding abilities of the two organic solvents. In the case
of acetonitrile, it is obvious that for concentrations
greater than 80# (by volume), the measured polarity
decreases rapidly.
Balakrishnan and Easteal (1931b) have discussed the
variation in E^(30) polarity in acetonitrile/water mixtures
and have found it to be consistent with the Naberukhin-
Rogov model (1971) for binary mixtures of water with a
nonelectrolyte. The Naberukhin-Rogov model describes the
structure in terras of two microphases (a and g) at
concentrations of greater than 0.15 (mole fraction) of
acetonitrile. The a phase consists primarily of highly
structured water, while microphase g contains mostly
acetonitrile. At concentrations of greater than 0.6,
Balakrishnan and Easteal (1981b) postulated that the g
microphase predominates, and the water exists as single
molecules coordinated to these "globules" of
acetonitrile. Further evidence of the existence of
microphases is the phase separation that occurs in this
system, at a critical temperature and concentration of
272 K and 33 mole # acetonitrile, respectively.


58
Unlike methanol, acetonitrile is a very weak hydrogen
bond donor solvent and thus as the concentration is
increased, the remaining water becomes specifically
associated with the ET-30 due to the presence of the
negatively charged phenoxide group. As the water is
completely removed, and the ET-30 is no longer stabilized
through this hydrogen-bonded network, the apparent polarity
plunges 46.0 kcal/mole. This large change in E.j(30)
polarity is not mirrored by the changes seen in log x'
retention measurements. Retention data for concentrations
greater than 80$ have not been included in the present data
analysis. There were 61 cases among these data sets where
the 90% acetonitrile point was not included; these were all
from one reference (Hanai and Hubert, 1933). It must also
be pointed out, however, that at these concentrations the
retention time will be very short for most solutes, so that
the resultant k' (approaching zero) and log k' values
(approaching minus infinity) will have the highest relative
uncertainty of the entire retention data set. In fact, the
average log k' for the 61 (90$ acetonitrile) points not
included was 0.049 (s = 0.089), corresponding to an average
k' of 1.12.


59
Relationship Between Snyder's P1 Polarity Values
and the Ern(50) Scale-
Snyder (1974, 1978) has devised the P' scale of
solvent polarity for use in characterizing solvents used in
liquid chromatography. These values are based on
gas/liquid partition coefficients for various solutes and
solvents reported in the literature (Rohrschneider,
1973). For each solvent, the logarithm of the corrected
partition coefficients (K"; corrected to account for
differences in molecular volume and concentration units)
for ethanol, dioxane, and nitroraethane are summed together
to calculate a P' polarity as shown below:
P' = log K"(1,4-dioxane) + log K"(ethanol)
+ log K"(nitroraethane) (2-2)
In this manner, the solvents ability to undergo three
types of interactions (proton donor/acceptor, polar) with
solutes is measured, and P' values then represent the total
of these potential interactions. Snyder also reported the
fractional contribution of each of the three test solutes
(Xe> X^, Xn parameters) to the overall P' value. Using
these partial contribution values, Snyder classified all
solvents into eight possible categories. This
classification is often referred to as Snyder's solvent


50
selectivity triangle, in that three characteristics (proton
donor, proton acceptor, and polar) are assigned to each of
the three vertices of a triangle). Each solvent can then
be placed into a unique position within this triangle on
the basis of its Xe, X^j, and Xn values.
Since Snyder's classification scheme is intended to be
useful for the measurement of solvent selectivity in liquid
chromatography, it is worthwhile to examine briefly the
relationship (if any) between the P' and Ej.(30) scales of
solvent polarity. The relationship between Snyder's eluent
strength parameters for NPLC and Erj(30) polarity has
already been discussed in Chapter I.
The easiest comparison that can be made is between the
P' (summed polarity) values reported by Snyder (1978) and
Eq>(30) polarity values for pure solvents reported by
Reichardt and Harbusch-Gornert (1983). There were 48 cases
in which tnis comparison could be made; the resultant
comparison plot is shown in Figure 2-14. While there is a
statistically significant correlation between the two sets
(r = 0.7986), there is also a great deal of scatter around
the line (s = 1.1146), so Erj(30) values cannot be used to
accurately predict P' values or vice versa. The line drawn
through the data (using linear regression) in Figure 2-14
has a slope of 0.18510.04 and y-intercept of -3.541.34.
That there is such a poor correlation is not
surprising, since the P' values represent the summation of


61
Figure 2-14. Comparison between Snyder's P' and Dimroth-
Reichardt's Erp(30) polarity values for pure
solvents.


62
the three interactions in proportions that will not
necessarily be similar to the responsiveness of the ET-30
probe. Also, it should be noted that according to the ?
scale, methanol is a stronger organic modifier for RPLC (?'
= 5.1) than acetonitrile (P1 = 5.8), which is not in
agreement with the known chromatographic properties of
these two solvents.
Perhaps a better way to compare these scales is to
compare E>j(30) polarity values with the partial
contribution values (X9, Xd, and Xn) by using multiple
linear regression. This should allow the various
contributions to be more properly weighted. However, it
must be remembered that these partial values represent the
fraction of the total P' value for each solvent and will
always add up to one. Thus, the true magnitude of each of
the three interactions is masked, and to make a valid
comparison, one must first multiply each partial
contribution value by the total P' value for each
solvent. Using multiple linear regression, an attempt was
made to correlate each E^(30) value with the three
corrected partial contributions for the same solvent. For
the 48 cases, the multiple correlation coefficient was
found to be 0.3912, with a standard deviation of 3.685.
The equation relating the Eij(30) to the three interactions
was


63
Et(30) = 29.93.8 + 7.83+1.8 X + 2.3+2.6
- 1.792.9 X (2-3)
The regression coefficients indicate that the E^(30)
scale is significantly related to only the terms derived
from the partition coefficients for ethanol and dioxane.
These results are shown graphically in Figure 2-15, where
the Et(30) values predicted by equation 2-3 are plotted
with respect to actual reported ET(30) polarity values
(Reichardt and Harbusch-Gornert, 1983). It is interesting
to note that this multiple linear regression leads to a
poorer standard deviation (s = 3.86) than obtained by
plotting the original P' versus E.j(30) values (s = 1.11).


64
Et(30)
(predicted)
Figure 2-15.
Et(30) (Actual)
Comparison between E predicted by equation 2-3 and actual ET(30)
polarity values reported by Reichardt and
Harbusch-Gornert (1983).


CHAPTER III
CORRELATIONS BETWEEN CHROMATOGRAPHIC
RETENTION AND MOBILE PHASE POLARITY
Experimental
Retention measurements (other than those reported in
the literature) were obtained with a Spectra-Physics SP8700
ternary proportioning LC system (Spectra-Physics, San Jose,
CA). Columns were an Altex Ultrasphere ODS (5 micron
particle size; Altex Scientific, San Ramon, CA) and a
Hamilton PRP-1 (10 micron; Hamilton Company, Reno, NV).
Both columns were of size 15 cm X 4.6 mm I.D. Test solutes
were obtained from Aldrich Chemical Co. (Milwaukee, WI) and
the Eastman Kodak Co. (Rochester, NY). Sample introduction
was achieved with either an Altex injector equipped with a
5 microliter sample loop (Altex Scientific, San Ramon, CA)
or a Rheodyne Model 7125 injector equipped with a 20
microliter sample loop (Rheodyne, Inc., Cotati, CA). Plow
rates were either 1.0 or 2.0 mL/min. The column was
therraostatted at 400.1C with a Haake Model D1 water bath
(Haake, Saddle Brook, NJ). Solvents were obtained as
described previously (Experimental, Chapter II). A fixed
wavelength, 254 nm, Beckman Model 153 UV detector (Altex
Scientific, San Ramon, CA) was used.
65


oS
The retention times for an unretained species (tQ)
were evaluated with injections of the pure organic solvent
(either methanol or acetonitrile). For the Hamilton PRP-1
column, this proved to be difficult at low organic modifier
concentrations due to actual retention of the acetonitrile
or methanol. Other supposedly unretained solutes (such as
urea and uracil) exhibited similar behavior. Therefore,
the tQ obtained from injections of pure organic modifier at
60% organic modifier concentration was used, since at this
concentration the retention time reached a minimum in each
of the two solvent systems.
Simple linear regression calculations were done with
the program "Curve Fitter" (Interactive Microware, Inc.,
State College, PA) run on an Apple II Plus 43K
microcomputer (Apple Computer, Inc., Cupertino, CA). The
program was modified to allow calculation of 95$ confidence
intervals
for
slope
and y-intercept values.
This
program
was also
use
d to
interpolate E^(30) values
for
solvent
compositions
that
had not been measured
(e.g
., 45$
methanol/water).
When curve fitting the data to either a linear or 2nd
degree polynomial, the resultant standard deviations
(s-values) were used to calculated an F-ratio as
F = s(linear)/s(2nd degree polynomial)
(3-1)


67
The significance level (<*% values reported in Table
3-1) of a given F-ratio was then determined by using the
program "F Distribution" (public domain software provided
by Computer Learning Center, Tacoma, WA). In this way,
much more accurate estimates of the significance level were
obtained than those from published F-distribution
statistical tables.
.Multiple linear regression calculations were done by
using the program "Statworks" (Datametrics, Inc., and
Heyden and Son Limited, Philadelphia, PA), run on a
Macintosh 512K computer (Apple Computer, Inc., Cupertino,
CA).
Results
In RPLC, retention of solutes decreases as the
concentration of organic modifier is increased. That is,
as the overall polarity of the mobile phase is decreased,
solutes will spend less time in the stationary phase. Of
course, there are many ways to express this decrease in
polarity; the simplest measure of this is the proportion of
the organic modifier. Traditionally, chromatographers have
measured capacity factors at various organic modifier
concentrations and then plotted the logarithm (base 10) of
the capacity factor as a function of this concentration.
In the present discussion, the abbreviation "log" shall
denote the base ten logarithm. Plotting the logarithm of


68
capacity factor is quite logical, owing to its dependence
on the free energy of transfer (AG) of the solute between
the mobile and stationary phases. This relationship is
expressed by the following equation:
log k' = (-2.303 AG/RT) + log(<|>) (3-2)
where

Thus, plotting log k' versus percent organic modifier gives
a sense of the change in the energetics of chromatographic
retention as the composition of the mobile phase is
changed. Whether or not this type of plot is linear in
nature has been the subject of much debate. In terms of
concentration, the only reason that percent organic
modifier is usually used is that all chromatographic
instrumentation has been built to deliver mixtures by
volume percentage. While plots of log k' versus percent
organic modifier often appear to be linear, they will
always exhibit some curvature if a wide enough
concentration range is investigated and are best fit by a
quadratic equation (Schoenmakers et al., 1933). To
illustrate this point, in Figure 3-1, retention data for 4-
nitrophenol have been plotted with respect to percent
organic modifier. If the data are fitted with a straight
line, a squared correlation coefficient of 0.9803 is found,
while a quadratic curve-fitting leads to an increase to


59
0.9983. Clearly, the variation in the log k' values is
best accounted for by an equation containing a quadratic
term.
From a physical standpoint, it would be much more
logical to plot the retention data with respect to the mole
fraction of organic modifier. That is, solution properties
(of which reversed phase chromatographic retention can be
considered to be a result of) are best expressed by
observing the property as a function of mole fraction. In
such cases, deviations from linearity are then (by
definition) deviations from nonideal solution behavior.
The extent to which plotting log k' values versus
either volume percent or mole fraction or organic modifier
can affect the curve shape is illustrated in Figures 3-2
and 3-3. For both methanol and acetonitrile, the mole
fraction has been plotted with respect to percent of
organic modifier. In both cases, the actual mole percent
is significantly lower than the percent by volume at all
concentrations (except, of course, at the 0 and 100%
points). Using the same log k* values shown in Figure 3-1,
the data have been re-plotted with respect to the mole
fraction of acetonitrile in Figure 3-4. Here the curvature
has been accentuated, and a straight line fit of the data
yields a r~ of 0.9332. Since the variation in mobile phase
strength is not necessarily directly related to the percent
(by volume) or the mole fraction, a more logical approach


70
would be to compare retention with experimentally derived
measures of mobile phase polarity, such as the u* and
E^(30) values. In Figure 3-5, log k' values for 4-
nitrophenol (same values as used in Figures 3-1 and 3-4)
are plotted with respect to the tr* values for the same
composition (ir*-values discussed in Chapter II). In this
case, there is a point of inflection, and the data are best
fit by a 3rd degree polynomial. As discussed in Chapter
II, one would not expect the tt* scale to correlate well
with chromatographic retention, owing to its insensitivity
(by design) to hydrogen bonding effects in solution. This
is clearly reflected by the data shown in Figure 3-5. A
straight line fit of the data results in a squared
correlation coefficient of 0.9667.
The E^(30) values discussed in Chapter II can also be
compared with chromatographic retention. The ET(30) scale
has been shown to be sensitive to both hydrogen bonding and
dipolarity effects (as discussed in Chapter I) and thus may
serve as a better indicator of the strength of the mobile
phases used in RPLC. In Figure 3-6, retention data used in
previous figures have been plotted with respect to the
measured E^OO) polarity for the same mobile phase
composition. In this case, the linearity is much greater,
yielding a square correlation coefficient of 0.9950 when
fitted to a straight line model. This is in great contrast


71
Figure 3-1.
Retention data for 4-nitrophenol plotted with
respect to percent acetonitrile. Ultrasphere
ODS (C18) column; flow rate 1.0 mL/min.


72
O 20 40 60 80 100
% Methanol
Figure 3-2. Variation in mole fraction of methanol as a
function of volume percent.


73
Figure 3-3. Variation in mole fraction of acetonitrile as
a function of volume percent.


74
y
Acetonitrile
Figure 3-4. Retention data for 4-nitrophenol plotted with
respect to mole fraction of acetonitrile.
Ultrasphere ODS (C-18) column; flow rate 1.0
mL/min.


75
Retention data for 4-nitrophenol plotted with
respect to ir dipolarity/polarizabi 1 ity for
the same solvent mixtures. Ultrasphere ODS
(C-18) column; flow rate 1.0 mL/min.
Figure 3-5.


76
Et(30)
Retention data for 4-nitrophenol plotted with
respect to the E.p(30) polarity for the same
solvent mixtures. Ultrasphere ODS (C-18)
column; flow rate 1.0 mL/min.
Figure 3-6.


77
to the other three values for Figures 3-1, 3-4, and 3-5, of
0.9803, 0.9332, and 0.9667. The best fit is obtained when
the log k' values are plotted with respect to the measured
E^(30) polarity for the same mobile phase mixture.
Of course, the previous figures pertain to only one
individual set of retention data generated for this
research; in order to make any generalizations about the
correlations between the various variables, it is necessary
to examine a large body of chromatographic data. A total
of 332 sets of chromatographic retention data (log k*
versus percent organic modifier) have been examined.
Retention data reported in the literature, as well as data
generated exclusively for this study, have been included in
these correlations. Hereafter the discussion will be
confined to two types of correlations: those between log
k' and either percent organic modifier or ET(30) polarity.
Linear regression was carried out for all retention
data sets with the log k' data compared to both percent
organic modifier and the ET(30) polarity. The results of
these correlations are compiled in Table 3-1. The data
have been sorted in a hierarchical manner, using the
following sequence: organic modifier, column, and
solute. Squared correlation coefficients (r^) for both log
k' versus organic modifier and E>p(30) polarity are
reported, as well as the regression coefficients for the


Table 3-1 .
Linear regression results for correlations between log k' and either percent organic
modifier or E.p(30) polarity.
column
Solvent/% Range
r2 vs. %
r2 vs. Et
(30) Slope(xl02)
-ly-int)

n
ba*
Reference
1
2-N1troanlline
r
A
ACN/10-60
0.9069
0.9909
23.413.1
13.211.0
0.0490
6
This Work
2
4-Nltroanllino
A
ACN/10-60
0.9865
0.9903
2O.02.8
11 .911 .7
0.0456
6
This Work
1
4-N1trophonol
A
ACN/10-60
0.9803
0.9940
24.512 .4
13.911.4
0.0391
6
This Work
4
4-N1 troanlsolo
A
ACN/10-80
0.9874
0.9859
31.113.7
17.312.1
0.0870
8
99.2
This Work
5
Benzene
A
ACN/31.3-68.7
0.9957
0.9947
34.517.6
19.014.3
0.0342
4
This Work
6
Butylbenzene
A
ACN/31 .3-68.7
0.9870
0.9999
60.2H .9
32.711.1
0.009
4
This Work
7
Ethylbenzene
A
ACN/31.3-68.7
0.9912
0.9988
47.215.1
25.812.9
0.0219
4
This Work
8
Isopropylbenzene
A
ACN/31.3-68.7
0.9900
0.9992
52.314.4
20.512.5
0.0203
4
This Work
9
Anthracene
A
ACN/40-77.5
0.9883
0.9937
61.915.4
33.9t 3 .0
0.0467
6
Thl6 Work
10
Phenanthrene
A
ACN/40-77.5
0.9868
0.9949
60.014.7
32 .912 .6
0.0405
6
This Work
11
Pyrene
A
ACN/40-77.5
0.9842
0.9962
62.514.2
34.02.4
0.0366
6
This Work
12
Toluene
A
ACN/31.3-68.7
0.9937
0.9973
40.916.6
22.513.0
0.0291
4
This Work
13
Anthracene
A
ACN/50-80
0.9893
0.9949
68.015.6
37.313.1
0.0296
7
Lipford (1905)
14
Napthalene
A
ACN/50-80
0.9991
0.9894
55.4i6.6
30.513.7
0.0347
7
83.3
"
15
1,2-Dlhydroxybenzono
G
ACN/10-80
0.9110
0.9927
15.911.4
8.8810.78
0.0319
8
Hanai and Hubert
16
1 ,3-Dlhydroxybenzeno
G
ACN/10-80
0.8964
0.9079
14.OH .6
7.9010.09
0.0364
8
95.1
"
17
1 ,4-Dlhydroxybenzeno
G
ACN/10-80
0.9103
0.9903
10.Ill.0
5.7510.57
0.0234
0
"
18
2-Hydroxyacetophenone
G
ACN/10-80
0.8792
0.9021
19.612.6
10.9H .5
0.0620
0
90.5
"
19
4-Me thylphenol
G
ACN/10-80
0.9427
0.9976
27.111 .3
14.910.76
0.0310
0
M
20
4-Nitrophenol
G
ACN/10-80
0.9414
0.9965
26.9i3 .3
14.9i1.9
0.0372
a
"
21
Phenol
G
ACN/10-80
0.9480
0.9975
20.9H .0
11,60.60
0.0366
0
22
2,4-Dlnltrophenol
G
ACN/20-80
0.9652
0.9942
31.112.7
17.U1 .6
0 .0426
7
21
2,5-Dinitrophenol
G
ACN/20-80
0.9690
0.9933
31.8l3 .0
17.Si 1*7
0.0460
7
"
24
2,6-Dlnitrophenol
G
ACN/20-80
0.9754
0.9918
29.4i3.1
16.211.8
0.0480
7
"
25
2-Bromophenol
G
ACN/20-80
0.9530
0.9952
31 .112.5
17.U1 .4
0.0388
7
"
26
2-Chlorophenol
G
ACN/20-80
0.9536
0.9949
29.312.4
16.111.4
0.0370
7
"
27
2-Ethylphenol
G
ACN/20-80
0.9478
0.9943
34.213.0
18.011.7
0.0464
7
"
28
2-Methylphenol
G
ACN/20-80
0.9604
0.9962
27.7t2.0
15.311.1
0.0309
7
"
29
2-Nitrophenol
G
ACN/20-80
0.9700
0.9950
29.212.4
15.911.4
0.0371
7
"
30
3,4-Dime thylphenol
G
ACN/20-80
0.9466
0.9939
32.2i2.9
17.7H .7
0.0455
7
11
3,4-Dinltrophenol
G
ACN/20-BOi
0.9441
0.9921
36.313.7
20.112.1
0.0501
7
"
32
3,5-Dimethylphenol
G
ACN/20-00
0.9493
0.9944
33.212.9
18.2H .6
0 .0450
7
"
33
3-Bromophenol
G
ACN/20-80
0.9516
0.9949
34.213.8
10.011.6
0.0441
7
34
3-Chlorophenol
G
ACN/20-80
0.9519
0.9946
32.412.7
17.011 .6
0.0429
7
"
35
3-E thylphenol
G
ACN/20-80
0.9515
0.9949
33.912.8
18.6t1.6
0.0440
7
"


Table 3-1continued
Data
Soluta column
Solvent/% Range
r^ va. 1
36
3-Methylphenol
G
ACH/20-80
0.9536
37
3-Nltrophenol
G
ACN/20-80
0.9498
38
4-Bromophenol
G
ACN/20-80
0.9475
39
4-Chlorophenol
G
ACN/20-80
0.9496
40
4-Ethylphenol
G
ACN/20-80
0.9500
41
1-Hydroxynaptha lene
G
ACN/30-80
0.9588
42
2,3 ,5-Trichlorophenol
G
ACN/30-80
0.9659
43
2,3 ,5-Trimethylphenol
G
ACN/30-80
0.9640
44
2,3 ,6-Trimethylphenol
G
ACN/30-80
0.9688
45
2,3-Dlchlorophenol
G
ACN/30-80
0.9562
46
2,3-Dime thy1phenol
G
ACN/30-80
0.9641
47
2,4,-Dlmethylphenol
G
ACN/30-80
0.9552
48
2,4,6-Trimethylphenol
G
ACN/30-80
0.9681
49
2,4-Dibromophenol
G
ACN/30-80
0.9606
50
2,4-Dichlorophenol
G
ACN/30-80
0.9602
51
2,5-Dichlorophenol
G
ACN/30-80
0.9639
52
2,5-Dimethylphenol
G
ACN/30-80
0.9652
53
2,6-Dibromophenol
G
ACN/30-80
0.9678
54
2,6-Dichlorophenol
G
ACN/30-80
0.9677
55
2,6-Dimethylphenol
G
ACN/30-80
0.9689
56
2-Chloro-5-Methy1phenol
G
ACN/30-80
0.9646
57
2-Hydroxynaphtha lene
G
ACN/30-80
0.9538
58
3,4-Dichlorophenol
G
ACN/30-80
0.9589
59
3,5-Dichlorophenol
G
ACN/30-80
0.9634
60
4-Chloro-2-Methylphenol
G
ACN/30-80
0.9626
61
4-Chloro-3,5-Dimethylphenol
G
ACN/30-80
0.9588
62
4-Chloro-3-Hethylphenol
G
ACN/30-80
0.9591
63
4-Hydroxybutylbenzoate
G
ACN/30-80
0.9518
64
4-Hydroxypropylbenzoate
G
ACN/30-80
0.9481
65
1-Hydroxy-2,4-Dinltronapthalene
G
ACN/40-80
0.9778
66
2,3,4,5-Tetrachlorophenol
G
ACN/40-80
0.9759
67
2,3,4-Trichlorophenol
G
ACN/40-80
0.9732
68
2,3,5,6-Tetrachlorophenol
G
ACN/40-80
0.9780
69
2,3,5,6-Tetramethylphenol
G
ACN/40-80
0.9826
70
2,3,6-Trichlorophenol
G
ACN/40-80'
0.9772
71
2,4,5-Trichlorophenol
G
ACN/40-80|
0.9757
72
2,4,6-Trichlorophenol
G
ACN/40-80
0.9786
73
3,4.5-Trichloroohenol
G
ACN/40-80
0.9744
74
4-tert-Butylphenol
G
ACN/40-80
0.9722
75
Pentachlorophenol
G
ACN/50-80
0.9913
Rtfir ! va. Et( 30)
Slope(x10^)
-(y-lnt)
0
0.9955
27 .32.1
15.011.2
0.0330
0.9943
27.72 .4
15.311.4
O.0377
0.9942
34 .03 .0
18.7H .7
0.0466
0.9949
32.02.6
17.611.5
0.0411
0.9946
34.112.9
18.711 .6
0.0451
0.9877
38.315.9
21.013.4
0.0582
0.9915
38.8t5 .0
21.212.8
0.0489
0.9903
38.915.4
21.313.0
0.0525
0.9921
38.514.5
21 .0i2 .7
0.0465
0.9876
38.015.9
20.913.4
0.0581
0.9902
33 .214.6
18.212.6
0.0450
0.9842
32.915.8
18.013.3
0.0568
0.9922
39.014.8
21.312.7
0.0473
0.9892
43.216.3
23.6*3.5
0.0614
0.9891
39.3*5.7
21 .613.3
0.0563
0.9902
39.615 .5
21.713.1
0.0537
0.9908
33.8t4.5
18.512.6
0.0442
0.9919
39.514.9
21.6l2.8
0 .0485
0.9918
36.014.6
19.712.6
0.0447
0.9921
33.514.2
18.312.4
0.0407
0.9905
35.514 .8
19.512.7
0.0475
0.9849
36.216.2
19.913.5
0.0610
0.9885
40.616.1
22.313.5
0.0598
0.9904
43.415.9
23.7*3.4
0.0582
0.9898
38.6*5.4
21 .213.1
0.0534
0.9884
42.416.4
23.2*3.6
0.0624
0.9881
37.015.6
20.313.2
0.0553
0.9849
45 .617.8
25.014.4
0.0768
0.9826
37 .917.0
20.814.0
0.0686
0.9850
44.5110.1
24.315.7
0.0587
0.9835
50.9H2.1
27.716 .8
0.0703
0.9813
43. U10.9
23.516.1
0.0635
0.9852
49 .6U 1.1
27.016.3
0.0649
0.9894
37.317.1
20.214.0
0.0413
0.9844
41 .8i9.7
22.815.4
0.0562
0.9830
44.8110.8
24.516.1
0.0629
0.9855
43 .0i9.6
23.515.4
0.0558
0.9821
45.9111.4
25.1l6.4
0.0662
0.9800
41 .6H0.9
22.716.1
0.0635
0.9916
48.6113.6
26.3*7.6
0.0402
Hanal and Hubert (1983)
61 .3
91.1
75.6
84.1
84.4
-0
VD
83.7
85.6
79.8
85.8
83.0
89.9
90.1
99.0
98 .8
98.9
98.7
96.7
98.7
98.7
98.6
98.8
98.6
JT-
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
5
5
5
5
5
5
5
5
5
5
4


Table 3-1continued
Data
Soluta
column
Solvent/% Range
r2 ve. %
r2 v. et(3i
76
Aniline
G
ACN/10-70
0.9720
0.9951
77
N-Me thylanlllne
G
ACN/20-70
0.9074
0.9901
70
N-Ethylanlline
G
ACN/20-70
0.9070
0.9904
79
N-Butylanlllne
G
ACN/20-70
0 .9007
0.9973
00
N.N-Dlmethylanlllne
G
ACN/30-70
0.9060
0.9901
01
N,N-Dlethylanlllne
G
ACN/40-70
0.9001
0.9970
02
2-Methylanlline
G
ACN/10-70
0.9704
0.9964
03
3-Methylan11lne
G
ACN/10-70
0.9651
0.9967
04
4-Methylanlllne
G
ACN/10-70
0.9654
0.9973
05
2,4-Dlmethylanlllne
G
ACN/20-70
0.9716
0.9970
06
4-Methoxyanlllne
G
ACN/10-70
0.9416
0.9901
07
2,4-Dlethoxyanillne
G
ACN/20-70
0.9691
0.9903
00
2-Chloroaniline
G
ACN/20-70
0.9020
0.9927
09
3-Chloroanlllne
G
ACN/20-70
0.9705
0.9949
90
4-Chloroanlline
G
ACN/20-70
0.9742
0.9964
91
2 ,5-Dlchloroani1lne
G
ACN/30-70
0.9006
0.9904
92
3,4-Dlchloroanlllne
G
ACN/30-70
0.9767
0.9902
93
4-Bromoan11lne
G
ACN/20-70
0.9743
0.9936
94
2-N1troanl1lne
G
ACN/10-70
0.9737
0.9936
95
3-Nltroanl1lne
G
ACN/10-70
0.9006
0.9095
96
4-N1troanlline
G
ACN/10-70
0.9770
0.9924
97
Pyridine
G
ACN/10-70
0.0965
0.9003
90
2-Aminopyrldine
G
ACN/10-70
0.7304
0.9017
99
3-Amlnopyrldlne
G
ACN/10-70
0.0436
0.9661
100
2-Methylpyridine
G
ACN/10-70
0.0974
0.9007
101
3-Methylpyridine
G
ACN/10-70
0.9142
0.9940
102
4-Methylpyridlne
G
ACN/10-70
0.9072
0.9920
103
4-Ethylpyridine
G
ACN/20-70
0.9420
0.9973
104
4-tert-Butylpyridine
G
ACN/30-70
0.9637
0.9956
105
2,4-Dimethylpyridlne
G
ACN/30-70
0.9606
0.9967
106
2,5-Dimethylpyridlne
G
ACN/20-70
0.9432
0.9973
107
2 ,6-Dimethylpyridlne
G
ACN/10-70
0.9072
0.9920
100
Pyrazine
G
ACN/10-70
0.7610
0.9196
109
2-Methylpyrazine
G
ACN/10-70
0.0009
0.9433
1 10
2,5-Dimethylpyrazine
G
ACN/10-70
0.0105
0.9530
111
2 ,6-Dimethylpyrazine
G
ACN/10-70
0.0103
0.9472
112
Quinoline
G
ACN/20-70
0.9370
0.9959
1 13
2-Me thylquinollne
G
ACN/20-70
0.9425
0.9971
114
4-Methylquinoline
G
ACN/20-70
0.9573
0.9964
1 15
0-Methylquinoline
G
ACN/20-70
0.9551
0.9905
116
5-Amlnolndan
G
ACN/20-70
0.9669
0.9901
1 17
5-Aminolndole
G
ACN/10-70
0.9403
0.9960
1 10
1-Amlnonapthalene
G
ACN/20-70
0.9721
0.9976
1 19
2-Aminonapthalene
G
ACN/20-70
0.9691
0.9977
120
1-Aminoanthracene
G
ACN/30-70
0.9717
0 .9976
121
1-Amlnopyrene
G
ACN/40-70
0.9019
0.9937
Befarenc<
ilope(xl02)
-(y-int)
a
bg%
19.51.6
11.110.9
0.0300
7
20.03.9
15.612.2
0.0475
6
33.04.5
10.312.6
0.0553
6
53.910.6
29.714.9
0.0263
4
30.413.0
21.2H.7
0.0205
5
54.119.0
29.715.1
0.0276
4
24.51.7
13.011.0
0.0334
7
25.3H .7
14.211 .0
0 .0329
7
25.4H .5
14.310.09
0.0301
7
31 .4121.
17.511.2
0.0252
6
21.311.1
12.210.6
0.0212
7
36.512.1
20.3tl.2
0.0256
6
30.713.7
17.112.1
0.0449
6
32.113.2
10.011.0
0.0256
6
31.312.6
17.611.5
0.0322
6
44.313.3
24.611.9
0.0222
5
43.013.4
24.0H .9
0.0227
5
33.512.0
10.011.6
0.0338
6
20.612.6
16.111.5
0.0520
7
26.213.1
14.011.0
0.0613
7
95.7
26.312.6
14.911.5
0.0520
7
17.012.1
9 .011 .2
0.0420
7
93.1
12.514.0
7.712.0
0.0936
7
90.5
15.613.3
9.3l 1 .9
0.0661
7
97.1
22.712.0
12.011.6
0.0412
7
96.9
23.512.1
13.211.2
0.0412
7
23.612.4
13.311.4
0.0474
7
20.212.0
15.711.2
0.0250
6
37.714.6
20.012.6
0.0309
5
26.012.0
14.911.6
0.0192
5
26.6H .9
14.011.1
0.0236
6
10.114.9
10.512.0
0.0556
7
10.213.5
6.212.0
0.0601
7
96.3
14.214.0
0.412.3
0.0787
7
98.3
10.214.6
10.512.7
0.0916
7
99.5
10.114.9
10 .512.8
0.0966
7
97 .0
29.012.6
16.711.5
0.0324
6
33 .612.5
10 .711.4
0.0309
6
32.4*2.7
10.0*1.5
0.0329
6
34.7H.0
19.2H.1
0.0226
6
34.012.0
19.011.2
0.0251
6
21.0H.4
12.210.8
0.0274
7
36.112.5
20.2l1.4
0.0304
6
37.112.5
20.7H .4
0.0303
6
53.314 .0
29.512.7
0.0326
5
55.5H3.4
30.717.6
0.0401
4
Hanal and Hubert (1905)
03
o


3l<
Data
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
3-1 continued
r2 vs. %
r2 va. Et(30)
Slope(x102]
-(y-int)
a
Reference
2,4-Dlnitrophenol
II
ACN/20-80
0 9652
0.9917
31 .8*3.3
17 .7*1 .9
0.0521
7
llanal and lluber
3-Bromophenol
H
ACM/20-80
0 9495
0.9919
34.713.6
19.3*2.1
0.0565
7
"
4-Nitrophenol
H
ACN/20-80
0 9536
0.9936
27.312.5
15.3*1 .4
0.0394
7
"
2,3,4,5-Tetrachlorophenol
H
ACN/40-80
0 9675
0.9702
52.4H6.9
28.8*12.5
0.0982
5
71.4
"
2,4,5-Trichlorophenol
H
ACN/40-80
0 9688
0.9688
45.7*15.1
25.2*8.5
0.0876
5
70.7
-
2,5- Dlchlorophenol
H
ACN/30-80
0 9653
0.9877
40.616.3
22.5*3.6
0.617
6
61 .8

4-Chloro-3,5-Dimethylphenol
H
ACN/30-80
0 9024
0.9434
42.3*14.4
23.4*8.2
0.1412
6
65.2

4-Chioro-3-Me thylphenol
H
ACN/30-80
0 9587
0 .9847
37.9*6.6
21.0*3.7
0.0644
6
68.7
"
Toluene
B
ACN/25-40
0 9905
0.9724
28.3*14.5
15.8*8.4
0.0662
4
58.3
Woodbum ( 1985)
n-Butylbenzene
B
ACN/25-40
0 9998
0.9936
47.5*11.6
26.3*6.7
0.0531
4
-
1,2,4-Trimethylbenzene
B
ACN/25-50
0 9994
0.9912
38.5*11.0
21 .4*6.4
0.0504
4
"
An thracene
B
ACN/25-50
0 9988
0.9917
51.2114.3
28.5*8.3
0.0653
4
"
Benzene
B
ACN/25-50
0 9771
0.9522
22.5*15
12.6*8.9
0.0699
4
53.4
. *
Biphenyl
B
ACN/25-50
0 9995
0.9919
45.0*12.5
25.0*7.2
0.0567
4
"
Bromobenzene
B
ACN/25-50
0 9947
0.9803
31 .2*13.5
17.4*7.8
0.0614
4
83.9
Chlorobenzene
B
ACN/25-50
0 9880
0.9686
29.3*16.1
16.4*9.3
0.0735
4
85.5
Ethylbenzene
B
ACN/25-50
0.9954
0.9815
34.4*14.4
19.1*8.4
0.0656
4
57.1
"
Fluoranthene
B
ACN/25-50
0 9998
0.9968
54.2*9.4
30.2*5.5
0.0429
4
"
Fluorobenzene
B
ACN/25-50
0.9846
0.9630
25.2*15.0
14.2*8.7
0.0688
4
78.8
Iodobenzene
B
ACN/25-50
0 9965
0.9838
34.2*13.4
19.0*7.8
0.0609
4
78 .6
"
Napthalene
B
ACN/25-50
0.9977
0.9865
36.7*13.1
20.5*7.6
0.0596
5
67.1
Nitrobenzene
B
ACN/25-50
0 9854
0.9642
23.8*14.0
13.4*8.1
0.0639
4
77.6
"
Phenanthrene
B
ACN/25-50
0.9999
0.9950
48.9*10.5
27.2*6.1
0.0484
4
M
Pyrene
B
ACN/25-50
0 9999
0.9966
53.9*9.5
30.0*5.5
0.0435
4
"
m-Diethylbenzene
B
ACN/25-50
0.9989
0.9895
46.2*14.4
25.6*8.4
0.0661
4
78.1
"
n-Propylbenzene
B
ACN/25-50
0 9981
0.9873
40.9*14.1
22.7*8.2
0.0644
4
54.5
"
o-Xylene
B
ACN/25-50
0.9941
0.9789
33.0*14 .7
18.4*8.5
0.0674
4
55.3
"
p-Xylene
B
ACN/25-50
0 9920
0.9752
33.7*16.3
18.7*9.5
0.0747
4
79.8
M
Chrysene
B
ACN/30-50
0 9997
0.9981
63.3*34.4
35.2*19.8
0.0378
3
"
1,2,4-Trimethylbenzene
C
ACN/30-60
0 9692
0.9993
41 .6*3.0
22.9*1.7
0.0147
4
"
Anthracene
C
ACN/30-60
0 9881
0.9994
50.7*3.7
28.0*2.1
0.0174
4
"
Benzene
C
ACN/30-60
0 9989
0.9936
26.9*6.6
15 .0*3 .8
0.0298
4
"
Biphenyl
C
ACN/30-60
0 9908
0.9995
46 .8*3.5
25.9*x.0
0.0147
4
"
Bromobenzene
C
ACN/30-60
0 9962
0.9973
34.7*5.4
19.3*3.1
0.0247
4
"
Chlorobenzene
C
ACN/30-60
0.9976
0.9964
33.0*6.1
18 .3*3 .5
0.0275
4

Chrysene
C
ACN/30-60.
0 9823
0.9985
60.7*7.1
33.5*4.0
0.0325
4
"
Ethylbenzene
C
ACN/30-60
0 9966
0.9977
37.8*5.5
20.9*3.2
0.0250
4
"
Fluoranthene
C
ACN/30-60
0.9869
0.9994
53.8*4.1
29.7*2.4
0.0175
4
"
Fluorobenzene
C
ACN/30-60
0 9982
0.9954
29.0*6.1
16.2*3.5
0.0272
4
"
Iodobenzene
C
ACN/30-60
0.9946
0.9986
37.1*4.2
20.5*2.4
0.0189
4
"


Table 3-1continued
column
Solvont/% Kan r2 va.
162
Napthalene
C
ACN/30-60
0.9936
163
Nitrobenzene
C
ACN/30-60
0.9985
164
p-Xylene
C
ACN/30-60
0.9946
165
Phenanthrene
C
ACN/30-60
0.9867
166
Pyrene
C
ACN/30-60
0.9848
167
Toluene
C
ACN/30-60
0.9983
168
m-Diethylbenzene
C
ACN/30-60
0.9915
169
n-Butylbenzene
C
ACN/30-60
0.9920
170
n-Propylbenzene
C
ACN/30-60
0.9945
171
o-Xylene
C
ACN/30-60
0.9949
172
n-Hexylbenzene
C
ACN/40-60
0.9976
173
1 ,2,4-Trlmethylbenzene
D
ACN/30-80
0.9786
174
Benzene
D
ACN/30-80
0.9877
175
Biphenyl
D
ACN/30-80
0.9739
176
Bromobenzene
D
ACN/30-80
0.9818
177
Chlorobenzene
D
ACN/30-80
0.9813
178
Ethylbenzene
D
ACN/30-80
0.9833
179
Fluorobenzene
D
ACN/30-80
0.9841
180
lodobenzene
D
ACN/30-80
0.9825
181
Nitrobenzene
D
ACN/30-80
0.9843
182
n-Propylbenzene
D
ACN/30-80
0.9796
183
Toluene
D
ACN/30-80
0.9846
184
m-Diethylbenzene
0
ACN/30-80
0.9791
185
o-Xylene
D
ACN/30-80
0.9841
186
p-Xylene
D
ACN/30-80
0.9816
187
Anthracene
D
ACN/40-80
0.9807
188
Chrysene
D
ACN/40-80
0.9758
189
Fluoranthene
D
ACN/40-80
0.9761
190
Napthalene
D
ACN/40-80
0.9792
191
Phenanthrene
0
ACN/40-80
0.9774
192
Pyrene
D
ACN/40-80
0.9750
193
n-Butylbenzene
D
ACN/40-80
0.9780
194
n-Hexylbenzene
D
ACN/40-80
0.9764
195
Bromobenzene
E
ACN/40-70
0.9976
196
Fluorobenzene
E
ACN/40-70
0.9981
197
lodobenzene
E
ACN/40-70
0.9968
198
Nitrobenzene
E
ACN/40-70
0.9984
199
1,2,4-Trimethylbenzene
E
ACN/50-70
0.9966
200
Anthracene
E
ACN/50-70
0.9957
201
Benzene
E
ACN/50-70
0.9995
Rfranc
va, ET(30)
Slope(x102)
-(y-int)
a
0.9988
39.114.0
21 .712.3
0.0185
0.9952
27.115.7
15.213.2
0.0259
0.9983
37 .6i4 .6
20.812.6
0.0214
0.9993
50.214.1
27.8i2 .4
0.0180
0.9990
54 .05.3
29.813.1
0.0238
0.9955
32.016.4
17.713.7
0.0295
0.9998
47 .9i2.2
26.4H.3
0.0090
0.9994
50.613.6
27.912.1
0.0169
0.9909
44 .0t4.5
24.212.6
0.0202
0.9984
36.914.6
20.4i2 .6
0.0204
0.9991
60.8123.2
33.3113.2
0.0199
0.9973
49.513.6
27.212.0
0.0371
0.9883
34.1*5.2
19.012.9
0.0535
0.9905
54.312.9
29.911.7
0.0302
0.9948
42.014.2
23.212.4
0.0439
0.9951
40.714.0
22.612.2
0.0413
0.9945
45.614.7
25.212.7
0.0492
0.9913
36.214.7
20.212.7
0.0491
0.9952
44.514.3
24 .612.4
0.0446
0.9915
35.114 .6
19.612.6
0.0470
0.9966
51.9i4.2
28.512.4
0.0438
0.9914
39.715.1
22.012.9
0.0534
0.9976
56.013.9
30.712.2
0.0396
0.9947
44.614 .6
24.612.6
0.0471
0.9960
45.314.0
25.012.2
0.0415
0.9981
58.914 .8
32.412 .7
0.0281
0.9995
67 .512.9
37.0H .6
0.0164
0.9989
62.1l3.6
34.U2.0
0.0220
0.9962
48.515.5
26.813.1
0.0324
0.9990
58.613.3
32.211.9
0.0199
0.9992
61.013.1
33.511 .7
0.0182
0.9985
59.814.3
32.812.4
0.0253
0.9988
70.514.6
38.512.6
0.0268
0.9969
45.917.7
25.014.3
0.0149
0.9963
40.717.5
22.514.2
0.0145
0.9977
47 .817.0
26.213.9
0.0134
0.9958
39.517 .9
22.014.4
0.0149
0.9978
52.217.3
28.514.1
0.0143
0.9983
58.517.4
31 .914.1
0.0142
0.9931
38.219.7
21.15.5
0.0187
Wood bum (1985)
65 .7
00
(V>
n
4
4
4
4
4
4
4
4
4
4
3
6
6
6
6
6
6
6
6
6
6
6
6
6
6
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4


Table 3-1continued
Data
Soluta
aColumn
Solvent/% Range
r^ va. %
r2 va. EtC 30)
Slope(x102)
-(y-lnt)
B
n
ba%
Reerence
202
Biphenyl
E
ACN/50-70
0.9963
0.9980
55.1*7.5
30.2*4.2
0.0146
4
Woodburn (1985)
203
Chrysene
E
ACN/50-70
0.9947
0.9988
65.916.8
35.7*3.8
0.0131
4
204
Ethylbenzene
E
ACN/50-70
0.9967
0.9976
48.917.2
26.8*4.1
0.0141
4
"
205
Napthalene
E
ACN/50-70
0.9968
0.9974
49.017.5
26.9*4.2
0.0146
4
"
206
Phenanthrene
E
ACN/50-70
0.9951
0.9989
57.616.2
31 .4*3.5
0.01 16
4
"
207
Pyrene
E
ACN/50-70
0.9953
0.9986
60.016.8
32.4*3.8
0.0129
4
"
208
Toluene
E
ACN/50-70
0.9967
0.9975
43.416.5
23.9*3.7
0.0127
4
"
209
m-Diethylbenzene
E
ACN/50-70
0.9967
0.9977
57.718.5
31.4*4.8
0.0161
4
"
210
n-Butylbenzene
E
ACN/50-70
0.9968
0.9975
59.018.8
32.1*5 .0
0.0172
4
"
211
n-Hexylbenzene
E
ACN/50-70
0.9961
0.9982
69.019.1
37.3*5.1
0.0171
4
212
n-Propylbenzene
E
ACN/50-70
0.9962
0.9980
54.217.4
29.6*4.1
0.0142
4
213
o-Xylene
E
ACN/50-70
0.9970
0.9976
47.817.2
26.2*4.0
0.0137
4
214
p-Xylene
E
ACN/50-70
0.9966
0.9979
48.516.8
26.6*3.8
0.0131
4
215
Acetophenone
F
ACN/50-80
0.9989
0.9960
33.716.5
19.3*3.6
0.0192
4
Jandera (1985)
216
Anisle
F
ACN/50-80
0.9965
0.9801
40.613.6
23.0*7.6
0.0401
4
29.3
217
Benzaldehyde
F
ACN/50-80
0.9985
0.9947
38.618.6
22.0*4 .8
0.0252
4
..
218
Benzonltrile
F
ACN/50-80
.9983
0.9920
39.2*10.7
22.316.0
0.0317
4
..
219
Benzophenone
F
ACN/50-80
>.9997
0.9976
47.9*7.1
26.9*4 .0
0.0210
4
H
220
Benzotrichloride
F
ACN/50-80
0.9984
0.9989
52.4*5.4
29.2*3.0
0.0158
4
221
Bromobenzene
F
ACN/50-80
0.9993
0.9942
44.4*10.3
24.9*5.7
0.0303
4
222
Chlorobenzene
F
ACN/50-80
0.9998
0 .9969
44.6*7.6
25.1*4.3
0.0225
4
..
223
Chlorobromuron
F
ACN/50-80
0.9998
0.9966
46.6*8.3
26.2*4.6
0.0245
4

224
Dl-n-Butylether
F
ACN/50-80
0.9975
0.9947
46.6*10.3
25.9*5 .8
0.0304
4
..
225
Ethyl benzoate
F
ACN/50-80
0.9990
0.9934
45.4111 .3
25.5*6.3
0.0333
4

226
Linuron
F
ACN/50-80
0.9999
0.9970
46.6*7 .8
26.3*4.4
0.0231
4
.1
227
Methyl benzoate
F
ACN/50-80
0.9976
0.9926
39.0*10.3
22.1*5.7
0.0303
4
M
228
Nitrobenzene
F
ACN/50-80
0.9995
0.9948
40 .0*8 .8
22.7*4.9
0.0261
4

229
Phenetole
F
ACN/50-80
0.9892
0.9765
41 .9*19 .8
23.6*11.0
0.0584
4
29.3

230
Phenol
F
ACN/50-80
0.9587
0.9691
43.4*2 .4
25.0*13.2
0.0697
4
54.0
231
Phenyl acetate
F
ACN/50-80
0.9969
0.9911
36.0*10.4
20.5*5.8
0.0306
4
232
Styrene
F
ACN/50-80
0.9988
0.9944
45.5*10.4
25.5*5.8
0.0307
4
M
233
o-Cresol
F
ACN/50-80
0.9937
0.9833
39.4*15.6
22.6*8.7
0.0462
4
29.3

234
n-Butylbromide
F
ACN/50-80
0.9990
0.9966
44.8*8.0
25.1*4.5
0.0235
4

235
n-Butylphenyl Carbamate
F
ACN/50-80;
0.9999
0.9981
48.0*6.3
27.0*3 .5
0.0186
4

236
n-Heptane
F
ACN/50-80
0.9990
0.9986
54.5*6.1
29.9*3.4
0.0181
4

237
n-Octane
F
ACN/50-801
0.9981
0.9976
59.0*8.8
32.3*4 .9
0.0260
4

238
n-Propylphenylether
F
ACN/50-80
0.9999
0.9960
46.1*8.9
25.9*5.0
0.0262
4
239
o-Cresol
F
ACN/50-80
0.9952
0.9959
39.0*7.7
22.4*4.3
0.0226
4

j>-Cresol
F
ACN/50-80
0.9984
0.9900
41.9*5 .6
23.9*3.2
0.0166
4

241
1 ,2,4-Trimethylbenzene
B
MeOH/35-60
0.9930
0.9852
53.3*19.9
30.5*"'7
0.0699
4
54.5
Woodburn (1985


Table 3-1continued
aColunm
Solvent/* Kan-je
r2 vs. *
r2 vs. En.(30)
Slope(xI02 J
-(y-Int)
8
n
ba%
24 2
B
MeOH/35-60
0.9976
0.9923
7O.710.9
40.4*11.1
0.0665
4
83 .0
243
B
MeUll/35-60
0.9606
0.9535
33.1 122.2
19.3i13.0
0.0781
4
03.6
244
Biphenyl
B
MeOII/35-60
0.9959
0.9895
61 .6*19.3
35.2*11 .3
0 .0600
4
80.3
245
Broioobenzene
B
MeOII/35-60
0.9043
0.9066
45.122.7
26.0*13.3
0.0799
4
03.7
246
Chlorobenzene
B
MeOII/35-60
0.9837
0.9723
42.2*21.6
24.2*12.7
0.0762
4
76.5
247
Chrysene
B
MeOII/35-60
0.9994
0.9966
92.6*69.1
52.0*40.5
0.0507
3
248
Ethylbenzene
B
MeOII/35-60
0.9867
0.9763
46.1*21 .8
26.5*12.0
0.0767
4
61 .0
249
Fluorobenzene
B
MeOH/35-60
0.9766
0.9633
36.1*21.4
21.0*12.6
0.0753
4
03.2
250
lodobenzene
B
MeOII/35-60
0.9095
0 .9002
40.3*20.9
27.0*12.3
0 .0734
4
02.3
251
Naptha lene
B
MeOH/35-60
0.9910
0.9823
51 .9*21 .2
29.8*12.4
0.0745
4
79.5
252
Nitrobenzene
B
MeOH/35-60
0.9598
0.9629
36.2*21 .6
21 .2*12.7
0 .0760
4
04.7
253
Phenanthrene
B
MeOH/35-60
0.9977
0.9926
69.2*18.2
39.6*10.7
0.0640
4
254
Pyrene
B
MeOH/35-60
0.9987
0.9945
77.8*17.7
44.4*10.4
0.0619
4
255
Toluene
B
MeOH/35-60
0.9797
0.9672
39.2*21.9
22.7*12.9
0.0772
4
64.3
256
m-Die thylbenzene
B
MeOH/35-60
0.9961
0.9899
60.7*10.6
34.5*10.9
0.0654
5
54.
257
n-Butylbenzene
B
MeOH/35-60
0.9959
0.9895
65.1*20.5
37.0*12.0
0.0710
4
63.6
250
n-Propylbenzene
B
MeOH/35-60
0.9920
0.9037
54.6*21.4
31.2*12.6
0.0753
4
61 .8
259
o-Xylene
B
MeOH/35-60
0.9868
0.9765
45.4*21.4
26.1*12.6
0.0754
4
57.1
260
p-Xylene
B
MeOH/35-60
0.9863
0.9756
47 .0*22.6
27.0*13.3
0.0795
4
80.4
261
1,2,4-Trlmethylbenzene
C
MeOH/40-75
0.9999
0.9950
60.6*7.2
34.3*4.2
0.0457
5
262
Benzene
C
MeOH/40-75
0.9960
0.9053
39.5*8.9
22 .6*5.1
0.0557
5
67.4
263
Bromobenzene
C
MeOH/40-75
0.9986
0.9905
51.0*9.2
29.1*5.3
0.0570
5
264
Chlorobenzene
C
MeOH/40-75
0.9988
0.9913
48 .9*0.4
27.9*4.9
0.0529
5
265
Ethylbenzene
C
MeOH/40-75
0.9997
0.9924
54.0*7.7
31 .1*4.5
0 .0438
5
266
Fluorobenzene
C
MeOH/40-75
0.9973
0.9872
43.0*9.0
24 .6*5.2
0.0564
5
00.9
267
lodobenzene
C
MeOH/40-75
0.9990
0.9950
55.0*7.2
31 .3*4.2
0.0451
5
268
Napthalene
C
MeOH/40-75
0.9999
0.9097
54.7*10.3
31 .0*5.9
0.0644
4
66.6
269
N1trobenzehe
C
MeOH/40-75
0.9983
0.9903
41.8*7 .6
24.0*4.4
0.0477
5
270
Toluene
C
MeOII/40-75
0.9986
0.9910
46.7*0.2
26.6*4.7
0.0514
5
271
p-Xylene
C
MeOH/40-75
0.9994
0.9933
54.2*0.2
30.8*4.7
0.0514
5
272
Anthracene
C
MeOH/50-75
0.9999
0.9098
75.3*23.3
42.5*13.4
0.0681
4
56.1
273
Biphenyl
C
MeOII/50-75
0.9999.
0.9807
60.7*22.4
38.9*12.9
0.0655
4
53.7
274
Chrysene
C
MeOH/50-75
0.9993
0.9913
89.8*25.7
50.6*14.0
0.0751
4
275
Phenanthrene
c
MeOH/50-75
0.9996
0.9897
73 .9*23.0
41.8*13.2
0.0671
4
53.4
276
Pyrene
c
MeOH/50-75
0.9083
0.9906
00.3*23 .7
45.3*13.6
0.0696
4
277
m-Diethylbenzene
c
MeOH/50-75
0.9998
0.9976
74 .0*11 .3
42.2*6.5
0.0329
4
270
n-Butylbenzene
c
MeOH/50-75
0.9999
0.9990
77 .0*7.5
43 .9*4.3
0.0220
4
279
n-Propylbenzene
c
MeOH/50-75
0.9999
0.9983
68.4*8.5
30.7*4.9
0.0248
4
280
p-Xylene
c
MeOH/50-75
0.9999
0.9980
56.6*7 .8
32.1*4.5
0.0228
4
201
o-Xylene
c
MeOtl/50-80
0.9999
0.9976
61.2*9.2
34.5t5-3
0.0303
4
Reference
(1985)
oo
-F^


Table 3-1continued
Solute
flColumn
Solvent/% Range
T1, V 3 .
202
Toluene
C
McOII/50-75
0.9986
283
n-Hexylbenzene
c
M. -11/60-75
0.9990
284
1,2,4-Trimethylbenzene
D
MeOH/50-80
0.9997
205
Anthracene
D
MeOII/50-80
0.9984
286
Benzene
D
MeOH/50-80
0.9999
287
Biphenyl
D
MeOII/50-80
0.9907
288
Bromobenzene
D
MeOll/50-60
0.9990
209
Chlorobenzene
D
MeOH/50-80
0.9999
290
Ethylbenzene
D
MeOII/50-00
0.9999
291
Fluorobenzene
D
MeOH/50-80
0.9999
292
Iodobenzene
D
MeOII/50-80
0.9998
293
Napthalene
D
MeOH/50-80
0.9994
294
Nitrobenzene
D
MeOH/50-80
0.9999
295
Phenanthrene
D
MeOH/50-80
0.9983
296
Pyrene
D
MeOII/50-80
0.9973
297
m-Diethylbenzene
D
MeOH/50-80
0.9995
290
n-Butylbenzene
D
MeOII/50-80
0.9990
299
n-Propy1benzene
D
MeOII/50-80
0.9996
300
p-Xylene
D
MeOII/50-80
0.9999
301
Chrysene
D
McOH/60-80
0.9992
302
n-Hexylbenzene
D
MeOII/60-80
0.9997
303
Acetophenone
F
Me0ll/60-90
0.9990
304
Anisle
F
MeOH/60-90
0.9979
305
Benzaldehyde
F
MeOII/60-90
0.991 1
306
Benzonitrile
F
MeOII/60-90
0.9992
307
Benzophenone
F
He0ll/60-90
0.9996
308
Benzotrichloride
F
MeOII/60-90
0.9988
309
Bromobenzene
F
MeOII/60-90
0.9999
310
Chlorobenzene
F
MeOH/60-90
0.9998
311
Chlorobromuron
F
MeOH/60-90
0.9978
312
Di-n-Butylether
F
MeOII/60-90
0.9988
313
Ethyl benzoate
F
MeOH/60-90
0.9996
314
Linuron
F
MeOH/60-90
0.9993
315
m-Cresol
F
MeOH/60-90
0.9937
316
Methyl Benzoate
F
MeOH/60-90
0.9996
317
n-Butyl Bromide
F
MeOH/60-90
0.9990
310
n-Heptane
F
MeOH/60-90
0.9999
319
Nitrobenzene
F
MeOH/60-90
0.9944
320
o-Creaol
F
MeOII/60-90
0.9896
321
p-Creeol
F
MeOH/60-90
0.9984
VB
vs. E-no)
Slope(x102)
-(y-int)
B
n
Hefeience
0.9966
55.419.0
31 .415.6
0.0325
4
Woodburn (1905
1 .000
1 11 .015.6
57.216.4
0.005
3

0.9901
69.019.1
30 .015.2
0.0301
4
0.9996
82.415.1
46.312.9
0.0163
4
0.9955
47.219.5
26.915.5
0.0317
4
-
0.9993
76.516.0
43.It3.5
0.0207
4
"
0.9979
59.110.4
33.514 .0
0.0274
4
0.9960
57. U9.8
32.415.6
0.0327
4
0.9971
64.0i1 .1
36.216.1
0.0346
4
0.9955
50.8110.5
29.016.0
0.0342
4
"
0.9978
62.519.1
35.315.2
0.0294
4
"
0.9907
64.416.8
36.413.9
0.0230
4

0.9963
47.218.7
27.015.0
0.0207
4
"
0.9996
00.714.7
45.412.7
0.0161
4
"
0.9999
87.312.6
48.911.5
0.008
4
"
0.9906
79.519.1
44.615.2
0.0297
4
0.9992
82.617.4
46.314.2
0.0235
4
0.9903
73.319.2
41.2l5.3
0.0300
4
0.9972
62.0110.2
35.415.9
0.0334
4
0.9999
90.5113.5
55.U7 .6
0 .007
3
0.9996
28.5114.1
50.9H6.2
0.0100
3
"
0.9989
50.515.0
29.212.8
0.0136
4
Jandera ( 1985)
0.9989
57.0117.5
32.019.9
0.0473
4

0.9777
55.U25.3
31.9114.4
0.0685
4
60.9

0.9952
53.6H 1 .3
31 .016.4
0.0305
4
0.9980
69.419.5
39.615.4
0.0257
4

0.9980
79.810.3
45.214.7
0.0225
4

0.9951
'67.U14 .3
38.210.1
0.0387
4

0.9944
64.7H4 .7
36.910.3
0.0397
4
H
0.9922
73.9H9.9
42.2H1.3
0.0538
4
N
0.9990
74.517.3
42.314.1
0.0195
4

0.9970
68.219.7
38.915.5
0.0263
4

0.9905
70.118 .4
40.014.7
0.0227
4

0.9772
62.6129.1
36.2H6.5
0 .0706
4
50.5

0.9901
59.417.9
34.114 .5
0.0213
4

0.9927
66.9H7.5
38.119.9
0.0472
4

0.9962
95.1117.8
53.5110.1
0.0478
4

0.9041
50.2122.5
33.5112.7
0.0608
4
61 .1

0.9792
61 .0127.0
35.3115.3
0.0730
4
67.9

0.9040
50.0122.2
34.011 2.6
0.0600
4
01 .1
N


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SOLVATOCHROMIC SOLVENT POLARITY MEASUREMENTS,
RETENTION, AND SELECTIVITY
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BY
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A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1986

This dissertation is dedicated
to my son, Garrett Chase, whose
arrival coincided with the
completion of this work.

ACKNOWLEDGMENTS
There are many people that I wish to acknowledge; in
his or her own way, each has contributed to my educational
progression. I would like to begin with my parents, Stan
and Connie Johnson, who constantly encouraged me to explore
my world and who instilled in me an unquenchable thirst for
knowledge. There are not many children who are fortunate
enough to grow up with a laboratory and a photographic
darkroom in their own basement!
My deepest gratitude is extended to Prof. Dr.
Christian Reichardt of Phillips-Universitat (Marburg, West
Germany), who so generously provided my advisor with
samples of the ET-30 dye, as well as providing helpful
comments during the preparation of two manuscripts.
I must also express my gratitude to the Eastman Kodak
Company, who funded 3 years of my graduate education
through the Kodak Fellow program, with no strings attached.
My advisor, Dr. John G. Dorsey, has been one of the
most enjoyable aspects of my graduate education. The many
hours we spent talking about everything from chromatography
to congealed desserts will always be treasured. He should
also be thanked for initiating my addiction to the
iii

Wall Street Journal, though he was unable to turn me into
an oenophile.
I also want to acknowledge my fellow group members,
who, along with their superb sense of humor, have made
graduate school an experience I shall always cherish.
Lastly, without the love, patience, and support of my
wife, Bonnie, and her parents, Phil and Sylvia Reinstein,
the completion of this work would not have been possible;
this was especially so after the arrival of our son,
Garrett Chase, whose timely (?) arrival coincided with the
completion of this tome.

TABLE OF CONTENTS
ACKNOWLEDGMENTS iii
LIST OF TABLES vii
LIST OF FIGURES ix
ABSTRACT xiii
CHAPTERS
I INTRODUCTION 1
Mobile Phase Effects 3
Stationary Phase Effects 7
Empirical Measures of Solvent Polarity .17
Analytical Application of the ET-30 Dye 26
II SOLVATOCHROMIC SOLVENT POLARITY MEASUREMENTS ... 34
Experimental 34
Results 42
Relationship Between Snyder's P' Polarity
Values and the ET(30) Scale 59
III CORRELATIONS BETWEEN CHROMATOGRAPHIC
RETENTION AND MOBILE PHASE POLARITY 65
Experimental 65
Results 67
Comparison with the "Carr Approach" 99
IV CORRELATIONS BETWEEN CHROMATOGRAPHIC
SELECTIVITY AND MOBILE PHASE POLARITY 104
Experimental 104
Introduction 105
Results 108
V DISCUSSION AND CONCLUSIONS 136
Stationary Phase Effects 150
Application of These Results 156
v

Interfacial Tension Effects....
Suggestions for Future Research
160
166
APPENDICES
A CHROMATOGRAPHIC RETENTION AND SELECTIVITY
DATA 175
B MODIFICATION OF CURVE FITTER PROGRAM TO
ALLOW CALCULATION OF CONFIDENCE INTERVALS 196
C MODIFICATION OF CURVE FITTER PROGRAM
TO INTERPOLATE SPECTRAL PEAK POSITIONS 197
D SOLVATOCHROMIC SOLVENT POLARITY
MEASUREMENTS 198
REFERENCES 201
BIOGRAPHICAL SKETCH 212
vi

LIST OF TABLES
Table Page
2-1
Effect of varying ET-30 concentration on
X and absorbance in 45/35/20 (v/v/v)
Me0H/ACN/H20
. . .36
3-1
Linear regression results for correlations
between log k' and either percent organic
modifier or ET(30) polarity
. . .73
3-2
p
Mean and median r^ values for correlations
shown in Table 3-1 -
.. .95
3-3
Multiple linear regression between log k'
values and a, 8, and ,
4-1
Squared correlation coefficients (r2) for
log a data with respect to percent organic
modifier (0M), mole fraction 0M, and ET(30)
polarity
4-2
Comparison of log a values as measured by
nitroalkanes and alkylbenzenes for a
Hamilton PRP-1 column
. .125
4-3
Correlations between log a and percent
organic modifier (0M), mole fraction organic
modifier (MF 0M), or ET(30) polarity for
a Hamilton PRP-1 polymeric column
. .126
5-1
Effect of increasing solute size upon
sensitivity to changes in E for alkylbenzenes
. .139
5-2
Effect of increasing solute size upon
sensitivity to changes in E^(30) polarity
for halobenzenes
5-3
Comparison of slope and y-intercept values
for log k' versus ET(30) polarity for
phenanthrene
. .145
vii

5-4 Comparison of slope and y-intercept values
for log k' versus ET(30) polarity for
ethylbenzene 145
5-5 Correlations between enthalpy of transfer
(aH) and 5^(50) polarity values 147
5-6 Ratio of slopes for a given solute and column
with methanol and acetonitrile as organic
modifiers 150
5-7 Intersection points for log k' versus Erj(30)
for alkylbenzenes 154
viii

LIST OF FIGURES
Figure Page
1-1 Structure of the ET-30 dye molecule,
2,6-Diphenyl-4-(2,4,6-triphenyl-N-
pyridino)phenolate in the ground and
excited states 24
2-1 Beer's law plot for ET-30 dissolved in
45/30/10 raethanol/acetonitrile/water (v/v/v)....37
2-2 Thermochromism of 4-nitroanisole in
33.3/33.3/33.4 methanol/water/acetonitrile
(v/v/v) 40
2-3 Thermochromism of 4-nitroanisole in
33.3/33.3/33.4 methanol/water/acetonitrile
(v/v/v) 41
2-4 Representative UV/VIS absorbance spectrum of
4-nitroanisole in methanol 43
2-5 Measurements of n* dipolarity/polarizability
for methanol/water mixtures with respect to
percent methanol 45
2-6 Measurements of tt* dipolarity/polarizability
for methanol/water mixtures with respect to
mole fraction of methanol 46
2-7 Measurements of tt* dipolarity/polarizability
for acetonitrile/water mixtures with respect
to percent acetonitrile 47
2-8 Measurements of it* dipolarity/polarizability
for acetonitrile/water mixtures with respect
to mole fraction acetonitrile 48
2-9 Representative UV/VIS absorption spectrum
of the ET-30 dye dissolved in methanol 51
IX

2-10 Measurements of Em(30) polarity for methanol/
water mixtures with respect to percent
methanol 52
2-11 Measurements of Ej(30) polarity for methanol/
water mixtures with respect to mole fraction
of methanol 53
2-12 Measurements of E,j(30) polarity for
acetonitrile/water mixtures with respect to
percent acetonitrile 54
2-13 Measurements of E^OO) polarity for
acetonitrile/water mixtures with respect to
mole fraction of acetonitrile 55
2-14 Comparison between Snyder's P' and Dimroth-
Reichardt's E^(30) polarity values for pure
solvents 61
2-15 Comparison between Eqi(30) polarity values
predicted by equation 2-3 and actual
E'p(30) polarity values reported by Reichardt
and Harbusch-Gornert (1983) 64
3-1 Retention data for 4-nitrophenol plotted with
respect to percent acetonitrile 71
3-2 Variation in mole fraction of methanol as
a function of volume percent 72
3-3 Variation in mole fraction of acetonitrile as
a function of volume percent 73
3-4 Retention data for 4-nitrophenol plotted with
respect to mole fraction of acetonitrile 74
3-5 Retention data for 4-nitrophenol plotted with
respect to tt* dipolarity/polarizability for
the same solvent mixtures 75
3-6 Retention data for 4-nitrophenol plotted with
respect to the E-j(30) polarity for the same
solvent mixtures 76
3-7 Histogram of r values for the 332 retention
data sets plotted with respect to percent
organic modifier 90
x

p
3-8 Histogram of r values for the 332 retention
data sets plotted with respect to E.j>(30)
polarity 91
p
3-9 Modified histogram of r values for the
332 retention data sets plotted with respect
to percent organic modifier 92
p
3-10 Modified histogram of r^ values for the
332 retention data sets plotted with respect
to Erp(30) polarity 93
4-1 Chromatographic selectivity measurements as a
function of percent methanol 110
4-2 Chromatographic selectivity measurements as a
function of mole fraction of methanol 111
4-3 Chromatographic selectivity measurements as a
function of E>p(30) polarity of methanol/
water mixtures 112
4-4 Chromatographic selectivity measurements as a
function of percent acetonitrile 113
4-5 Chromatographic selectivity measurements as a
function of mole fraction of acetonitrile 114
4-6 Chromatographic selectivity measurements as a
function of ET(30) polarity of acetonitrile/
water mixtures 115
4-7 Comparison between r^ values for plotting
methylene selectivity data with respect to
either percent organic modifier or E^(30)
polarity 119
4-8 Comparison between methylene selectivity
results obtained with either 1-nitroalkanes
or alkylbenzenes as the homologous series 124
4-9 Example of the measurement of methylene
selectivity with nitroalkanes as the
homologous series 128
4-10 Chromatographic selectivity measurements as
a function of percent methanol 129
4-11 Chromatographic selectivity measurements as
a function of mole fraction of methanol 130
xi

4-12 Chromatographic selectivity measurements as
a function of Ep(30) polarity of methanol/
water mixtures 131
4-13 Chromatographic selectivity measurements as
a function of percent acetonitrile 132
4-14 Chromatographic selectivity measurements as
a function of mole fraction of acetonitrile.... 133
4-15 Chromatographic selectivity measurements as
a function of Em(30) polarity of
acetonitrile/wafer mixtures 134
5-1 Slope of log k' versus E-p(30) polarity as a
function of carbon number for methanol/
water mixtures 142
5-2 Slope of log k' versus Eij(30) polarity as a
function of carbon number for acetonitrile/
water mixtures 143
5-3 Variation in surface tension as a function
of percent methanol 161
5-4 Variation in surface tension as a function
of mole fraction of methanol 162
5-5 Variation in surface tension as a function
of percent acetonitrile ....163
5-6 Variation in surface tension as a function
of mole fraction of acetonitrile 164
5-7 Comparison between surface tension and
E 5-8 Comparison between surface tension and
E-p(30) polarity for acetonitrile/water
mixtures 168
xii

Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
SOLVATOCHROMIC SOLVENT POLARITY MEASUREMENTS,
RETENTION, AND SELECTIVITY
IN REVERSED PHASE LIQUID CHROMATOGRAPHY
BY
BRUCE PHILIP JOHNSON
August, 1986
Chairman: John G. Dorsey
Major Department: Chemistry
The E>j(30) polarity and n* dipolarity/polarizability
of binary acetonitrile/water and methanol/water mobile
phases used in reversed-phase liquid chromatography were
measured and compared with chromatographic retention and
selectivity. For the retention data, plots of log k*
versus the Em(30) polarity were generally found to be
better descriptors of retention than the more commonly used
plots of log k’ versus percent organic modifier. A total
of 332 sets of retention data were examined, and the
overall average r^ values obtained for simple linear
regression of log k' versus either percent organic modifier
or E^j>(30) values were 0.9783 and 0.9910, respectively.
The slope and y-intercepts of plots of log k' versus
E^(30) polarity were found to be dependent on the solute
xiii

size, solvent system, and the column. Also, for a given
column and solute, the slope for the two solvent systems
examined was found to vary in systematic matter, with that
of raethanol/water mixtures 1.43 times greater (on the
average) than that for acetonitrile/water mixtures. This
variation in slope is evidence of differential solvation of
the bonded phase alkyl chains by the two organic modifiers.
In addition, the variation in methylene selectivity as
a function of either percent organic modifier or Erp(30)
polarity has been examined for various bonded phases, as
well as for a polymer-based column.
Solvatochromic solvent polarity measurements offer a
unique view of the retention process, by providing a means
of determining mobile phase polarity that is independent of
the chromatographic system, thus allowing de-convolution of
subtle stationary phase solvent effects, as well as the
prediction of chromatographic retention.
xiv

CHAPTER I
INTRODUCTION
The actual mechanism of retention in reversed phase
liquid chromatography (RPLC) has been the subject of much
controversy and debate since the first bonded phases for
chromatography became commercially available in the early
1970s. Despite its name, reversed phase liquid
chromatography is actually a more "popular" technique than
normal phase liquid chromatography (NPLC). Stationary
phases used in RPLC typically consist of a silica-based
supporting material to which nonpolar carbon chains are
bonded. These carbon chains are most commonly straight
chains of length 8 or 18 carbons (hence the terms "octyl,"
"octadecyl," C-8, C-18, etc. to describe the type of bonded
phase). The carbon chains are attached through a bonding
reaction in which the surface hydroxyl groups present on
the silica (silanols) are reacted with the appropriate
chlorosilane, leading to an Si-O-Si-C bond. For example,
to produce an octadecyl bonded phase, one could react
dimethyloctadecylchlorosilane with silica. The bonding
reaction is not exhaustive, however, so in a second step
trimethylchlorosilane or hexamethyldisilazine is typically
added in order to "endcap" the residual silanols that may
1

2
not be accessible to the larger, more sterically hindered
silane used in the first bonding reaction.
An ideal bonded phase would have no residual silanols
and would possess univariate pore and particle size
distributions. Practically speaking, no bonded phase can
be said to be free of residual silanol groups; one of the
major differences between competing commercial stationary
phases is in the degree of endcapping.
The presence of residual silanols is highly
undesirable since it leads to a second mechanism of
retention. Polar compounds and/or ones possessing hydrogen
bond donor/acceptor ability can interact with these
silanols (silanophilic solutes), leading to distorted peak
shape and/or greatly increased retention (Bij et al., 1981;
Nahum and Horvath, 1981). This problem was recently
reviewed, and the effects of both silanophilic and
metallophilic interactions were compared (Sadek et al.,
1985a). It was found that stainless steel inlet frits
commonly employed in LC columns also cause losses in
efficiency, due to both mechanical and chemical
interactions. Silanophilic interactions were found to be
the major factor in affecting the retention of basic amine
compounds.
While the mechanism of normal phase liquid
chromatography (NPLC) can be said to be fairly well
characterized in terms of adsorption at active sites upon

3
the silica or alumina surface, that of RPLC remains
controversial. In general, one can distinguish two broad
areas of study of this mechanism. These two areas are
referred to as "mobile phase effects" and "stationary phase
effects. "
Mobile Phase Effects
In the first of these ("mobile phase effects"), one
observes or calculates the effects of changing mobile phase
composition on chromatographic retention. Typical mobile
phases used in RPLC consist of water to which an organic
modifier has been added. The most frequently used organic
modifiers are methanol, acetonitrile, and tetrahydrofuran.
One example of the approaches classified as "mobile
phase effects" is that of solubility parameter theory.
Hildebrand's solubility parameter has been shown to be
useful in the prediction of many solution properties and is
defined by
6 = (E/V)1/"2
(1-1 )
where E is the molar heat of vaporization of the solvent
and V is its molar volume. When applied to chromatography,
retention is viewed in terms of the relative solubility
parameters of the solute, mobile phase, and the stationary
phase (Xarger et al., 1978; Schoenmakers et al., 1982).
1978; Schoenmakers et al.,

4
Capacity factors can then be considered to be related to
these parameters, as shown in the following equation:
In k' = (v/RT)(5m + 6s - 26.)^ - 5s)
+ In (n /n ) (1-2)
s m
where v is the molar volume of the solute and <5m, 6g, and
are the solubility parameters of the mobile phase,
stationary phase, and solute, respectively. The (ng/nm)
terra is the ratio of moles of the stationary and mobile
phases, respectively. If the solubility parameter for a
solvent mixture is approximated by assuming linear
additivity of volume fractions, the dependence of retention
on the volume fraction of one of the components becomes
In k' = A (4)2 + B (4>) + C (1-3)
where A, B, and C are constants. Assuming linear
additivity of solubility parameters is questionable,
however. Particularly for aqueous mixtures, where hydrogen
bond forces have a very large effect on the heat of
vaporization, the solubility parameter is likely to be
complex function of the volume fraction of the
components. This equation also results from assuming that
the stationary phase solubility parameter is a constant,

5
regardless of the mobile phase composition, which is also a
questionable assumption (see discussion of stationary phase
solvation in the latter part of this section). Moreover,
it is impossible to measure the solubility parameter of
either the binary/ternary solvent mixtures used in RPLC, or
the alkyl chains of the stationary phase. While the theory
enables qualitative predictions to be made on the basis of
relative polarity of the solute and phases, quantitative
calculations are not possible.
Hafkenscheid and Tomlinson (1983) have recently re¬
cast solubility parameter theory for RPLC. Semi-empirical
relationships were derived in order to allow more accurate
predictions of retention. Other workers have subdivided
the solubility parameter into individual contributions due
to dispersive forces, proton transfer, polar interactions,
etc., in an attempt to predict retention with greater
accuracy. An example of this approach would be the work of
Tjissen et al. (1976). Unfortunately, as the accuracy of
prediction increases the practicality of applying such
complex equations also decreases in an inverse fashion.
One of the most well-known approaches to
chromatographic retention is the hydrophobic theory of
Sinanoglu (1968), as applied by Horvath and Melander
(1977). This model (also referred to as the solvophobic
model) describes retention in terras of repellent forces
between the relatively nonpolar solute and the highly polar

6
aqueous mobile phase. This results in the formation of a
complex between the stationary phase ligands and the
relatively hydrophobic solute. Here the stationary phase
acts as a passive receptor to hydrophobic molecules that
are repelled by the aqueous mobile phase (cavity effect).
The stationary phase is treated as a constant, and specific
interactions between residual silanols and polar groups on
the solute molecules are not treated. Various mathematical
expressions were derived relating retention to solute
properties such as the hydrocarbonaceous surface area (HSA)
and solvent properties such as the dielectric constant or
surface tension.
Recently, Antle et al. (1985) compared various RPLC
columns with respect to solvophobic selectivity. Retention
differences seen among columns were ascribed to three
effects: differences in phase ratio, the polarity of the
bonded phase, and the dispersion solubility parameter of
the stationary phase.
Martire and Boehm (1980, 1983) have applied
statistical-mechanical theory to the description of
chromatographic retention. Using a lattice model,
predictions were made about the effects of either changing
mobile phase composition or length of alkyl bonded
groups. Though these derivations are quite rigorous,
practical application of the results is somewhat

7
difficult. Furthermore, because of several assumptions
made, again only qualitative predictions are possible.
Interaction indices (empirical measurement of I values
based on solute retention) have also been used by Jandera
et al. (1982) to predict retention. Here it is assumed
that the empirical interaction index of a solvent mixture
is a linear sum of the volume fraction contributions of the
solvents and again only qualitative predictions are
possible.
Stationary Phase Effects
In the second broad area of study ("stationary phase
effects"), the nature of the stationary phase is studied
through either direct physical measurement or through the
effects of changing the type of bonded phase (i.e., C-2,
C-8, etc.) on chromatographic retention. Direct physical
measurements of the stationary phase involve either
spectroscopic methods or actual chemical dissolution.
The most basic chemical analysis of a stationary phase
is the determination of percent carbon. The percentage of
carbon loading provides information about the extent of the
bonding reaction, as well as the degree of surface coverage
(assuming the surface area has been determined). Of
course, this provides no information about the conformation
or spatial distribution of the alkyl chains. Other
dissolution methods have been used in an attempt to examine

8
the chemical form of the bonded alkyl chains. For example,
Lullman et al. (1935) carried out studies in which bonded
phase packings were fused with potassium hydroxide. In
this manner, the alkyl ligands were cleaved from the silica
substrate, and subsequent 3C analysis of the fusion
products revealed the presence of hexaalkyldisiloxanes and
trialkylsilanols for monomeric bonded phases. Another
approach is to digest the stationary phase in hydrofluoric
acid and then to subject this digest to analysis by gas
chromatography (Fazio et al., 1935). Based on GC analysis
of these digests, it was possible to distinguish between
the various methods used to derivatize the silica (i.e.,
whether mono-, di-, or tri-chlorosilanes had been used).
While the stationary phase is often treated as a
passive or invariant entity, there is much evidence that
the solvation of the alkyl ligands themselves changes in
response to varying composition of the mobile phase. This
is best exemplified by the re-equilibration necessary after
an organic concentration gradient. That is, the alkyl
chains that comprise the stationary phase surface are
preferentially solvated by the organic component of the
mobile phase. Because of this, the interfacial region
between the bulk mobile phase and the surface of the silica
base has widely varying physical properties, so that
chromatographic retention reflects the statistical mean of
these varying physical properties. The organic modifier

9
content of
the
stationary
phase increases
with
the
concentration
of
modifier in
the mobile phase
(Yonker
et
al., 1932a, 1932b). Among the three most commonly used
organic modifiers, tetrahydrofuran has been shown to
solvate the stationary phase to the greatest extent,
followed by acetonitrile and methanol (Yonker et al.,
1982a, 1932b). Thus, while the mobile phase may consist of
a 50/50 mixture, the stationary phase will be solvated by a
mixture with a significantly higher proportion of the
organic modifier.
Lochmuller and Wilder (1979) compared the selectivity
of various bonded phases with that of equivalent 1iquid-
liquid systems. For chain lengths greater than
approximately 12 carbons, the selectivity was found to be
comparable to the liquid-liquid system. Also, Lochmuller
et al. (1981) prepared bonded phases with either n-heptyl,
cyclohexyl, or bicyclohepty1 alkyl chains. The n-heptyl
phase was found to have the highest selectivity and
capacity, though the cyclic phases were found to retain
cycloalkanes preferentially. Jinno and Okamato (1984)
prepared bonded phases with various aromatic moieties.
Capacity factors were measured for various polynuclear
aromatic hydrocarbons (PAHs). In this case, the pore size
of the silica matrix appeared to influence retention,
either because of its effect on the bonding reaction or

10
varying abilities of the PAHs to penetrate the interior
pores (steric effects).
One way to use a spectroscopic method in
characterizing the stationary phase is to sorb or
chemically bond a probe molecule to the surface and then
observe the electronic spectrum of the probe molecule.
Fluorescence spectroscopy lends itself to this type of
measurement, because of the type of sample and the inherent
lower detection limits possible. Since the sample is a
solid, it is very difficult to observe the adsorbed species
directly through absorption spectroscopy. That is, the
solid silica particles tend to scatter the incoming light
beam to a greater degree; using a lower amount of suspended
solid lowers the degree of light scattering at the expense
of lowered sensitivity to the presence of the probe
molecule. A secondary problem is the need to apply very
small amounts of the probe molecule to the stationary
phase. If too much is applied, more than a monolayer may
be formed, and thus the resultant information is of
questionable value. Also, one would not want to "overload"
the packing, i.e., operate at a concentration where the
sorption isotherm becomes nonlinear, which would also yield
results not applicable to the true conditions seen by the
stationary phase. For these reasons, fluorescence (for
UV/VIS) or diffuse reflectance (for infrared or UV/VIS)
spectroscopy are ideally suited to this type of

11
experiment. Of course, it is essential that for
fluorescence experiments, the excitation and emission
wavelengths be sufficiently separated to avoid interference
from the aforementioned scattered light.
In choosing a probe molecule to study the stationary
phase, the two most important criteria are spectral
response to changing solvent polarity and affinity for the
bonded alkyl chains. A probe molecule with insufficient
affinity (i.e., too low of a partitioning coefficient
between the mobile and stationary phases) will reside in
the mobile phase to such an extent that the fluorescence
cannot be attributed solely to that residing on the
stationary phase. For these reasons, the most commonly
used probe molecule has been pyrene, a 4-ring fused
aromatic compound. The fluorescence spectrum has vibronic
structure which is quite sensitive to the solvent environ¬
ment. In fact, this molecule has been used to establish
the Py scale of solvent polarity (Dong and Winnik, 1934;
empirical solvent polarity scales are discussed in detail
in the latter part of this chapter). The fluorescence
spectrum of pyrene contains five major vibronic bands,
labeled I to V, beginning with the 0-0 band. The ratio of
the intensities of bands I and III has been shown to be
highly responsive to changing solvent environment. Being a
large, hydrophobic molecule, it has a very large affinity
for the alkyl chains of the stationary phase. Two recent

12
papars have reported on the variation in stationary phase
polarity (as seen by pyrene sorbed onto the column packing)
as a function of the mobile phase composition (Carr and
Harris, 1986; Stahlberg and Almgren, 1985).
It is interesting to note that these two groups
obtained data for complementary organic modifier
concentration ranges, as a result of the experimental
conditions used. Stahlberg and Almgren (1985) measured the
surface polarity of C-2 and C-18 surfaces in the presence
of 0-30# methanol/water and acetonitrile/water mixtures.
This was done by using a suspension of 2-3 rag packing per
raL of solvent. Sodium tetradecylsulfate was also added
(0.5 mg/mL) to prevent flocculation of the particles. In
the 0-30# acetonitrile range, the surface polarity of the
C-18 packing was found to be greatest at the extremes,
while in methanol it decreased steadily as the
concentration increased. At higher concentrations of
organic modifier (>30# v/v), the concentration of pyrene in
the solvent mixture became too great and thus obscured the
fluorescence spectrum of the sorbed material. The
interpretation of these results is complicated, however,
because of the presence of added surfactant (0.5 mg/mL;
0.0015 M), which is also likely to sorb onto the bonded
chains and modify the surface polarity. Carr and Harris
(1936) studied both polymeric and monomeric C-13 phases in
a similar manner, except that the sample consisted of a

13
flow-cell packed with the solid, through which the solvent
mixture with pyrene was passed. In this case, the
investigators were limited to concentrations greater than
20, 25, and 50$ acetonitrile, tetrahydrofuran, and
methanol, respectively, because the entire packed particle
bed could not be fully equilibrated with pyrene. Here the
ratio of stationary phase to mobile phase volume was much
higher, leading to a much greater quantity of sorbed
pyrene.
This effect can be demonstrated quantitatively by the
following equation relating capacity factor (k1) to the
thermodynamic distribution coefficient (K) and phase ratio
U):
k' = k

The phase ratio, , is the ratio of the volumes of the
stationary and mobile phases. The capacity factor, k',
corresponds to the ratio of the moles of the sorbed
material present in the stationary and mobile phases at any
given instant. Thus, the packed bed used by Carr and
Harris (1986) has a much higher value than the slurry used
by Stahlberg and Almgren (1985), making the use of higher
organic modifier concentrations necessary (lower X
values). On the other hand, the upper limit of organic
modifier concentration is increased, since the higher value

14
compensates for the greatly decreased affinity of pyrene
for the stationary phase (lower K). Thus, Carr and Harris
(1936) were able to report surface polarities for up to 80,
45, and 70# methanol, tetrahydrofuran, or acetonitrile,
respectively. For a C-18 monomeric packing, the surface
polarity was found to increase with increasing organic
modifier concentration, with methanol systems having
consistently lower polarity than that of the acetonitrile
or tetrahydrofuran systems. This is a direct reflection of
the fact that much less methanol is absorbed by the alkyl
chains as the organic concentration is increased, so the
polarity remains closer to that of a pure alkane. On the
other hand, much greater amounts of acetonitrile and
tetrahydrofuran solvate these alkyl chains, leading to an
increase in apparent polarity (with respect to a pure
alkane). These results are fully consistent with those of
earlier workers who measured the adsorption isotherms of
organic modifiers onto various column packings. For
example, McCormick and Karger (1980a, 1980b) and Tanaka et
al. (1980) reported the organic modifier content of
reversed phase column packings under various
concentrations. Even at a concentration of 10# organic
modifier, acetonitrile was found to solvate the alkyl
chains to a much higher degree than methanol.
One way to get around the problem of lowered affinity
of the probe for the stationary phase at high organic

15
modifier concentration is to simply immobilize it by
bonding it to the stationary phase. Lochmuller et al.
(1985) measured the fluorescence of surface bonded
exciplexes (pyrene/N,N-dimethylaniline) to measure the
surface polarity after endcapping with either
trimethylchlorosilane (TMCS) or hexamethyldisilazine
(HMDS). Trimethylchlorosilane was found to yield a
stationary phase of lower polarity.
Another major area of spectroscopic examination of
stationary phases involves the use of nuclear magnetic
resonance (NMR). As with the sorbed probe fluorescence
experiments, the greatest wealth of information is derived
from those in which the packing is examined under "real"
conditions, i.e., in the presence of a mobile phase. Most
often, 13c is used in NMR experiments. One problem that
must be overcome is the low signal to noise ratio of 13q_
NMR, which is aggravated by the nature of the sample.
Also, alkyl chain C-atoras have nearly identical chemical
shifts, making it difficult to differentiate between
individual positions within the chain. Gilpin and Gangoda
(1984, 1985) have synthesized stationary phases in which
the terminal carbon atom is enriched with the isotope,
thus overcoming some of these difficulties. The spin-
lattice relaxation times (in either pure deuterated
chloroform or acetonitrile) were found to be fairly
constant for the various chain lengths studied. However,

16
at higher coverage densities, a decrease was noted. This
is evidence for the increasing interaction between the
neighboring alkyl chains. The effect of solvent viscosity
was also explored; an inverse relationship was found
between spin-lattice relaxation time and solvent
viscosity. Also, i—NMR with magic angle spinning has
been used to differentiate between the various chemical
environments of the silicon atoms in dry samples of column
packings (Fyfe et al., 1985).
Fourier transform infrared spectroscopy (FTIR) has
been used to directly observe the stationary phase alkyl
chains. Again, experiments have been done with both dry
packings and in the presence of solvent mixtures. In this
case, a major difficulty arises from the strong infrared
absorption band of water and methanol (0-H stretching),
which tends to obscure the C-H stretching band of the
bonded alkyl chain. One solution to this problem is to use
deuterated solvents, as Sander et al. (1983) have done with
C-1 to C-22 column packings. The range of 70-100# methanol
was studied, and evidence of increasing chain order was
found at the higher organic concentrations. Also,
temperature studies were carried out on the dry packings,
and no phase transitions were observed at temperatures near
or below the corresponding alkanes. The degree of disorder
of the chains was found to be comparable to that of liquid
n-alkanes at room temperature; thus the surface of the

17
bonded phase behaves like silica with a thin oily
coating. Suffolk and Gilpin (1985) have made FTIR
measurements of a cyanoalkyl bonded phase. Here the
cyanoalkyl group could easily be observed with little
interefrence from the solvent. In hexane, there appeared
to be two distinct populations of bonded ligands (possibly
due to interaction with surface silanols), while in 1-
butanol ligand-solvent interaction was more apparent.
Other studies of the stationary phase have made use of
such diverse analytical techniques as differential scanning
calorimetry (Hansen and Callis, 1983), ESCA (Miller et al.,
1934), and photoacoustic spectroscopy (Lochmuller et al.,
1980; Miller et al., 1934). Recently, two general reviews
of stationary phase structural studies have been published
(Gilpin, 1984, 1985).
Despite the plethora of spectroscopic studies
published on the nature of the stationary phase, in no case
is a quantitative relationship derived between these
experimental results and actual chromatographic
retention. In all cases, the spectroscopic results are
interpreted in a qualitative manner.
Empirical Measures of Solvent Polarity
For any chemical process occurring in solution, the
polarity of the solvent plays a crucial role in determining
the outcome. While this has been known for many years,

18
only recently has the exact role of the solvent begun to be
clarified and quantitated. Solvent properties influence
not only the rates of chemical reactions, but also the
position of chemical equilibria. Many spectral properties
are affected by the nature of the solvent. It is well
known that both the intensity and absorption or emission
frequency of NMR, IR, UV/VIS, and luminescence spectra are
affected by the solvent. This is an example of
solvatochromism, in which the position, intensity, or shape
of a spectral peak is affected by the solvent. The
importance of solvatochromism is demonstrated quite clearly
by the Sadtler library of standard ultraviolet spectra
(Sadtler Research Laboratories, Philadelphia, PA), in which
the spectra are reported for solutes dissolved in methanol,
wherever solubility permits. In this way, peak positions
for different substances are easily compared, with no need
to correct for the effect of different solvents.
In the field of analytical chemistry, solvent effects
must be taken into account when developing a method of
analysis. Solvents will affect the position and intensity
of spectral peaks being measured in quantitative IR or
UV/VIS spectroscopy, the rates and extant of reactions used
in derivatization or titration, etc. Also, chemical
separations by liquid chromatography (either normal or
reversed phase), which are controlled primarily by the
nature of the solvent(s) used as the mobile phase, are a

19
direct result of the different polarities of the stationary
and mobile phases.
There are many ways to characterize the polarity of a
solvent. Bulk physical properties, such as dielectric
constant, viscosity, or refractive index represent the
simplest measures of solvent properties. However, no
single physical property can adequately characterize the
"polarity" of a solvent. The "polarity" of a solvent is
extremely difficult to define and represents the sum total
of all possible interactions that a solute may experience
when dissolved in a particular medium. Therefore, bulk or
macroscopic properties will only provide information about
the interaction between the solvent molecules themselves.
Interactions that a solute may experience include
dispersion, dipole-dipole, dipole-induced dipole, and
hydrogen-bond forces. Because of the difficulty of
characterizing the polarity of a solvent through bulk
physical properties, a number of empirical scales of
solvent polarity have been developed in the past 50
years. These empirical scales are based on the properties
of particular solutes dissolved in the solvent of
interest. In this way, specific, microscopic interactions
with the solvent are probed, since the test solute is able
to "see" these better than bulk, macroscopic properties
can. Extensive reviews of empirical measures of solvent

20
polarity have been published (Griffiths and Pugh, 1979;
Reichardt, 1979)•
The earliest empirical scales of solvent polarity were
based on a kinetic measurement of some reaction carried out
in the solvent of interest. Perhaps the most well-known
scale of this type is the Y-scale, developed by Grunwald
and Winstein (1948). The Y-scale is based on the
solvolysis of t-butyl chloride. The rate constant for this
first order process is measured, and a Y-value is
calculated with the following equation:
log k - log kQ = raY (1-5)
where k is the rate constant, kQ is the rate constant in
80$ (aqueous) ethanol, and m is the sensitivity of the
substrate (m = 1 for t-butyl chloride, by definition).
There are also many empirical scales of solvent
polarity based on a spectroscopic measurement. The fact
that a solvent will influence the spectral properties of a
solute is used as a way of characterizing solvent
polarity. These measurements are quite simple and involve
nothing more than dissolving the test solute in the solvent
and recording the absorption or emission spectrum (either
IR, NMR, or UV/VIS). One example of this type of scale is
that of Xosower's Z-values (Kosower, 1958), which are based
on the interraolecular charge-transfer absorption of

21
1-raethyl-4-carbomethoxypyridinium iodide. The Z-values are
defined by
Z = 28592/X (1-5)
max
where Amax is the position of the charge transfer peak (in
nm). The constant in equation 1-6 is the product of
Avogadro's number, the speed of light, and Planck's
constant. The Z-values have been reported for more than 50
pure solvents and solvent mixtures (Kosower, 1953). For
mixtures with a high water content, the charge transfer
peak merges with that of the aromatic ring and is unable to
be located.
The it* scale of solvent polarity was developed by
Kamlet et al. (1977). Its name derives from the fact that
it is based on the positions of the n to tt* transitions of
a series of chroraophores. Rather than a single solute, it
is based on a series of aromatic solutes, in which the tt*
parameter was adjusted to give the most consistent
correlation among the various test solutes. The inventors
of this scale prefer to refer to it as the tt* scale of
solvent dipolarity/polarizability. In fact, in solvents
with no potential for hydrogen bonding, there is a linear
correlation between the molecular dipole moment and the
measured tt* value. Brady and Carr (1982, 1935) have
discussed this scale in terms of the Onsager reaction field

22
and Block and Walker dielectrically saturable reaction
field models. For a given solute, tt* values are calculated
with the following equation:
** = (v - vQ)/s (1-7)
where s is the sensitivity of the solute to the it* scale,
and v and vq are the absorption maxima (X 10"^ cm-1) of the
solute in the solvent and cyclohexane, respectively. The
appropriate constants for this equation have been published
(Kamlet et al., 1977). In addition both a and B measures
of solvent hydrogen bond donor and acceptor ability have
been derived from these same solutes. These measures are
based on the enhanced solvatochromic shift of one indicator
relative to another in the presence of hydrogen bond
donor/acceptor solvents. For example, one way to measure
the 6 value is to compare the solvatochromism of 4-
nitroanisole with respect to 4-nitrophenol; solvents
capable of hydrogen bond acceptor interactions will cause
an enhanced solvatochromic shift for the 4-nitrophenol with
respect to 4-nitroanisole (Karalet and Taft, 1976). In a
similar manner, solvent a values can be derived from the
enhanced solvatochromic shift of ET-30 with respect to 4-
nitroanisole (vide infra).
The Erj(3o) scale of solvent polarity was developed in
the early 1960s by Dimroth et al. (1963a, 1963b) and

23
Reichardt (1979), who reported on the solvatochroraism of a
series of 42 pyridinium betaine dye molecules. In the
original paper, derivative #30 was found to have the
greatest sensitivity to changes in solvent polarity. Thus,
the Ef(30) scale was named as such because it is derived
from the molar energy of transition (ET) of the thirtieth
pyridinium betaine (30). The E^(30) scale of solvent
polarity is based on the intramolecular charge transfer
absorption of 2,6-Diphenyl-4-(2,4,6-triphenyl-N-pyridino)-
phenolate (structure shown in Figure 1-1). It possesses a
number of unique features, such as a 44-electron aromatic
ring system, a negatively charged phenoxide group and a
positively charged pyridine ring nitrogen atom. This
molecule undergoes one of the largest known shifts in Xmax,
amounting to some 357 nm in going from water (453 nm) to
diphenyl ether (310 nm). Since this dye absorbs within the
visible light region, it is possible to estimate visually
the polarity of a solvent. In methanol, the solution is
wine-red, while in acetonitrile the solution becomes deep
blue in color. Values of ET(30) polarity are calculated in
the same manner as are Z-values (equation 1-6) and have
been reported for over 200 solvents (Reichardt and
Harbusch-Gornert, 1983). Also, the range of the scale has
been expanded through the use of a more lipophilic betaine,
in which a t-butyl group is attached to each of the five

24
Figure 1-1. Structure of the ET-30 dye molecule, 2,6-
Diphenyl-4-(2,4,6-triphenyl-N-pyridino)-
phenolate in the ground and excited states.

25
phenyl groups (para position). Recently, a normalized
scale of Srp(30) polarity (E.jji) has been defined by Reichardt
and Harbusch-Gornert (1983), in which the polarity of water
is defined to be 1.0, while that of tetramethylsilane (TMS)
is 0. These values are calculated by using the following
equation:
E (solvent) - E (TMS)
N _ _± L
u - et(h20) - Et(TMS) 1 ;
where Er^( solvent) is the E^(30) polarity of the solvent in
question as calculated by equation 1-6, and Erptl^O) and
E^(TMS) have values of 63.1 and 30.7, respectively. The
normalized scale is used for convenience in expressing a
polarity relative to water or tetramethylsilane and has no
actual effect on the types of correlations discussed
herein. All E^^O) polarity values reported here are in
kcal/mole, as calculated from equation 1-6.
The Et(30) scale has been shown to be sensitive to
both solvent dipolarity/polarizability as well as solvent
hydrogen bond donor ability (HBD). Taft and Kamlet (1976)
calculated that 68$ of the shift in Xmax in going from
cyclohexane to n-butanol is due to HBD stabilization of the
ET-30. This stabilization is a direct result of the
presence of the negatively charged phenoxide group on the
ET-30 molecule. The phenoxide group acts as a hydrogen
bond acceptor, so that protic solvents may function as

26
suitable H-bond donors. In fact, Taft and Kamlet (1976)
have used the enhanced solvatochromic shift of ET-30 with
respect to 4-nitroanisole to measure the solvent hydrogen
bond donor
acidity
(a-scale).
In
both protonic
and
nonprotonic
solvents,
the Et(30)
scale
can be related
to
the tt* and
a scales
by use of
the
following equation
(derived from equation
7 of Kamlet
et al
., 1976):
E.r(30) =
30.31 + 14.
6 IT* +
16.53a (1
-9)
Analytical Applications of the ET-30 Dye
Owing to its extreme sensitivity to changes in overall
solvent polarity, ET-30 may be used to determine the
composition of binary solvent mixtures. However, ET-30 is
particularly sensitive to the presence of small amounts of
water in aprotic solvents. For protic solvents, the
presence of water has a smaller effect, as illustrated with
tert-butyl hydroperoxide. Langhals et al. (1980) have
reported that the presence of 5.2 moles/liter water changes
the apparent solution color from blue (x^^ = 575 nm) to
red (Xmax = 532 nm). Thus, the color of the solution
serves as a visual indicator of the water content, and
measurement of *max for ET-30 dissolved in a given solvent
can be a rapid and precise alternative to Karl-Fischer
water determinations. Of course, quantitation of the water

27
content for a given solvent requires that the E be known for each composition. Values of E.j(30) polarity
for many binary solvent systems have been reported
(3alakrishnan and Easteal, 1931a, 1931b; De Vijlder, 1982;
Dimroth and Reichardt, 1965; Jouanne et al., 1973; Koppel
and Koppel, 1983a, 1983b; Krygowski et al., 1935;
Maksimovic et al., 1974). If the variation in ET-30 as a
function of composition is monotonic, i.e., no maxima or
minima occur, this determination is fairly
straightforward. On the other hand, if there are any
maxima or minima, this is not possible, since a given Amax
value will correspond to more than one concentration. This
would be the case, for example, for mixtures of
acetonitrile with isopropanol, as reported by Koppel and
Koppel (1983a). Langhals (1982a) has proposed the
following equation to follow changes in Erp(30) polarity
values in binary solvent mixtures:
Et(30) = Ed ln(Cp/C* + 1) + E°(30) (1-10)
where Cp is the molar concentration of the most polar
component, Ed and C* are constants determined for each
binary system, and E-^(30) is the E^(30) polarity for the
least polar solvent. The appropriate constants for a total
of 46 binary solvent systems have been reported, as well as
for an organic co-polymer (Langhals, 1982a, 1982b). This

28
equation is discussed in further detail in Chapter III.
Alternatively, the change in absorbance of a solution of
ET-30 at a fixed wavelength has been used to determine
mixture composition. For example, Kumoi et al. (1970) have
reported that water concentrations of 60 yg/mL can be
detected in acetonitrile. In this case a major dis¬
advantage of the method is that the ET-30 concentrations
must be precisely controlled, and a calibration curve must
also be constructed for each determination.
In the examination of the polarity of aqueous micellar
media, ET-30 has also been shown to be useful. Use of
micellar solutions in analytical chemistry has increased in
recent years and has been reviewed by Cline-Love et al.
(1984). Since ET-30 is essentially insoluble in pure
water, the hydrophobic interior of aqueous micelles
provides an ideal site for solvation. Its insolubility in
water means that partitioning between the micelles and
surrounding water will not occur to a significant extent,
and thus interpretation of the spectral results is
simplified. Zachariasse et al. (1981) have reported the
use of ET-30 as a polarity probe for micelles,
microemulsions, and phospholipid bilayers. Changes in
micelle conformation (e.g., sphere-to-rod transition) were
easily detected by the discontinuity in measured E polarity as the concentration of sodium chloride was
increased. Also, Plieninger and Bauragartel (1983) have

29
studied the NMR spectrum of ET-30 in various surfactant
media to determine the position in which the molecule
resides in the micelles. In cationic micelles the
phenoxide group was found to be located in the rigid region
of the electrical double layer, while in anionic micelles
it is found in the diffuse layer, with the pyridinium
nitrogen atom in the rigid layer.
In addition to being used as a probe of micellar
environments, ET-30 also provides useful information about
the structure of binary solvent mixtures. For example,
Kohler et al. (1969) compared the NMR absorption spectrum
for the water proton in aqueous/organic mixtures with the
E^(30) polarity. Binary mixtures of water with either
acetone, dioxane, or tetrahydrofuran were studied, and a
linear relationship was found between the water proton
absorption peak and the measured Erp(30) polarity for the
same mixture. It must be noted, however, that the
concentration range examined was fairly small (50-95%
organic component by volume), so it is possible that
outside this range the relationship is not linear.
Balkrishnan and Easteal (1981b) have also discussed the
variation in Erj,(30) polarity in binary acetonitrile/water
mixtures (see Chapter II).
Heats of solution at infinite dilution have been
correlated with the Ex(30) polarity scale by Ilic and
coworkers (1984). A linear relationship was found between

30
a solute's ET(30) polarity and its heat of solution.
Solutes that were studied included n-alkyl ketones, n-
alcohols, and di-n-alkyl ethers. The heats of solution of
these solutes were measured in solvents such as n-hexane,
carbon tetrachloride, benzene, etc. None of the solvents
were capable of hydrogen bonding with the solutes, however,
and thus the results cannot be generalized to include every
solute/solvent system. Also, heats of solution were
measured only in pure solvents, rather than mixtures. In
addition, this type of correlation would not be possible
for solid compounds, since it is not possible to measure
their E"j.(30) polarity. Of course, it might be possible to
estimate the Erp(30) polarity for solid compounds by using
heat of solution measurements, as Fuchs and Stephenson
(1983) have done for the n* dipolarity/polarizability of
solid compounds.
The Et(30) scale of solvent polarity has been applied
to chromatographic systems in a number of ways. The
applications discussed here include supercritical fluid
chromatography and normal phase liquid chromatography
(NPLC). These types of investigations can provide
information about either the mobile phase (solvent
polarity) or the stationary phase (surface polarity).
For example, the E^(30) polarity of a mobile phase
used in supercritical-fluid chromatography (3FC) has been
reported (Hyatt, 1984). Typical mobile phases used in SFC

31
are compressed gases such as carbon dioxide or ammonia, at
a temperature greater than their critical point. Hyatt
calculated the Ej>(30) polarity of both sub- and
supercritical carbon dioxide to be 33.8 kcal/mole, by using
the more lipophilic penta(tert-butyl) derivative of ET-30
(Reichardt and Harbusch-Gornert, 1983). It was necessary
to use the more lipophilic compound due to the low
solubility of ET-30 in supercritical CO2. An E^(30)
polarity of 33.8 kcal/mole is comparable to that of either
toluene or tetrachloroethylene. However, the strength of
the mobile phases used in SFC is controlled by the pressure
(and resultant density). The E supercritical CO2 was reported for only one pressure (1000
PSI) and temperature (42°C), and thus it is likely that a
different polarity would result for different pressures
(densities). For example, Sigman et al. (1985) measured
the it* dipolarity/polarizability and B (hydrogen bonding
basicity) for supercritical CO2, which were found to be
highly dependent on the density. Since these measurements
are also based on the use of solvatochromic dyes, it is
likely that the ET(30) polarity would also be greatly
affected by a change in the CO2 pressure. Thus, useful
information would be provided by performing the same
experiments with the more lipophilic, t-butyl derivatized
betaine. Levy and Ritchey (1935) have reported on the
effects of adding small amounts of additives such as

32
methanol or acetonitrile to the mobile phase in SFC. In
theory, E-p(30) polarity of these binary mixtures could also
be measured.
The polarity of silica surfaces used in normal phase
liquid chromatography was examined (Lindley et al.,
1985). In this case, the diffuse reflectance spectrum of
the betaine adsorbed onto the silica was measured. The
peak corresponding to minimum reflectance was used, in
conjunction with that of 4-nitroanisole, to calculate a, a
measure of the acidity of the silica surface. The silica
surface was found to be a strong hydrogen bond donor. The
degree of the dye loading also influenced the measured
values, which decreased at higher levels, apparently as a
result of the formation of more than a monolayer of the
test solutes on the silica surface. None of these
experiments were done in the presence of a mobile phase,
however, most likely because the ST-30 is quite soluble in
typical mobile phases used in NPLC (such as those
containing dichlororaethane).
Another interesting application of ET(30) polarity
measurements involves Snyder's eluent strength parameters
for solvents used in normal phase liquid chromatography.
Krygowski et al. (1981) compared the ET(30) polarity of
various pure solvents with Snyder's eluent strength
parameter ( e°) •
In this case, it was necessary to

33
incorporate a second parameter, B^rp (Karalet/Taft basicity),
in order to predict the s° values. Also, only pure
solvents were treated, rather than the binary or ternary
mixtures typically used in normal phase liquid
chromatography.
To date there have been no comparisons made between
empirical measurements of mobile phase polarity and
chromatographic retention or selectivity. In reversed
phase chromatographic experiments, it is often assumed that
the strength of the mobile phase varies linearly with the
percentage of organic modifier. In this dissertation, the
results of empirical solvent polarity measurements of the
most commonly used mobile phases are discussed, as well as
the correlation between these measurements and
chromatographic retention and selectivity.

CHAPTER II
SOLVATOCHROMIC SOLVENT
POLARITY MEASUREMENTS
Experimental
E^(3Q)-Value Measurements
A sample of the ET-30 was kindly provided by Professor
Christian Reichardt of Philipps-Universitat Marburg,
Federal Republic of Germany. The synthesis of ET-30, which
is not commercially available, is reported elsewhere
(Dimroth et al., 1963b). Binary solvent mixtures were
generated by a Spectra-Physics Model SP8700 ternary
proportioning LC system. Degassing was achieved by
sparging the solvents vigorously with helium. Both HPLC
grade methanol and acetonitrile (Fisher Scientific, Fair
Lawn, NJ) were used as received. Water was first purified
with a Barnstead Nanopure system (Boston, MA) and then
irradiated with UV light in a Photronix Model 816 H.P.L.C.
reservoir (Photronix Corp., Medway, MA) for at least 24
hours. The water was then filtered through a 0.45
micrometer Nylon-66 membrane filter (Rainin Instruments,
Woburn, MA) prior to use.
After collecting 3 mL of a given solvent mixture in a
1 cm path length quartz cell, approximately 0.3 rag of ET-30
34

35
was added, and a spectrum was obtained with a Hewlett-
Packard Model 8450A diode array spectrophotometer.
Wavelength accuracy of the instrument was checked with a
Holmiura Oxide interference filter. Spectra were acquired
at 25±2°C. In pure methanol, the change in Amax is 10 nm
for a temperature change from 25 to 55°C (Diraroth et al.,
1963a). Thus, a ±2 degree variation leads to an
uncertainty in E kcal/raole. The "peak-find" function of the instrument was
used to determine Xmax* For each solvent mixture, ten
spectra were acquired at one second integration time, and
the resultant A x values averaged. The pooled standard
deviation for 620 Xraax measurements was found to be
1.16 nm. Values of Erj,(30) polarity were calculated from
Amax data by using equation 1-6.
As with many dye molecules, the possibility of
dimerization of the ST-30 exists. Since E zwitterionic form, dimerization would be favored through
interaction between oppositely aligned molecules.
Dimerization would lead to a dependence of Amax upon its
concentration, as well as nonlinearity of a Beer's law
plot. It has been reported that Beer's law is obeyed for
concentrations in the range of 10“^ to 10-0^ M (Diraroth
and Reichardt, 1966); all sample concentrations were in
this range. As a further check, the concentration of ST-30

36
in 45/35/10 MeOH/ACN/^O was varied, and Amax and
absorbance at imax measured. These data are shown in Table
2-1 and are plotted in Figure 2-1. No dependence of imax
on ET-30 concentration was observed. Also, Beer's law was
obeyed over the concentration range studied.
Table 2-1.
Effect of varying ET-30 concentration on A and
absorbance in 45/35/20 (v/v/v) MeOH/ACN/HpO.
Cone. (mg/mL) *max Absorbance
0.13
508.5
0.2757
0.26
508.3
0.6901
0.38
508.3
1.111
0.52
509.5
1.498
0.65
508.4
1.914
Values of Erp(30) have been previously reported for
these same solvent mixtures (Dimroth and Reichardt, 1966;
Krygowski et al., 1985); however, in these cases mixtures
were prepared by adding water to the organic solvent to
attain a fixed total volume. In contrast, LC pumps
typically mix solvents on the basis of additive volume.
For example, 100 raL of 50/50 (v/v) mixture of
methanol/water (as delivered by an LC pump) is comprised of
50 mL methanol to which 50 mL water is added. Excess
volumes of mixing lead to slight differences in solvent
composition and resultant ET(30) polarity values, so these

37
Figure 2-1. Beer's law plot for ET-30 dissolved
45/30/10 methanol/acetonitrile/water (v/v/v)
in

38
measurements were made with solvent mixtures generated with
the LC pump system itself.
tt*-Value Measurements
Measurements of tt* values were made with 4-
nitroanisole (Aldrich Chemical Co., Milwaukee, 41) and
using the following equation from Kamlet et al. (1977):
IT
*
( V
max
vQ)/2.343
(2-1)
where vjnax is the observed maximum in wavenumbers (X 10-0^
cm-1), and vq is the value for the solute in cyclohexane
(it* = 0 in cyclohexane, by definition). This reference
(Kamlet et al., 1977) lists a number of solutes (for
example, 4-ethylnitrobenzene) that can be used to measure
the tt* dipolarity/polarizability; 4-nitroanisole was chosen
because of its low sensitivity to hydrogen bond
donor/acceptor effects. In this case the 4-nitroanisole
was added to the water at a concentration of 5 Mg/mL, and
the resulting solvent mixture + solute was passed through a
0.25 mL Hellma flow cell therraostatted at 40±0.1°C with a
Haake Model D1 water bath (Haake, Saddle Brook, NJ). Flow
was stopped while acquiring spectra to equilibrate the
temperature of the mixture and reduce the effect of
refractive index variability in the sample.
Because of the very small wavelength shift observed
with this substance in going from pure organic to pure

39
water (*max of 9 nra between water and acetonitrile), the
following algorithm was used to evaluate *max* Spectra
were acquired, and the absorbance recorded at each
wavelength (1 nm readout resolution). Next the absorbance
data were fit with a 3rd degree polynomial using the
program "Curve Fitter" (see Appendix C; this algorithm was
suggested by Savitizky and Golay, 1964). The first
derivative (dy/dx) of the resultant polynomial was then
used to evaluate *max (by setting this equal to zero and
solving for Xraax with the quadratic formula). Repeated
calculations with either the entire data set (30 points;
30 nm wide) or only five points (Xraax-10, Xraax'5, Xmax,
*max+5» Xmax+^^ showed that only five were needed to
define the spectral peak accurately. By interpolating the
spectral peak position in this manner, the precision of
Vax measureraent was greatly improved. As an illustration
of the utility of this algorithm, in Table 2-2 and Figures
2-2 and 2-3, the effect of temperature on the peak position
of 4-nitroanisole in 33.3/33.3/33.4 (v/v/v) MeOH/ACN/^O is
shown. Data of Xmax provided directly by the instrument or
that from interpolation (of the same spectral data set) are
plotted in Figures 2-2 and 2-3, respectively. The data
clearly indicate that thermochroraism of 4-nitroanisole is
not observable without the use of this algorithm.

40
Absorbance
Maximum
(nm)
Figure 2-2.
Temperature (°C)
Therraochroraism of 4-nitroanisole in
33.3/33.3/33.4 methanol/water/acetonitrile
(v/v/v). Wavelengths obtained directly from
the diode array spectrophotometer.

41
31 1 .4 -r
311.2 -•
Interpolated
Absorbance
31 1 .0 -•
Maximum
(nm)
310.8 -â– 
310.6 -
30
Temperature (°C)
Figure 2-3. Therraochroraism of 4-nitroanisole in
33.3/33.3/33.4 methanol/water/acetonitrile
(v/v/v). Wavelengths obtained by
interpolation of absorbance data from the
diode array spectrophotometer.
70

42
Table 2-2.
Thermochromism of 4-nitroanisole in
33.3/33.3/33.4 (v/v/v) Me0H/ACN/H20.
Temperature Vax Xmax
(°C) directly (interpolated)
40.0
312
311.4
45.0
311
311.2
50.0
311
311.1
55.0
312
310.9
60.0
312
310.8
Spectra of 4-nitroethylbenzene and 4-nitrophenol were
also acquired in the same manner in raethanol/water and
acetonitrile/water mixtures, in connection with the
measurement of solvent a and 3 values (not utilized in the
present discussion; results tabulated in Appendix D).
Results
iT*-Values
While the primary purpose of this research was to
investigate the Eij(30) polarity scale in regard to
chromatographic retention, measurements were also done for
the it* scale of solvent dipolarity/polarizability in binary
hydro-organic mobile phases.
In Figure 2-4, a representative spectrum for 4-nitro¬
anisole in methanol is shown. One advantage of the use of
this scale is that the spectral peak of interest (due to
the nitro group) is widely separated from that of the

ABSORBANCE
43
WAVELENGTH (ni.)
Figure 2-4. Representative UV/VIS absorbance spectrum of
4-nitroanisole in methanol. Concentrations
for the two curves are top, 0.1 mg/mL; bottom,
0.02 mg/mL.
500

44
aromatic ir-electron system. As discussed in Chapter I,
overlap of peaks can be a problem, as best exemplified with
Z-values (Kosower, 1958), in which the charge transfer peak
merges with that of the pyridine ring in highly aqueous
mixtures.
The results of dipolarity/polarizability
measurements for binary methanol/water mixtures appear in
Figures 2-5 and 2-6. In terms of percentage methanol
(Figure 2-5), the values are seen to decrease steadily,
in a highly nonlinear fashion. However, when the data are
plotted versus mole fraction of methanol (Figure 2-6), a
nearly straight line results (r- = 0.9959, s = 0.0119).
In Figures 2-7 and 2-8, the corresponding measurements
for the acetonitrile/water solvent mixtures are depicted.
Here the variation is much more complex; this is especially
true when compared to percentage of acetonitrile (Figure
2-7), where there are at least two points of inflection at
approximately the 30 and 70% concentrations. In contrast
to methanol/water mixtures, the variation with respect to
mole fraction of acetonitrile (Figure 2-8) is seen to be
highly nonlinear.
The ** scale of solvent dipolarity/polarizability is
distinctly different from the E^(30) scale in that it is
specifically intended to exclude hydrogen bond
donor/acceptor effects. As such these results then show

45
% Methanol
Figure 2-5. Measurements of u* dipolarity/polarizabi1ity
for methanol/water mixtures with respect to
percent methanol.

46
Figure 2-6. Measurements of it* dipolarity/polarizability
for methanol/water mixtures with respect to
mole fraction of methanol.

47
% Acetonitrile
Figure 2-7. Measurements of ir* dipolarity/polarizability
for acetonitrile/water mixtures with respect
to percent acetonitrile.

48
1.2
1.1
1 .0
JJ -X- 0.9
0.8
0.7
0.6
0.0 0.2 0.4 0.6 0.8 1.0
* Acetonitri le
Figure 2-8. Measurements of n* dipolarity/polarizability
for acetonitrile/water mixtures with respect
to mole fraction of acetonitrile.

49
the variation in polarity due only to dipole/dipole,
dipole/induced dipole, and dispersion interactions. Thus
it is not surprising that at 100# organic concentration,
methanol is actually less, polar than acetonitrile (â– "*
values of 0.57 and 0.67, respectively). This is a direct
reflection of the fact that the nitrile bond of
acetonitrile is much more dipolar in nature than either the
C-0 or 0-H bonds of methanol. Kamlet et al. (1983) have
reported it* values of 0.60 and 0.75 for methanol and
acetonitrile, respectively. These compare with the values
reported here of 0.57 and 0.67 for the cor responding
solvents. This discrepancy between the values reported by
Kamlet et al. and shown here is not significant, however.
In the present work, n* values were calculated from
measurements obtained with one solute (4-nitroanisole) ,
while those reported by Kamlet et al. (1983) are actually
the values that lead to the most consistent result from
several test solutes. In fact, in the original paper
describing the ir* scale, Kamlet et al. (1977) reported
values of 0.58 and 0.71 for methanol and acetonitrile,
respectively.
Based solely on the ir* scale, one would conclude that
methanol should be a stronger (less polar) organic modifier
for RPLC. However, this conclusion does not agree with the
known properties of the two organic modifiers, since
acetonitrile behaves as a more nonpolar, hence stronger,

50
solvent in RPLC. Also, one would expect (based on tt*
values) that methanol would solvate the stationary phase
alkyl chains to a greater extent, which, again, is simply
not consistent with the known properties of the two
modifiers (as discussed in Chapters I and V).
Erp( 30)-Values
A representative spectrum for ET-30 dissolved in pure
methanol is shown in Figure 2-9. The very large absorption
at wavelengths less than 400 nm is due to the aromatic ir-
electron system. In pure water, Araax decreases to 453 nm
(Dimroth et al., 1963a; a 10 cm path length cell was
used). It was not possible to obtain spectra of E pure water (due to its extremely low solubility; <10-0^ M),
so this
value has been
used
in the following figures.
In
Figures 2-10
and
2-11, the
Erji (30)-values
are
plotted
with respect
to
percent and
mole fraction
of
methanol
, respectively
•
In Figures 2
-12 and 2-13,
the
corresponding results
for
acetonitrile/water mixtures
are
shown.
With both organic modifiers, the ET(30) polarity is
clearly a nonlinear function of composition; this is not
surprising since none of the solvents form thermo¬
dynamically ideal solutions. For a thermodynamically ideal
binary solvent mixture, any bulk physical property, such a
dielectric constant or viscosity, is expected to be a

ABSORBANCE
51
Figure 2-9.
Representative UV/VIS absorption spectrum of
the ET-30 dye dissolved in methanol.

52
Et(30)
Measurements of Eij(30) polarity for methanol/
water mixtures with respect to percent
methanol.
Figure 2-10.

53
Et(30)
Figure 2-11.
Measurements of Ej.(30) polarity for methanol/
water mixtures with respect to mole fraction
of methanol.

54
Figure 2-12. Measurements of Erp(30) polarity for aceto¬
nitrile/water mixtures with respect to
percent acetonitrile.

55
Figure 2-13. Measurements of E/j.(30) polarity for aceto¬
nitrile/water mixtures with respect to mole
fraction of acetonitrile.

55
linear function of the mole fraction of either component.
This is also the case for empirical solvent polarity
measurements. For example, this was reported to be true
for the 2^(30) polarity of binary mixtures of 1,2-
dibroraoethane and 1 ,2-dibroraopropane, whose mixtures obey
Raoult's law, demonstrating ideal solution behavior
(Balakrishnan and Easteal, 1981a).
That raethanol/water and acetonitrile/water mixtures
are not ideal solutions is also evidenced by the nonlinear
variation in viscosity and dielectric constant (Horvath and
Melander, 1977). Thus, it is not surprising that the
measured E,j(30) polarity varies in a highly nonlinear
manner versus either percent or mole fraction of organic
component. The nonlinearity of these diverse properties
also illustrates the danger of assuming strictly additive
solvent properties, as is done in the derivation of both
liquid chromatographic retention models and gradient
elution schemes. It should also be pointed out here that
in gas chromatography, blending of stationary phase
materials can be done with this assumption in mind. This
is a reflection of the fact that these phases are almost
always nonpolar or weakly polar, nonhydrogen bonding
materials, and thus mixtures are nearly ideal in a
thermodynamic sense (Chien et al., 1980). Also, the mobile
phases used in gas chromatography are nearly inert gases

57
(hydrogen, helium, or nitrogen) and do not solvate the
stationary phase.
It is apparent that the variation in polarity of the
two systems is quite different. The different character of
these curves is a reflection of the differing hydrogen
bonding abilities of the two organic solvents. In the case
of acetonitrile, it is obvious that for concentrations
greater than 80# (by volume), the measured polarity
decreases rapidly.
Balakrishnan and Easteal (1931b) have discussed the
variation in E^(30) polarity in acetonitrile/water mixtures
and have found it to be consistent with the Naberukhin-
Rogov model (1971) for binary mixtures of water with a
nonelectrolyte. The Naberukhin-Rogov model describes the
structure in terms of two microphases (a and g) at
concentrations of greater than 0.15 (mole fraction) of
acetonitrile. The a phase consists primarily of highly
structured water, while microphase g contains mostly
acetonitrile. At concentrations of greater than 0.6,
Balakrishnan and Easteal (1981b) postulated that the g
microphase predominates, and the water exists as single
molecules coordinated to these "globules" of
acetonitrile. Further evidence of the existence of
microphases is the phase separation that occurs in this
system, at a critical temperature and concentration of
272 K and 33 mole # acetonitrile, respectively.

58
Unlike methanol, acetonitrile is a very weak hydrogen
bond donor solvent and thus as the concentration is
increased, the remaining water becomes specifically
associated with the ET-30 due to the presence of the
negatively charged phenoxide group. As the water is
completely removed, and the ET-30 is no longer stabilized
through this hydrogen-bonded network, the apparent polarity
plunges 46.0 kcal/mole. This large change in E.j(30)
polarity is not mirrored by the changes seen in log x'
retention measurements. Retention data for concentrations
greater than 80$ have not been included in the present data
analysis. There were 61 cases among these data sets where
the 90% acetonitrile point was not included; these were all
from one reference (Hanai and Hubert, 1933). It must also
be pointed out, however, that at these concentrations the
retention time will be very short for most solutes, so that
the resultant k' (approaching zero) and log k' values
(approaching minus infinity) will have the highest relative
uncertainty of the entire retention data set. In fact, the
average log k' for the 61 (90$ acetonitrile) points not
included was 0.049 (s = 0.089), corresponding to an average
k' of 1.12.

59
Relationship Between Snyder's P1 Polarity Values
and the Ern(50) Scale-
Snyder (1974, 1978) has devised the P' scale of
solvent polarity for use in characterizing solvents used in
liquid chromatography. These values are based on
gas/liquid partition coefficients for various solutes and
solvents reported in the literature (Rohrschneider,
1973). For each solvent, the logarithm of the corrected
partition coefficients (K"; corrected to account for
differences in molecular volume and concentration units)
for ethanol, dioxane, and nitroraethane are summed together
to calculate a P' polarity as shown below:
P' = log K"(1,4-dioxane) + log K"(ethanol)
+ log K"(nitroraethane) (2-2)
In this manner, the solvent’s ability to undergo three
types of interactions (proton donor/acceptor, polar) with
solutes is measured, and P' values then represent the total
of these potential interactions. Snyder also reported the
fractional contribution of each of the three test solutes
(Xe> X^, Xn parameters) to the overall P' value. Using
these partial contribution values, Snyder classified all
solvents into eight possible categories. This
classification is often referred to as Snyder's solvent

50
selectivity triangle, in that three characteristics (proton
donor, proton acceptor, and polar) are assigned to each of
the three vertices of a triangle). Each solvent can then
be placed into a unique position within this triangle on
the basis of its Xe, X^j, and Xn values.
Since Snyder's classification scheme is intended to be
useful for the measurement of solvent selectivity in liquid
chromatography, it is worthwhile to examine briefly the
relationship (if any) between the P' and Ej.(30) scales of
solvent polarity. The relationship between Snyder's eluent
strength parameters for NPLC and Erj(30) polarity has
already been discussed in Chapter I.
The easiest comparison that can be made is between the
P' (summed polarity) values reported by Snyder (1978) and
Eq>(30) polarity values for pure solvents reported by
Reichardt and Harbusch-Gornert (1983). There were 48 cases
in which tnis comparison could be made; the resultant
comparison plot is shown in Figure 2-14. While there is a
statistically significant correlation between the two sets
(r = 0.7986), there is also a great deal of scatter around
the line (s = 1.1146), so Erj(30) values cannot be used to
accurately predict P' values or vice versa. The line drawn
through the data (using linear regression) in Figure 2-14
has a slope of 0.1851±0.04 and y-intercept of -3.54±1.84.
That there is such a poor correlation is not
surprising, since the P' values represent the summation of

61
Figure 2-14. Comparison between Snyder's P' and Dimroth-
Reichardt's Erp(30) polarity values for pure
solvents.

62
the three interactions in proportions that will not
necessarily be similar to the responsiveness of the ET-30
probe. Also, it should be noted that according to the ?'
scale, methanol is a stronger organic modifier for RPLC (?'
= 5.1) than acetonitrile (P1 = 5.8), which is not in
agreement with the known chromatographic properties of
these two solvents.
Perhaps a better way to compare these scales is to
compare E>j(30) polarity values with the partial
contribution values (X9, Xd, and Xn) by using multiple
linear regression. This should allow the various
contributions to be more properly weighted. However, it
must be remembered that these partial values represent the
fraction of the total P' value for each solvent and will
always add up to one. Thus, the true magnitude of each of
the three interactions is masked, and to make a valid
comparison, one must first multiply each partial
contribution value by the total P' value for each
solvent. Using multiple linear regression, an attempt was
made to correlate each ET(30) value with the three
corrected partial contributions for the same solvent. For
the 48 cases, the multiple correlation coefficient was
found to be 0.3912, with a standard deviation of 3.685.
The equation relating the Eij(30) to the three interactions
was

63
Et(30) = 29.9±3.8 + 7.83+1.8 + 2.8+2.6
- 1.79±2.9 X¿ (2-3)
The regression coefficients indicate that the E scale is significantly related to only the terms derived
from the partition coefficients for ethanol and dioxane.
These results are shown graphically in Figure 2-15, where
the Et(30) values predicted by equation 2-3 are plotted
with respect to actual reported ET(30) polarity values
(Reichardt and Harbusch-Gornert, 1983). It is interesting
to note that this multiple linear regression leads to a
poorer standard deviation (s = 3.86) than obtained by
plotting the original P' versus E.j(30) values (s = 1.11).

64
Et(30)
(predicted)
Figure 2-15.
E-J-C30) (Actual)
Comparison between Erp(30) polarity values
predicted by equation 2-3 and actual ET(30)
polarity values reported by Reichardt and
Harbusch-Gornert (1983).

CHAPTER III
CORRELATIONS BETWEEN CHROMATOGRAPHIC
RETENTION AND MOBILE PHASE POLARITY
Experimental
Retention measurements (other than those reported in
the literature) were obtained with a Spectra-Physics SP8700
ternary proportioning LC system (Spectra-Physics, San Jose,
CA). Columns were an Altex Ultrasphere ODS (5 micron
particle size; Altex Scientific, San Ramon, CA) and a
Hamilton PRP-1 (10 micron; Hamilton Company, Reno, NV).
Both columns were of size 15 cm X 4.6 mm I.D. Test solutes
were obtained from Aldrich Chemical Co. (Milwaukee, WI) and
the Eastman Kodak Co. (Rochester, NY). Sample introduction
was achieved with either an Altex injector equipped with a
5 microliter sample loop (Altex Scientific, San Ramon, CA)
or a Rheodyne Model 7125 injector equipped with a 20
microliter sample loop (Rheodyne, Inc., Cotati, CA). Plow
rates were either 1.0 or 2.0 mL/min. The column was
therraostatted at 40±0.1°C with a Haake Model D1 water bath
(Haake, Saddle Brook, NJ). Solvents were obtained as
described previously (Experimental, Chapter II). A fixed
wavelength, 254 nm, Beckman Model 153 UV detector (Altex
Scientific, San Ramon, CA) was used.
65

oS
The retention times for an unretained species (tQ)
were evaluated with injections of the pure organic solvent
(either methanol or acetonitrile). For the Hamilton PRP-1
column, this proved to be difficult at low organic modifier
concentrations due to actual retention of the acetonitrile
or methanol. Other supposedly unretained solutes (such as
urea and uracil) exhibited similar behavior. Therefore,
the tQ obtained from injections of pure organic modifier at
60% organic modifier concentration was used, since at this
concentration the retention time reached a minimum in each
of the two solvent systems.
Simple linear regression calculations were done with
the program "Curve Fitter" (Interactive Microware, Inc.,
State College, PA) run on an Apple II Plus 43K
microcomputer (Apple Computer, Inc., Cupertino, CA). The
program was modified to allow calculation of 95$ confidence
intervals
for
slope
and y-intercept values.
This
program
was also
use
d to
interpolate E^(30) values
for
solvent
compositions
that
had not been measured
(e.g
., 45$
methanol/water).
When curve fitting the data to either a linear or 2nd
degree polynomial, the resultant standard deviations
(s-values) were used to calculated an F-ratio as
F = s(linear)/s(2nd degree polynomial)
(3-1)

67
The significance level (<*% values reported in Table
3-1) of a given F-ratio was then determined by using the
program "F Distribution" (public domain software provided
by Computer Learning Center, Tacoma, WA). In this way,
much more accurate estimates of the significance level were
obtained than those from published F-distribution
statistical tables.
.Multiple linear regression calculations were done by
using the program "Statworks" (Datametrics, Inc., and
Heyden and Son Limited, Philadelphia, PA), run on a
Macintosh 512K computer (Apple Computer, Inc., Cupertino,
CA).
Results
In RPLC, retention of solutes decreases as the
concentration of organic modifier is increased. That is,
as the overall polarity of the mobile phase is decreased,
solutes will spend less time in the stationary phase. Of
course, there are many ways to express this decrease in
polarity; the simplest measure of this is the proportion of
the organic modifier. Traditionally, chromatographers have
measured capacity factors at various organic modifier
concentrations and then plotted the logarithm (base 10) of
the capacity factor as a function of this concentration.
In the present discussion, the abbreviation "log" shall
denote the base ten logarithm. Plotting the logarithm of

68
capacity factor is quite logical, owing to its dependence
on the free energy of transfer (AG) of the solute between
the mobile and stationary phases. This relationship is
expressed by the following equation:
log k' = (-2.303 AG/RT) + logU) (3-2)
where is the phase ratio for the particular column.
Thus, plotting log k' versus percent organic modifier gives
a sense of the change in the energetics of chromatographic
retention as the composition of the mobile phase is
changed. Whether or not this type of plot is linear in
nature has been the subject of much debate. In terms of
concentration, the only reason that percent organic
modifier is usually used is that all chromatographic
instrumentation has been built to deliver mixtures by
volume percentage. While plots of log k' versus percent
organic modifier often appear to be linear, they will
always exhibit some curvature if a wide enough
concentration range is investigated and are best fit by a
quadratic equation (Schoenmakers et al., 1933). To
illustrate this point, in Figure 3-1, retention data for 4-
nitrophenol have been plotted with respect to percent
organic modifier. If the data are fitted with a straight
line, a squared correlation coefficient of 0.9803 is found,
while a quadratic curve-fitting leads to an increase to

59
0.9983. Clearly, the variation in the log k' values is
best accounted for by an equation containing a quadratic
term.
From a physical standpoint, it would be much more
logical to plot the retention data with respect to the mole
fraction of organic modifier. That is, solution properties
(of which reversed phase chromatographic retention can be
considered to be a result of) are best expressed by
observing the property as a function of mole fraction. In
such cases, deviations from linearity are then (by
definition) deviations from nonideal solution behavior.
The extent to which plotting log k' values versus
either volume percent or mole fraction or organic modifier
can affect the curve shape is illustrated in Figures 3-2
and 3-3. For both methanol and acetonitrile, the mole
fraction has been plotted with respect to percent of
organic modifier. In both cases, the actual mole percent
is significantly lower than the percent by volume at all
concentrations (except, of course, at the 0 and 100%
points). Using the same log k* values shown in Figure 3-1,
the data have been re-plotted with respect to the mole
fraction of acetonitrile in Figure 3-4. Here the curvature
has been accentuated, and a straight line fit of the data
yields a r~ of 0.9332. Since the variation in mobile phase
strength is not necessarily directly related to the percent
(by volume) or the mole fraction, a more logical approach

70
would be to compare retention with experimentally derived
measures of mobile phase polarity, such as the u* and
E^(30) values. In Figure 3-5, log k' values for 4-
nitrophenol (same values as used in Figures 3-1 and 3-4)
are plotted with respect to the it* values for the same
composition (ir*-values discussed in Chapter II). In this
case, there is a point of inflection, and the data are best
fit by a 3rd degree polynomial. As discussed in Chapter
II, one would not expect the tt* scale to correlate well
with chromatographic retention, owing to its insensitivity
(by design) to hydrogen bonding effects in solution. This
is clearly reflected by the data shown in Figure 3-5. A
straight line fit of the data results in a squared
correlation coefficient of 0.9667.
The E^(30) values discussed in Chapter II can also be
compared with chromatographic retention. The ET(30) scale
has been shown to be sensitive to both hydrogen bonding and
dipolarity effects (as discussed in Chapter I) and thus may
serve as a better indicator of the strength of the mobile
phases used in RPLC. In Figure 3-6, retention data used in
previous figures have been plotted with respect to the
measured E^OO) polarity for the same mobile phase
composition. In this case, the linearity is much greater,
yielding a square correlation coefficient of 0.9950 when
fitted to a straight line model. This is in great contrast

71
Figure 3-1.
Retention data for 4-nitrophenol plotted with
respect to percent acetonitrile. Ultrasphere
ODS (C-18) column; flow rate 1.0 mL/min.

72
O 20 40 60 80 100
% Methanol
Figure 3-2. Variation in mole fraction of methanol as a
function of volume percent.

73
Figure 3-3. Variation in mole fraction of acetonitrile as
a function of volume percent.

74
y
Acetonitrile
Figure 3-4. Retention data for 4-nitrophenol plotted with
respect to mole fraction of acetonitrile.
Ultrasphere ODS (C-18) column; flow rate 1.0
mL/min.

75
Retention data for 4-nitrophenol plotted with
respect to ir * dipolarity/polarizabi 1 ity for
the same solvent mixtures. Ultrasphere ODS
(C-18) column; flow rate 1.0 mL/min.
Figure 3-5.

76
Et(30)
Retention data for 4-nitrophenol plotted with
respect to the E.p(30) polarity for the same
solvent mixtures. Ultrasphere ODS (C-18)
column; flow rate 1.0 mL/min.
Figure 3-6.

77
to the other three values for Figures 3-1, 3-4, and 3-5, of
0.9803, 0.9332, and 0.9667. The best fit is obtained when
the log k' values are plotted with respect to the measured
E^(30) polarity for the same mobile phase mixture.
Of course, the previous figures pertain to only one
individual set of retention data generated for this
research; in order to make any generalizations about the
correlations between the various variables, it is necessary
to examine a large body of chromatographic data. A total
of 332 sets of chromatographic retention data (log k*
versus percent organic modifier) have been examined.
Retention data reported in the literature, as well as data
generated exclusively for this study, have been included in
these correlations. Hereafter the discussion will be
confined to two types of correlations: those between log
k' and either percent organic modifier or ET(30) polarity.
Linear regression was carried out for all retention
data sets with the log k' data compared to both percent
organic modifier and the ET(30) polarity. The results of
these correlations are compiled in Table 3-1. The data
have been sorted in a hierarchical manner, using the
following sequence: organic modifier, column, and
solute. Squared correlation coefficients (r^) for both log
k' versus organic modifier and E>p(30) polarity are
reported, as well as the regression coefficients for the

Table 3-1 .
Linear regression results for correlations between log k' and either percent organic
modifier or E.p(30) polarity.
•column
Solvent/% Range
r2 va. %
r2 vs. Et
(30) SlopelxlO2)
-ly-lnt)
•
n
ba*
Reference
1
2-N1troanlline
r
A
ACN/10-60
0.9869
0.9909
23.413.1
13.211.8
0.0498
6
This Work
2
4-Nltroanllino
A
ACN/10-60
0.9865
0.9903
20.812.8
1 1 .911 .7
0.0456
6
This Work
3
4-N1trophonol
A
ACN/10-60
0.9803
0.9948
24.512 .4
13.911.4
0.0391
6
This Work
4
4-Nitroanlsolo
A
ACN/10-80
0.9874
0.9859
31.113.7
17.312.1
0.0870
8
99.2
This Work
5
Benzene
A
ACN/31.3-68.7
0.9957
0.9947
34.517.6
19.014.3
0.0342
4
This Work
6
Butylbenzene
A
ACN/31 .3-68.7
0.9870
0.9999
60.2H .9
32.7H .1
0.009
4
This Work
7
Ethylbenzene
A
ACN/31.3-68.7
0.9912
0.9988
47.215.1
25.812.9
0.0219
4
This Work
8
Isopropylbenzene
A
ACN/31.3-68.7
0.9900
0.9992
52.3i4.4
28.512.5
0.0203
4
This Work
9
Anthracene
A
ACN/40-77.5
0.9883
0.9937
61.915.4
33.9t 3 .0
0.0467
6
Thl6 Work
10
Phenanthrene
A
ACN/40-77.5
0.9868
0.9949
60.014.7
32 .912 .6
0.0405
6
This Work
11
Pyrene
A
ACN/40-77.5
0.9842
0.9962
62.514.2
34.012.4
0.0366
6
This Work
12
Toluene
A
ACN/31.3-68.7
0.9937
0.9973
40.916.6
22.513.8
0.0291
4
This Work
n
Anthracene
A
ACN/50-80
0.9893
0.9949
68.015.6
37.313.1
0.0296
7
Llpford (1985)
14
Napthalene
A
ACN/50-80
0.9991
0.9894
55.416.6
30.513.7
0.0347
7
83.3
"
15
1,2-Dlhydroxybenzono
G
ACN/10-80
0.9110
0.9927
15.911.4
8.8810.78
0.0319
8
Hanal and Hubert
16
1,3-Dlhydroxybenzeno
G
ACN/10-80
0.8964
0.9879
14.OH .6
7.9010.89
0.0364
8
95.1
"
17
1,4-Dlhydroxybenzene
G
ACN/10-80
0.9103
0.9903
10.Ill.0
5.7510.57
0.0234
8
••
18
2-Hydroxyacetophenone
G
ACN/10-80
0.8792
0.9821
19.612.6
10.911.5
0.0620
8
98.5
"
19
4-Me thylphenol
G
ACN/10-80
0.9427
0.9976
27.111 .3
14.910.76
0.0310
8
M
20
4-Nitrophenol
G
ACN/10-80
0.9414
0.9965
26.9i3 .3
14.911.9
0.0372
a
M
21
Phenol
G
ACN/10-80
0.9480
0.9975
20.911 .0
11.6±0.60
0.0366
8
H
22
2,4-Dlnltrophenol
G
ACN/20-80
0.9652
0.9942
31 .112.7
17.U1 .6
0 .0426
7
"
23
2,5-Dinitrophenol
G
ACN/20-80
0.9690
0.9933
31.8l3 .0
17.5.1.7
0.0468
7
"
24
2,6-Dlnitrophenol
G
ACN/20-80
0.9754
0.9918
29.4i3.1
16.211.8
0.0480
7
"
25
2-Bromophenol
G
ACN/20-80
0.9530
0.9952
31 .112.5
17.U1 .4
0.0388
7
"
26
2-Chlorophenol
G
ACN/20-80
0.9536
0.9949
29.312.4
16.111.4
0.0378
7
"
27
2-Ethylphenol
G
ACN/20-80
0.9478
0.9943
34.213.0
18.811.7
0.0464
7
"
28
2-Methylphenol
G
ACN/20-80
0.9604
0.9962
27.712.0
15.311.1
0.0309
7
"
29
2-N1trophenol
G
ACN/20-80
0.9700
0.9950
29.212.4
15.911.4
0.0371
7
"
30
3,4-Dime thylphenol
G
ACN/20-80
0.9466
0.9939
32.2i2.9
17.7H .7
0.0455
7
"
31
3,4-Dinitrophenol
G
ACN/20-BOi
0.9441
0.9921
36.313.7
20.112.1
0.0581
7
"
32
3,5-Dimethylphenol
G
ACN/20-00
0.9493
0.9944
33.212.9
18.211 .6
0 .0450
7
"
33
3-Bromophenol
G
ACN/20-80
0.9516
0.9949
34.212.8
18.811 .6
0.0441
7
34
3-Chlorophenol
G
ACN/20-80
0.9519
0.9946
32.412.7
17.811.6
0.0429
7
"
35
3-E thylphenol
G
ACN/20-80
0.9515
0.9949
33.912.8
18.6.1.6
0.0440
7
"

Table 3-1—continued
Data
Soluta «column
Solvent/% Ranga
r^ va. 1
36
3-Methylphenol
G
ACH/20-00
0.9536
37
3-Nltrophenol
G
ACN/20-80
0.9490
38
4-Bromophenol
G
ACN/20-80
0.9475
39
4-Chlorophenol
G
ACN/20-80
0.9496
40
4-Ethylphenol
G
ACN/20-80
0.9500
41
1-Hydroxynaptha lene
G
ACN/30-80
0.9588
42
2,3 ,5-Trichlorophenol
G
ACN/30-80
0.9659
43
2,3 ,5-Trimethylphenol
G
ACN/30-80
0.9640
44
2,3 ,6-Trimethylphenol
G
ACN/30-80
0.9688
45
2,3-Dichlorophenol
G
ACN/30-80
0.9562
46
2,3-Dime thy1phenol
G
ACN/30-80
0.9641
47
2,4,-Dlmethylphenol
G
ACN/30-80
0.9552
48
2,4,6-Trimethylphenol
G
ACN/30-80
0.9681
49
2,4-Dibromophenol
G
ACN/30-80
0.9606
50
2,4-Dichlorophenol
G
ACN/30-80
0.9602
51
2,5-Dichlorophenol
G
ACN/30-80
0.9639
52
2,5-Dimethylphenol
G
ACN/30-80
0.9652
53
2,6-Dibromophenol
G
ACN/30-80
0.9670
54
2,6-Dichlorophenol
G
ACN/30-80
0.9677
55
2 ,6-Dimethylphenol
G
ACN/30-80
0.9689
56
2-Chloro-5-Methy1phenol
G
ACN/30-80
0.9646
57
2-Hydroxynaphtha lene
G
ACN/30-80
0.9530
58
3 ,4-Dichlorophenol
G
ACN/30-80
0.9589
59
3,5-Dichlorophenol
G
ACN/30-80
0.9634
60
4-Chloro-2-Methylphenol
G
ACN/30-80
0.9626
61
4-Chloro-3,5-Dimethylphenol
G
ACN/30-80
0.9588
62
4-Chloro-3-Hethylphenol
G
ACN/30-00
0.9591
63
4-Hydroxybutylbenzoate
G
ACN/30-80
0.9510
64
4-Hydroxypropylbenzoate
G
ACN/30-80
0.9481
65
1-Hydroxy-2,4-Dinltronapthalene
G
ACN/40-00
0.9770
66
2,3,4,5-Tetrachlorophenol
G
ACN/40-80
0.9759
67
2,3,4-Trichlorophenol
G
ACN/40-00
0.9732
68
2 ,3 ,5,6-Tetrachlorophenol
G
ACN/40-80
0.9780
69
2,3,5,6-Tetramethylphenol
G
ACN/40-80
0.9826
70
2,3,6-Trichlorophenol
G
ACN/40-00'
0.9772
71
2,4,5-Trichlorophenol
G
ACN/40-80|
0.9757
72
2,4,6-Trichlorophenol
G
ACN/40-80
0.9786
73
3,4.5-Trichloroohenol
G
ACN/40-80
0.9744
74
4-tert-Butylphenol
G
ACN/40-00
0.9722
75
Pentachlorophenol
G
ACN/50-80
0.9913
Rtfir ! va. Et( 30)
Slope(x102)
-(y-lnt)
0
0.9955
27 .3±2.1
15.011.2
0.0330
0.9943
27.7±2 .4
15.311.4
O.0377
0.9942
34 .0±3 .0
10.7H .7
0.0466
0.9949
32.0±2.6
17.611.5
0.0411
0.9946
34.U2.9
10.711 .6
0.0451
0.9077
38.315.9
21.013.4
0.0582
0.9915
38.015 .0
21.212.8
0.0409
0.9903
30.915.4
21.313.0
0.0525
0.9921
38.514.5
21 .0i2 .7
0.0465
0.9076
30.015.9
20.913.4
0.0581
0.9902
33 .214.6
10.212.6
0.0450
0.9842
32.915.8
18.013.3
0.0560
0.9922
39.014.0
21.312.7
0.0473
0.9892
43.216.3
23.6,3.5
0.0614
0.9891
39.3,5.7
21 .613.3
0.0563
0.9902
39.615 .5
21.713.1
0.0537
0.9900
33.014.5
18.512.6
0.0442
0.9919
39.514.9
21.6l2.0
0 .0485
0.9918
36.014.6
19.712.6
0.0447
0.9921
33.514.2
10.312.4
0.0407
0.9905
35.514.8
19.512.7
0.0475
0.9849
36.216.2
19.913.5
0.0610
0.9885
40.616.1
22.313.5
0.0598
0.9904
43.415.9
23.7,3.4
0.0502
0.9090
38.6,5.4
21 .213.1
0.0534
0.9884
42.416.4
23.2,3.6
0.0624
0.9801
37.015.6
20.313.2
0.0553
0.9849
45 .617.8
25.014.4
0.0760
0.9826
37 .917.0
20.814.0
0.0606
0.9050
44.5110.1
24.315.7
0.0507
0.9835
50.9H2.1
27.716 .0
0.0703
0.9013
43. U10.9
23.516.1
0.0635
0.9052
49 .6U 1.1
27.016.3
0.0649
0.9894
37.317.1
20.214.0
0.0413
0.9044
41 .019.7
22.015.4
0.0562
0.9830
44.8110.8
24.516.1
0.0629
0.9055
43 .0i9.6
23.515.4
0.0550
0.9821
45.9111.4
25.1l6.4
0.0662
0.9800
41 .6H0.9
22.716.1
0.0635
0.9916
48.6113 .6
26.3,7.6
0.0402
Hanai and Hubert (1983)
61 .3
91.1
75.6
84.1
84.4
-0
KD
83.7
85.6
79.8
85.8
83.0
89.9
90.1
99.0
98 .8
98.9
90.7
96.7
90.7
90.7
90.6
90.0
98.6
JT-
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
5
5
5
5
5
5
5
5
5
5
4

Table 3-1—continued
Data
Soluta
•column
Solvent/% Range
r2 va. %
r2 v«. et(3i
76
Aniline
G
ACN/10-70
0.9720
0.9951
77
N-Me thylanlllne
G
ACN/20-70
0.9074
0.9901
70
N-Ethylanlline
G
ACN/20-70
0.9070
0.9904
79
N-Butylanlllne
G
ACN/20-70
0 .9007
0.9973
00
N.N-Dlmethylanlllne
G
ACN/30-70
0.9060
0.9901
01
N,N-Dlethylanlllne
G
ACN/40-70
0.9001
0.9970
02
2-Methylanlline
G
ACN/10-70
0.9704
0.9964
03
3-Methylan11lne
G
ACN/10-70
0.9651
0.9967
04
4-Methylanlllne
G
ACN/10-70
0.9654
0.9973
05
2,4-Dlmethylanlllne
G
ACN/20-70
0.9716
0.9970
06
4-Methoxyanillne
G
ACN/10-70
0.9416
0.9901
07
2,4-Dlethoxyaniline
G
ACN/20-70
0.9691
0.9903
00
2-Chloroanillne
G
ACN/20-70
0.9020
0.9927
09
3-Chloroanlline
G
ACN/20-70
0.9705
0.9949
90
4-Chloroanlline
G
ACN/20-70
0.9742
0.9964
91
2 ,5-Dlchloroani1lne
G
ACN/30-70
0.9006
0.9904
92
3,4-Dlchloroanlllne
G
ACN/30-70
0.9767
0.9902
93
4-Bromoan11lne
G
ACN/20-70
0.9743
0.9936
94
2-N1troanlllne
G
ACN/10-70
0.9737
0.9936
95
3-Nltroanl1lne
G
ACN/10-70
0.9006
0.9095
96
4-N1troanlline
G
ACN/10-70
0.9770
0.9924
97
Pyridine
G
ACN/10-70
0.0965
0.9003
90
2-Aminopyrldine
G
ACN/10-70
0.7304
0.9017
99
3-Amlnopyrldlne
G
ACN/10-70
0.0436
0.9661
100
2-Methylpyridlne
G
ACN/10-70
0.0974
0.9007
101
3-Methylpyrldlne
G
ACN/10-70
0.9142
0.9940
102
4-Methylpyridlne
G
ACN/10-70
0.9072
0.9920
103
4-Ethylpyrldine
G
ACN/20-70
0.9420
0.9973
104
4-tert-Butylpyridine
G
ACN/30-70
0.9637
0.9956
105
2,4-Dimethylpyridlne
G
ACN/30-70
0.9606
0.9967
106
2,5-Dimethylpyridlne
G
ACN/20-70
0.9432
0.9973
107
2 ,6-Dlmethylpyridlne
G
ACN/10-70
0.9072
0.9920
100
Pyrazlne
G
ACN/10-70
0.7610
0.9196
109
2-Methylpyrazlne
G
ACN/10-70
0.0009
0.9433
1 10
2,5-Dlmethylpyrazlne
G
ACN/10-70
0.0105
0.9530
111
2,6-Dlmethylpyrazine
G
ACN/10-70
0.0103
0.9472
112
Quinoline
G
ACN/20-70
0.9370
0.9959
1 13
2-Me thylquinollne
G
ACN/20-70
0.9425
0.9971
114
4-Methylquinoline
G
ACN/20-70
0.9573
0.9964
1 15
0-Methylquinoline
G
ACN/20-70
0.9551
0.9905
116
5-Aminolndan
G
ACN/20-70
0.9669
0.9901
1 17
5-Acnl nolndole
G
ACN/10-70
0.9403
0.9960
1 10
1-Amlnonapthalene
G
ACN/20-70
0.9721
0.9976
1 19
2-Aminonapthalene
G
ACN/20-70
0.9691
0.9977
120
1-Aminoanthracene
G
ACN/30-70
0.9717
0 .9976
121
1-Ami nopyrene
G
ACN/40-70
0.9019
0.9937
Beferenc<
ilope(xl02)
-(y-int)
a
bg%
19.5±1.6
11.110.9
0.0300
7
20.0±3.9
15.612.2
0.0475
6
33.0±4.5
10.312.6
0.0553
6
53.910.6
29.714.9
0.0263
4
30.413.0
21.2H.7
0.0205
5
54.119.0
29.715.1
0.0276
4
24.5±1.7
13.011.0
0.0334
7
25.3H .7
14.211 .0
0 .0329
7
25.4H .5
14.310.09
0.0301
7
31 .4121.
17.511.2
0.0252
6
21.311.1
12.210.6
0.0212
7
36.512.1
20.3t1 .2
0.0256
6
30.713.7
17.112.1
0.0449
6
32.113.2
10.011.0
0.0256
6
31.312.6
17.611.5
0.0322
6
44.313.3
24.611.9
0.0222
5
43.013.4
24.0H .9
0.0227
5
33.512.0
10.011.6
0.0330
6
20.612.6
16.111.5
0.0520
7
26.213.1
14.011.0
0.0613
7
95.7
26.312.6
14.911.5
0.0520
7
17.012.1
9 .011 .2
0.0420
7
93.1
12.514.0
7.712.0
0.0936
7
90.5
15.613.3
9.3l 1 .9
0.0661
7
97.1
22.712.0
12.011.6
0.0412
7
96.9
23.512.1
13.211.2
0.0412
7
23.612.4
13.311.4
0.0474
7
20.212.0
15.711.2
0.0250
6
37.714.6
20.012.6
0.0309
5
26.012.0
14.911.6
0.0192
5
26.6H.9
14.011.1
0.0236
6
10.114.9
10.512.0
0.0556
7
10.213.5
6.212.0
0.0601
7
96.3
14.214.0
0.412.3
0.0707
7
90.3
10.214.6
10.512.7
0.0916
7
99.5
10.114.9
10 .512.0
0.0966
7
97 .0
29.012.6
16.7H .5
0.0324
6
33 .612.5
10 .711.4
0.0309
6
32.4*2.7
10.0*1.5
0.0329
6
34.7H.0
19.2H .1
0.0226
6
34.012.0
19.011.2
0.0251
6
21.0H.4
12.210.0
0.0274
7
36.112.5
20.2l1.4
0.0304
6
37.112.5
20.7H .4
0.0303
6
53.314 .0
29.512.7
0.0326
5
55.5H3.4
30.717.6
0.0401
4
Hanal and Hubert (1905)
CD
o

3l<
Data
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
3-1 —continued
r2 vs. %
r2 va. Et(30)
Slope(x102]
-(y-int)
a
Reference
2,4-Dlnitrophenol
II
ACN/20-80
0 9652
0.9917
31 .8*3.3
17 .7*1 .9
0.0521
7
llanal and Huber
3-Bromophenol
H
ACN/20-80
0 9495
0.9919
34.7t3 .6
19.3*2.1
0.0565
7
"
4-Nitrophenol
H
ACN/20-80
0 9536
0.9936
27.3*2.5
15.3*1.4
0.0394
7
"
2,3,4,5-Tetrachlorophenol
H
ACN/40-80
0 9675
0.9702
52.4116.9
28.8*12.5
0.0982
5
71.4
"
2,4,5-Trichlorophenol
H
ACN/40-80
0 9688
0.9688
45.7*15.1
25.2*8.5
0.0876
5
70.7
2,5- Dlchlorophenol
H
ACN/30-80
0 9653
0.9877
40.616.3
22.5*3.6
0.617
6
61 .8
••
4-Chloro-3,5-Dimethylphenol
H
ACN/30-80
0 9024
0.9434
42.3*14.4
23.4*8.2
0.1412
6
65.2
••
4-Chioro-3-Me thylphenol
H
ACN/30-80
0 9587
0 .9847
37.9*6.6
21.0*3.7
0.0644
6
68.7
"
Toluene
B
ACN/25-40
0 9905
0.9724
28.3*14.5
15.8*8.4
0.0662
4
58.3
Woodbum ( 1985)
n-Butylbenzene
B
ACN/25-40
0 9998
0.9936
47.5*11.6
26.3*6.7
0.0531
4
-
1,2,4-Trimethylbenzene
B
ACN/25-50
0 9994
0.9912
38.5*11.0
21 .4*6.4
0.0504
4
"
An thracene
B
ACN/25-50
0 9988
0.9917
51.2*14.3
28.5*8.3
0.0653
4
"
Benzene
B
ACN/25-50
0 9771
0.9522
22.5*15
12.6*8.9
0.0699
4
53.4
. *
Biphenyl
B
ACN/25-50
0 9995
0.9919
45.0*12.5
25.0*7.2
0.0567
4
"
Bromobenzene
B
ACN/25-50
0 9947
0.9803
31 .2*13.5
17.4*7.8
0.0614
4
83.9
Chlorobenzene
B
ACN/25-50
0 9880
0.9686
29.3*16.1
16.4*9.3
0.0735
4
85.5
Ethylbenzene
B
ACN/25-50
0.9954
0.9815
34.4*14.4
19.1*8.4
0.0656
4
57.1
"
Fluoranthene
B
ACN/25-50
0 9998
0.9968
54.2*9.4
30.2*5.5
0.0429
4
"
Fluorobenzene
B
ACN/25-50
0.9846
0.9630
25.2*15.0
14.2*8.7
0.0688
4
78.8
Iodobenzene
B
ACN/25-50
0 9965
0.9838
34.2*13.4
19.0*7.8
0.0609
4
78 .6
"
Napthalene
B
ACN/25-50
0.9977
0.9865
36.7*13.1
20.5*7.6
0.0596
5
67.1
Nitrobenzene
B
ACN/25-50
0 9854
0.9642
23.8*14.0
13.4*8.1
0.0639
4
77.6
"
Phenanthrene
B
ACN/25-50
0.9999
0.9950
48.9*10.5
27.2*6.1
0.0484
4
M
Pyrene
B
ACN/25-50
0 9999
0.9966
53.9*9.5
30.0*5.5
0.0435
4
"
m-Diethylbenzene
B
ACN/25-50
0.9989
0.9895
46.2*14.4
25.6*8.4
0.0661
4
78.1
"
n-Propylbenzene
B
ACN/25-50
0 9981
0.9873
40.9*14.1
22.7*8.2
0.0644
4
54.5
"
o-Xylene
B
ACN/25-50
0.9941
0.9789
33.0*14 .7
18.4*8.5
0.0674
4
55.3
"
p-Xylene
B
ACN/25-50
0 9920
0.9752
33.7*16.3
18.7*9.5
0.0747
4
79.8
M
Chrysene
B
ACN/30-50
0 9997
0.9981
63.3*34.4
35.2*19.8
0.0378
3
"
1,2,4-Trimethylbenzene
C
ACN/30-60
0 9692
0.9993
41 .6*3.0
22.9*1.7
0.0147
4
"
Anthracene
C
ACN/30-60
0 9881
0.9994
50.7*3.7
28.0*2.1
0.0174
4
"
Benzene
C
ACN/30-60
0 9989
0.9936
26.9*6.6
15 .0*3 .8
0.0298
4
"
Biphenyl
C
ACN/30-60
0 9908
0.9995
46 .8*3.5
25.9*x.0
0.0147
4
"
Bromobenzene
C
ACN/30-60
0 9962
0.9973
34.7*5.4
19.3*3.1
0.0247
4
"
Chlorobenzene
C
ACN/30-60
0.9976
0.9964
33.0*6.1
18 .3*3 .5
0.0275
4
••
Chrysene
C
ACN/30-60.
0 9823
0.9985
60.7*7.1
33.5*4.0
0.0325
4
"
Ethylbenzene
C
ACN/30-60
0 9966
0.9977
37.8*5.5
20.9*3.2
0.0250
4
"
Fluoranthene
C
ACN/30-60
0.9869
0.9994
53.8*4.1
29.7*2.4
0.0175
4
"
Fluorobenzene
C
ACN/30-60
0 9982
0.9954
29.0*6.1
16.2*3.5
0.0272
4
"
Iodobenzene
C
ACN/30-60
0.9946
0.9986
37.1*4.2
20.5*2.4
0.0189
4
"

Table 3-1—continued
“column
Solvont/% Kamje
r2 va.
162
Napthalene
C
ACN/30-60
0.9936
163
Nitrobenzene
C
ACN/30-60
0.9985
164
p-Xylene
C
ACN/30-60
0.9946
165
Phenanthrene
C
ACN/30-60
0.9867
166
Pyrene
C
ACN/30-60
0.9848
167
Toluene
C
ACN/30-60
0.9983
168
m-Diethylbenzene
C
ACN/30-60
0.9915
169
n-Butylbenzene
C
ACN/30-60
0.9920
170
n-Propylbenzene
C
ACN/30-60
0.9945
171
o-Xylene
C
ACN/30-60
0.9949
172
n-Hexylbenzene
C
ACN/40-60
0.9976
173
1 ,2,4-Trlmethylbenzene
D
ACN/30-80
0.9786
174
Benzene
D
ACN/30-80
0.9877
175
Biphenyl
D
ACN/30-80
0.9739
176
Bromobenzene
D
ACN/30-80
0.9818
177
Chlorobenzene
D
ACN/30-80
0.9813
178
Ethylbenzene
D
ACN/30-80
0.9833
179
Fluorobenzene
D
ACN/30-80
0.9841
180
lodobenzene
D
ACN/30-80
0.9825
181
Nitrobenzene
D
ACN/30-80
0.9843
182
n-Propylbenzene
D
ACN/30-80
0.9796
183
Toluene
D
ACN/30-80
0.9846
184
m-Diethylbenzene
0
ACN/30-80
0.9791
185
o-Xylene
D
ACN/30-80
0.9841
186
p-Xylene
D
ACN/30-80
0.9816
187
Anthracene
D
ACN/40-80
0.9807
188
Chrysene •
D
ACN/40-80
0.9758
189
Fluoranthene
D
ACN/40-80
0.9761
190
Napthalene
D
ACN/40-80
0.9792
191
Phenanthrene
0
ACN/40-80
0.9774
192
Pyrene
D
ACN/40-80
0.9750
193
n-Butylbenzene
D
ACN/40-80
0.9780
194
n-Hexylbenzene
D
ACN/40-80
0.9764
195
Bromobenzene
E
ACN/40-70
0.9976
196
Fluorobenzene
E
ACN/40-70
0.9981
197
lodobenzene
E
ACN/40-70
0.9968
198
Nitrobenzene
E
ACN/40-70
0.9984
199
1 ,2,4-Trimethylbenzene
E
ACN/50-70
0.9966
200
Anthracene
E
ACN/50-70
0.9957
201
Benzene
E
ACN/50-70
0.9995
R«f«ranc«
va, ET(30)
Slope(x102)
-(y-lnt)
a
0.9988
39.114.0
21 .712.3
0.0185
0.9952
27.115.7
15.213.2
0.0259
0.9983
37 .6i4 .6
20.812.6
0.0214
0.9993
50.214.1
27.8i2 .4
0.0180
0.9990
54 .0±5.3
29.813.1
0.0238
0.9955
32.016.4
17.713.7
0.0295
0.9998
47 .9i2.2
26.411.3
0.0090
0.9994
50.613.6
27.912.1
0.0169
0.9909
44 .0t4.5
24.212.6
0.0202
0.9984
36.914.6
20.4i2 .6
0.0204
0.9991
60.8123.2
33.3113.2
0.0199
0.9973
49.513.6
27.212.0
0.0371
0.9883
34.1*5.2
19.012.9
0.0535
0.9905
54.312.9
29.911.7
0.0302
0.9948
42.014.2
23.212.4
0.0439
0.9951
40.714.0
22.612.2
0.0413
0.9945
45.614.7
25.212.7
0.0492
0.9913
36.214.7
20.212.7
0.0491
0.9952
44.514.3
24 .612.4
0.0446
0.9915
35.114 .6
19.612.6
0 .0470
0.9966
51.9i4.2
28.512.4
0.0438
0.9914
39.715.1
22.012.9
0.0534
0.9976
56.013.9
30.712.2
0.0396
0.9947
44.614 .6
24.612.6
0.0471
0.9960
45.314.0
25.012.2
0.0415
0.9981
58.914 .8
32.412.7
0.0281
0.9995
67 .512.9
37.0H .6
0.0164
0.9989
62.1l3.6
34.U2.0
0.0220
0.9962
48.515.5
26.813.1
0.0324
0.9990
58.613.3
32.211.9
0.0199
0.9992
61.013.1
33.511 .7
0.0182
0.9985
59.814.3
32.812.4
0.0253
0.9988
70.514.6
38.512.6
0.0268
0.9969
45.917.7
25.014.3
0.0149
0.9963
40.717.5
22.514.2
0.0145
0.9977
47 .817.0
26.213.9
0.0134
0.9958
39.517.9
22.014.4
0.0149
0.9978
52.217.3
28.514.1
0.0143
0.9983
58.517.4
31 .914.1
0.0142
0.9931
38.219.7
21.1±5.5
0.0187
Wood bum (1985)
65 .7
00
(V>
n
4
4
4
4
4
4
4
4
4
4
3
6
6
6
6
6
6
6
6
6
6
6
6
6
6
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4

Table 3-1—continued
Data
Soluta
^Column
Solvent/% Range
r^ va. %
r2 va. EtC 30)
Slope(x102)
-(y-lnt)
B
n
ba%
Reíerence
202
Biphenyl
E
ACN/50-70
0.9963
0.9980
55.1*7.5
30.2*4.2
0.0146
4
Woodburn (1985)
203
Chrysene
E
ACN/50-70
0.9947
0.9908
65.916.8
35.7*3.8
0.0131
4
204
Ethylbenzene
E
ACN/50-70
0.9967
0.9976
48.917.2
26.0*4.1
0.0141
4
"
205
Napthalene
E
ACN/50-70
0.9968
0.9974
49.017.5
26.9*4.2
0.0146
4
"
206
Phenanthrene
E
ACN/50-70
0.9951
0.9989
57.616.2
31 .4*3.5
0.01 16
4
"
207
Pyrene
E
ACN/50-70
0.9953
0.9986
60.016.8
32.4*3.8
0.0129
4
"
208
Toluene
E
ACN/50-70
0.9967
0.9975
43.416.5
23.9*3.7
0.0127
4
"
209
m-Diethylbenzene
E
ACN/50-70
0.9967
0.9977
57.718.5
31.4*4.8
0.0161
4
"
210
n-Butylbenzene
E
ACN/50-70
0.9968
0.9975
59.018.8
32.1*5 .0
0.0172
4
"
211
n-Hexylbenzene
E
ACN/50-70
0.9961
0.9982
69.019.1
37.3*5.1
0.0171
4
212
n-Propylbenzene
E
ACN/50-70
0.9962
0.9980
54.217.4
29.6*4.1
0.0142
4
213
o-Xylene
E
ACN/50-70
0.9970
0.9976
47.817.2
26.2*4.0
0.0137
4
214
p-Xylene
E
ACN/50-70
0.9966
0.9979
48.516.8
26.6*3.8
0.0131
4
215
Acetophenone
F
ACN/50-80
0.9989
0.9960
33.716.5
19.3*3.6
0.0192
4
Jandera (1985)
216
Anisóle
F
ACN/50-80
0.9965
0.9801
40.6±13.6
23.0*7.6
0.0401
4
29.3
217
Benzaldehyde
F
ACN/50-80
0.9985
0.9947
38.618.6
22.0*4 .8
0.0252
4
..
218
Benzonltrile
F
ACN/50-80
.9983
0.9920
39.2*10.7
22.3*6.0
0.0317
4
..
219
Benzophenone
F
ACN/50-80
1.9997
0.9976
47.9*7.1
26.9*4 .0
0.0210
4
H
220
Benzotrichloride
F
ACN/50-80
0.9984
0.9989
52.4*5.4
29.2*3.0
0.0158
4
221
Bromobenzene
F
ACN/50-80
0.9993
0.9942
44.4*10.3
24.9*5.7
0.0303
4
222
Chlorobenzene
F
ACN/50-80
0.9998
0 .9969
44.6*7.6
25.1*4.3
0.0225
4
..
223
Chlorobromuron
F
ACN/50-80
0.9998
0.9966
46.6*8.3
26.2*4.6
0.0245
4
„
224
Dl-n-Butylether
F
ACN/50-80
0.9975
0.9947
46.6*10.3
25.9*5 .8
0.0304
4
..
225
Ethyl benzoate
F
ACN/50-80
0.9990
0.9934
45.4111 .3
25.5*6.3
0.0333
4
H
226
Linuron
F
ACN/50-80
0.9999
0.9970
46.6*7 .8
26.3*4.4
0.0231
4
.1
227
Methyl benzoate
F
ACN/50-80
0.9976
0.9926
39.0*10.3
22.1*5.7
0.0303
4
M
228
Nitrobenzene
F
ACN/50-80
0.9995
0.9948
40.0*8 .8
22.7*4.9
0.0261
4
..
229
Phenetole
F
ACN/50-80
0.9892
0.9765
41 .9*19 .8
23.6*11.0
0.0584
4
29.3
M
230
Phenol
F
ACN/50-80
0.9587
0.9691
43.4*2 .4
25.0*13.2
0.0697
4
54.0
231
Phenyl acetate
F
ACN/50-80
0.9969
0.9911
36.0*10.4
20.5*5.8
0.0306
4
232
Styrene
F
ACN/50-80
0.9988
0.9944
45.5*10.4
25.5*5.8
0.0307
4
M
233
o-Cresol
F
ACN/50-80
0.9937
0.9833
39.4*15.6
22.6*8.7
0.0462
4
29.3
••
234
n-Butylbromide
F
ACN/50-80
0.9990
0.9966
44.8*8.0
25.1*4.5
0.0235
4
»
235
n-Butylphenyl Carbamate
F
ACN/50-80;
0.9999
0.9981
48.0*6.3
27.0*3 .5
0.0186
4
••
236
n-Heptane
F
ACN/50-80
0.9990
0.9986
54.5*6.1
29.9*3.4
0.0181
4
••
237
n-Octane
F
ACN/50-801
0.9981
0.9976
59.0*8.8
32.3*4 .9
0.0260
4
«
238
n-Propylphenylether
F
ACN/50-80
0.9999
0.9960
46.1*8.9
25.9*5.0
0.0262
4
239
o-Cresol
F
ACN/50-80
0.9952
0.9959
39.0*7.7
22.4*4.3
0.0226
4
»
j>-Cresol
F
ACN/50-80
0.9984
0.9900
41.9*5 .6
23.9*3.2
0.0166
4
••
241
1 ,2,4-Trimethylbenzene
B
MeOH/35-60
0.9930
0.9852
53.3*19-9
30.5*"-7
0.0699
4
54.5
Woodburn (1985

Table 3-1—continued
aColumn
Solvent/* Harija
r2 vs. %
r2 vs. Eâ„¢.(30)
Slope(xI02 J
-(y-Int)
8
n
ba%
24 2
B
MeOH/35-60
0.9976
0.9923
7O.7±10.9
40.4*11.1
0.0665
4
83 .8
243
B
MeUll/35-60
0.9606
0.9535
33.1 122.2
19.3i13.0
0.0781
4
03.6
244
Biphenyl
B
MeOII/35-60
0.9959
0.9895
61 .6*19.3
35.2*11 .3
0 .0600
4
80.3
245
Broroobenzene
B
MeOII/35-60
0.9043
0.9066
45.1±22.7
26.0*13.3
0.0799
4
83.7
246
Chlorobenzene
B
MeOII/35-60
0.9037
0.9723
42.2*21 .6
24.2*12.7
0.0762
4
76.5
247
Chrysene
B
MeOII/35-60
0.9994
0.9966
92.6*69.1
52.0*40.5
0.0507
3
248
Ethylbenzene
B
MeOII/35-60
0.9867
0.9763
46.1*21 .8
26.5*12.8
0.0767
4
61 .0
249
Fluorobenzene
B
MeOH/35-60
0.9766
0.9633
36.1*21.4
21.0*12.6
0.0753
4
03.2
250
lodobenzene
B
MeOII/35-60
0.9095
0 .9002
48.3*20.9
27.0*12.3
0 .0734
4
02.3
251
Naptha lene
B
MeOH/35-60
0.9910
0.9823
51 .9*21 .2
29.8*12.4
0.0745
4
79.5
252
Nitrobenzene
B
MeOH/35-60
0.9598
0.9629
36.2*21 .6
21 .2*12.7
0 .0760
4
04.7
253
Phenanthrene
B
MeOH/35-60
0.9977
0.9926
69.2*18.2
39.6*10.7
0.0640
4
254
Pyrene
B
MeOH/35-60
0.9987
0.9945
77.8*17.7
44.4*10.4
0.0619
4
255
Toluene
B
MeOH/35-60
0.9797
0.9672
39.2*21.9
22.7*12.9
0.0772
4
64.3
256
m-Die thylbenzene
B
MeOH/35-60
0.9961
0.9899
60.7*18.6
34.5*10.9
0.0654
5
54.
257
n-Butylbenzene
B
MeOH/35-60
0.9959
0.9895
65.1*20.5
37.0*12.0
0.0710
4
63.6
250
n-Propylbenzene
B
MeOH/35-60
0.9920
0.9037
54.6*21.4
31.2*12.6
0.0753
4
61 .8
259
o-Xylene
B
MeOH/35-60
0.9868
0.9765
45.4*21.4
26.1*12.6
0.0754
4
57.1
260
p-Xylene
B
MeOH/35-60
0.9863
0.9756
47 .0*22.6
27.0*13.3
0.0795
4
88.4
261
1,2,4-Trlmethylbenzene
C
MeOH/40-75
0.9999
0.9950
60.6*7.2
34.3*4.2
0.0457
5
262
Benzene
C
MeOH/40-75
0.9960
0.9853
39.5*8.9
22.6*5.1
0.0557
5
67.4
263
Bromobenzene
C
MeOH/40-75
0.9986
0.9905
51.0*9.2
29.1*5.3
0.0570
5
264
Chlorobenzene
C
MeOH/40-75
0.9988
0.9913
48 .9*8.4
27.9*4.9
0.0529
5
265
Ethylbenzene
C
MeOH/40-75
0.9997
0.9924
54.0*7.7
31 .1*4.5
0 .0438
5
266
Fluorobenzene
C
MeOH/40-75
0.9973
0.9872
43.0*9.0
24 .6*5.2
0.0564
5
00.9
267
lodobenzene
C
MeOH/40-75
0.9998
0.9950
55.0*7.2
31 .3*4.2
0.0451
5
268
Napthalene
C
MeOH/40-75
0.9999
0.9097
54.7*10.3
31 .0*5.9
0.0644
4
66.6
269
N1trobenzehe
C
MeOH/40-75
0.9983
0.9903
41 .8*7.6
24.0*4.4
0.0477
5
270
Toluene
C
MeOII/40-75
0.9986
0.9910
46.7*8.2
26.6*4.7
0.0514
5
271
p-Xylene
C
MeOH/40-75
0.9994
0.9933
54.2*0.2
30.8*4.7
0.0514
5
272
Anthracene
C
MeOH/50-75
0.9999
0.9098
75.3*23.3
42.5*13.4
0.0681
4
56.1
273
Biphenyl
C
MeOII/50-75
0.9999.
0.9807
68.7*22.4
38.9*12.9
0.0655
4
53.7
274
Chrysene
C
MeOH/50-75
0.9993
0.9913
89.8*25.7
50.6*14.8
0.0751
4
275
Phenanthrene
c
MeOH/50-75
0.9996
0.9897
73 .9*23.0
41 .8*13.2
0.0671
4
53.4
276
Pyrene
c
MeOH/50-75
0.9883
0.9906
80.3*23 .7
45.3*13.6
0.0696
4
277
m-Dlethylbenzene
c
MeOH/50-75
0.9998
0.9976
74.0*11.3
42.2*6.5
0.0329
4
270
n-Butylbenzene
c
MeOH/50-75
0.9999
0.9990
77 .8*7.5
43 .9*4.3
0.0220
4
279
n-Propylbenzene
c
MeOH/50-75
0.9999
0.9983
68.4*8.5
30.7*4.9
0.0248
4
280
p-Xylene
c
MeOH/50-75
0.9999
0.9980
56.6*7 .8
32.1*4.5
0.0228
4
201
o-Xylene
c
MeOtl/50-80
0.9999
0.9976
61.2*9.2
34.5t5- 3
0.0303
4
Reference
(1985)
oo
-F^

Table 3-1—continued
Solute
flColumn
Solvent/% Range
T1, V 3 .
202
Toluene
C
McOII/50-75
0.9986
283
n-Hexylbenzene
c
M. -11/60-75
0.9990
284
1 ,2,4-Trimethylbenzene
D
MeOH/50-80
0.9997
205
Anthracene
D
MeOII/50-80
0.9984
286
Benzene
D
MeOH/50-80
0.9999
287
Biphenyl
D
MeOH/50-80
0.9907
288
Bromobenzene
D
MeOll/50-60
0.9990
209
Chlorobenzene
D
MeOII/50-80
0.9999
290
Ethylbenzene
D
MeOII/50-80
0.9999
291
Fluorobenzene
D
MeOH/50-80
0.9999
292
Iodobenzene
D
MeOII/50-80
0.9998
293
Napthalene
D
MeOH/50-80
0.9994
294
Nitrobenzene
D
MeOII/50-80
0.9999
295
Phenanthrene
D
MeOII/50-80
0.9983
296
Pyrene
D
MeOII/50-80
0.9973
297
m-Dlethylbenzene
D
MeOII/50-80
0.9995
290
n-Butylbenzene
D
Me0ll/50-80
0.9990
299
n-Propy1benzene
D
MeOII/50-80
0.9996
300
p-Xylene
D
MeOII/50-80
0.9999
301
Chrysene
D
McOH/60-80
0.9992
302
n-Hexylbenzene
D
MeOII/60-80
0.9997
303
Ace tophenone
F
Me0ll/60-90
0.9990
304
Anisóle
F
MeOH/60-90
0.9979
305
Benzaldehyde
F
MeOII/60-90
0.991 1
306
Benzonitrile
F
MeOII/60-90
0.9992
307
Benzophenone
F
He0ll/60-90
0.9996
300
Benzotrichloride
F
MeOII/60-90
0.9988
309
Bromobenzene
F
MeOII/60-90
0.9999
310
Chlorobenzene
F
MeOH/60-90
0.9998
311
Chlorobromuron
F
Me0ll/60-90
0.9978
312
Di-n-Butylether
F
MeOII/60-90
0.9988
313
Ethyl benzoate
F
MeOH/60-90
0.9996
314
Llnuron
F
MeOH/60-90
0.9993
315
m-Cresol
F
MeOH/60-90
0.9937
316
Methyl Benzoate
F
MeOH/60-90
0.9996
317
n-Butyl Bromide
F
MeOH/60-90
0.9990
318
n-Heptane
F
MeOH/60-90
0.9999
319
Nitrobenzene
F
MeOH/60-90
0.9944
320
o-Creaol
F
MeOH/60-90
0.9896
321
p-Creeol
F
MeOH/60-90
0.9984
VB â– 
vs. E-no)
Slope(x102)
-(y-int)
B
n
ba.
Hefeience
0.9966
55.419.0
31 .415.6
0.0325
4
Woodburn (1985
1 .000
1 11 .015.6
57.216.4
0.005
3
••
0.9901
69.019.1
30 .015.2
0.0301
4
0.9996
82.415.1
46.312.9
0.0163
4
0.9955
47.219.5
26.915.5
0.0317
4
0.9993
76.516.0
43.1±3.5
0.0207
4
"
0.9979
59.110.4
33.514 .0
0.0274
4
0.9960
57. U9.8
32.415.6
0.0327
4
0.9971
64.0i1 .1
36.216.1
0.0346
4
0.9955
50.8110.5
29.016.0
0.0342
4
"
0.9978
62.519.1
35.315.2
0.0294
4
0.9907
64.416.8
36.413.9
0.0230
4
••
0.9963
47.218.7
27.015.0
0.0207
4
»
0.9996
00.714.7
45.412.7
0.0161
4
"
0.9999
07.312.6
48.911.5
0.008
4
"
0.9906
79.519.1
44.615.2
0.0297
4
0.9992
82.617.4
46.314.2
0.0235
4
0.9903
73.319.2
41.2l5.3
0.0300
4
0.9972
62.0110.2
35.415.9
0.0334
4
0.9999
90.5113.5
55.U7 .6
0 .007
3
0.9996
28.5114.1
50.9H6.2
0.0100
3
"
0.9989
50.515.0
29.212.8
0.0136
4
Jandera (1985)
0.9989
57.0117.5
32.019.9
0.0473
4
„
0.9777
55.U25.3
31 .9114.4
0.0685
4
60.9
„
0.9952
53.6H 1 .3
31 .016.4
0.0305
4
0.9980
69.419.5
39.615 .4
0.0257
4
„
0.9980
79.810.3
45.214.7
0.0225
4
„
0.9951
'67.U14 .3
38.210.1
0.0387
4
„
0.9944
64.7H4 .7
36.910.3
0.0397
4
H
0.9922
73.9H9.9
42.2H1.3
0.0538
4
N
0.9990
74.517.3
42.314.1
0.0195
4
„
0.9970
68.219.7
30.915.5
0.0263
4
„
0.9905
70.118 .4
40.014.7
0.0227
4
„
0.9772
62.6129.1
36.2H6.5
0 .0706
4
50.5
„
0.9901
59.417.9
34.114 .5
0.0213
4
„
0.9927
66.9H7 .5
38.119.9
0.0472
4
„
0.9962
95.1±17.0
53.5110.1
0.0478
4
„
0.9041
50.2122.5
33.5112.7
0.0608
4
61 .1
H
0.9792
61 .0127.0
35.3115.3
0.0730
4
67.9
„
0.9040
50.0122.2
34.0i12.6
0.0600
4
81 .1
-

Pat
322
323
324
325
326
327
328
329
330
331
332
3-1 —continued
Solute
“Column
Solvent/% Range
r2 vs. %
rJ vo. et(30)
Slope(x102
-(y-lnt)
8
n ba*
Phenetole
F
Me0ll/60-90
0.9992
0.9971
61 .3110.1
35.115.7
0.0274
4
phenol
F
MeOII/60-90
0.9460
0.9198
61 .4165.1
35.7128.6
0.1489
Phenyl acetate
F
MeOll/60-90
0.9994
0.9985
50.116.0
29.013.4
Styrene
F
MeOII/60-90
0.9999
0.9961
65.7H2.6
37.517.1
n-Butylphenylcarbamate
F
MeOH/60-90
0.9995
0.9926
75.3H9.8
43.0HI .2
n-Propyl phenyl ether
F
MeOH/60-90
0.9999
0.9957
68.0H3.6
4.017.7
0.0369
Benzene
A
MeOH/48.9-70.7
0.9953
0.9948
38.218.3
21.414.7
Butylbenzene
A
MeOH/48.9-70.7
0.9980
0.9900
73.7122.5
40.8112.8
This Work
Isopropylbenzene
A
MeOH/48.9-70.7
0.9981
0.9904
63 .0118.8
35.OHO.7
Toluene
A
MeOH/48.9-70.7
0.9972
0.9922
47.4112.8
26.517.3
Ethylbenzene
A
MeOH/48.9-70.7
0.9981
0.9911
55.8H6.1
31 .0i9.2
0.0584
4
This Work
A. IS cm X 4.6 mn, 5 pm Ultrasphere 00S (Altex)
B. 5 can X 4.6 mm, 10 pm Sepralyte C2 (Analytlchem)
C. 5 cm X 4.6 mm, 10 pm Sepralyte C4 (Analytlchem)
D. S cm X 4.6 mm, 10 pm Sepralyte C8 (Analytlchem)
C. 5 cm X 4.6 am, 10 pm Sepralyte C18 (Analytlchem)
F. 30 cm X 3.8 mm, 7.5 pm Sllasorb C8 (Lachema)
G. 15 cm X 4.1 mm, 5 pm Unlsll Q C18 (Gasukuro Kogyo)
H. 15 cm X 4.1 mm, 5 pm Hypersll ODS (Shandon Southern)
^<3% la the significance level for the F ratio (n-2, n-3 degrees of freedom)
for fitting the the data to either a linear or quadratic model.
oo
(Ts

37
lattar comparison. Tha type of column is denoted by a
single letter (A-G); a key appears at the end of the
table. Confidence intervals reported for the log k' versus
3p(30) comparisons are for the 95% level of confidence (t
statistic, n-2 degrees of freedom). The column in Table
3-1 labeled is the significance level of the F-ratio
for fitting the data to either a linear or quadratic model
(discussed below). The last column in Table 3-1 denotes
the source of the retention data.
Weighted least squares regression calculations were
not used in these correlations for two primary reasons.
First, it is difficult to estimate the relative uncertainty
in each individual log k* value. There are two main
sources of error in log k’ ; one of these is systematic and
the other is random. The systematic error may be caused by
the method used to evaluate the void volume of the
column. There are many ways to estimate this, and two
recent papers have dealt with the problems inherent in this
type of measurement (Knox and Kaliszan, 1985; Zhu, 1985).
Any systematic error in tQ will lead to an error in the
calculated log k’ value. This is especially the case where
retention times are small, and thus k' approaches zero and
log k' becomes very large and negative.
Moreover, in addition to systematic errors in the
measurement of tQ and tr, there will always be a certain
amount of random variability in the measured t0, and hence

88
an extra source of error is introduced. This is especially
a problem for polar solutes which are poorly retained
and/or at high concentrations of organic modifier. For
example, when tQ is 1.2 minutes with an uncertainty of
+0.05 minutes, a peak with tr = 3.0 minutes will have a k'
of 1.5 and log k of 0.17o±0.04, which is 24% on a relative
basis. This error is in addition to any that may be caused
by systematic tQ measurement errors. While there is
uncertainty in the calculated log k' values, these errors
are also present in all chromatographic retention data and
will thus affect both types of comparisons presented here.
Secondly, in many cases, k' values reported in the
literature have been calculated using void volume
measurement techniques that are not specified. Thus, it is
simply not possible to estimate the relative variance of
log k' values for these cases. Even if the variance were
determined by multiple injections at each concentration,
the effect of systematic errors in the evaluation of void
volume is still not represented, and there is at present no
absolutely infallible way of measuring the true void volume
seen by the solute. It is probable that each log k' value
will have an uncertainty of at least ±0.1 log units, though
the variation in uncertainty as a function of organic
modifier concentration cannot be estimated accurately.
Overall, the average r2 value for plotting the data
versus percent organic modifier is 0.9783 and versus Erp(30)

89
polarity is 0.9910. However, these averages fail to convey
a sense of how the values are distributed among the 332
data sets. In Figures 3-7 and 3-8, histograms are shown
for each of the two methods of plotting the retention
O
data. It can be seen that a much wider range in r values
is encompassed when the data are plotted with respect to
percent organic modifier. However, the x-axis of the two
histograms is scaled differently in each case. So in
Figures 3-9 and 3-10, histograms have been constructed for
a standardized range (0.95 to 1.00), and thus the
distribution is more clearly presented. By confining the
histogram to those r^ values greater than 0.95, 89.2 and
98.2% of the sets of "versus percent organic" and "versus
E'j(30)," respectively, are represented. Figures 3-9 and
3-10 clearly demonstrate that the distribution is far less
skewed among the "log k' versus ET(30)" sets, and a much
p
higher number of sets have r values of greater than
0.9950. Squared correlation coefficients (r¿) are reported
for two reasons. First, it is a more conservative measure
of correlation, and secondly, r^ represents the fraction of
the variance in log k* values that is accounted for by a
linear statistical model (Edwards, 1984).
p
A poor r value (defined here as one less than 0.9900)
may be due to either a large amount of symmetrical scatter
around the line and/or systematic deviation (curvature).

90
200
Count
100-
i—i—r
i—i—r
0.748 0.784 0.820 0.856 0.892 0.928 0.964 1.000
r2(versus % organic)
Figure 3-7. Histogram of r^ values for the 332 retention
data sets plotted with respect to percent
organic modifier.

91
Count
r2 (versus ET(30) )
3-8. Histogram of r^ values for the 332 retention
data sets plotted with respect to ET(30)
polarity.
Figure

92
100
80
Count60
40
20
O
0.950 0.960 0.970 0.980 0.990 1 .000
r2(versus % organic)
Figure 3-9. Modified histogram of r^ values for the 332
retention data sets plotted with respect to
percent organic modifier. Range of values
limited to 0.95 to 1.00.

93
Count
Figure 3-10.
r2(versus ET(30) )
Modified histogram of r2 values for the 332
retention data sets plotted with respect to
Erp(30) polarity. Range of r2 values limited
to 0.95 to 1.00.

94
When comparing the relative fit of a linear or quadratic
model, the ratio of the variance (s^1) for the two models is
known as an F-value and can be used to assess whether the
"fit" is significantly better with a particular model. For
each case in which the r2 value for the log k' versus
E^(30) polarity linear regression fell below 0.9900, an F
value was calculated and the significance level (a%) was
determined for fitting the data to a quadratic model (2nd-
degree polynomial). The quadratic model did not fit the
data significantly better (at the 90% confidence level)
except in 16 out of the 332 sets; these were primarily the
tri- and tetrachlorophenols found in the data of Hanai and
Hubert (1933).
In Table 3-2, the average squared correlation
coefficients for the various columns and mobile phases are
summarized. Since the distribution of the r2 values is
highly skewed, both median and mean values are reported in
order to present a more accurate "picture" of the data.
p
Also, a Ar1^ value is reported for each LC column and
O
represents the difference between the mean r values for
the two types of correlations discussed herein. Thus, a
positive value denotes a better correlation versus E-p(30)
polarity values. The largest difference between the two
methods of treatment is for Column G (Hypersil ODS; from
Hanai and Hubert, 1983) in acetonitrile/water mixtures, in

Table 3-2.
Mean and median values for correlations shown in Table 3-1.
Column/Mobi
A/ACM (C
G/ACN (C
H/ACN (C
6/ACN (C
C/ACN (C
D/ACN (C
E/ACN (C
F/ACN (C
B/MeOH (
C/MeOH (
D/MeOH (
F/MeOH (
A/MeOH (
OVERALL
O
r values
(MEAN/MEDIAN/STD. DEV.)
le Phase
n
VS. % OM
VS. Et(30) POLARITY
Ar^
-18)
14
0.9890/0.9879/0.0048
0.9945/0.9947/0.0038
0.0055
-18)
117
0.9531/0.9646/0.0433
0.9397/0.9933/0.0137
0.0366
-18)
8
0.9539/0.9619/0.0219
0.9790/0.9862/0.0163
0.0251
-2)
21
0.9948/0.9977/0.0063
0.9828/0.9865/0.0128
-0.0120
-4)
22
0.9921/0.9946/0.0070
0.9980/0.9987/0.0017
0.0059
-3)
22
0.9802/0.9301/0.0036
0.9960/0.9964/0.0031
0.0158
-18)
20
0.9967/0.9967/0.0011
0.9975/0.9977/0.0013
0.0008
-8)
26
0.9965/0.9987/0.0081
0.9932/0.9954/0.0070
-0.0033
C-2)
20
0.9880/0.9903/0.0105
0.9805/0.9830/0.0119
-0.0075
C-4)
21
0.9987/0.9997/0.0025
0.9930/0.9913/0.0041
-0.0057
C-8)
21
0.9989/0.9997/0.0024
0.9982/0.9983/0.0014
-0.0007
C-8)
25
0.9960/0.9992/0.0108
0.9903/0.9957/0.0162
-0.0057
C-1 8)
5
0.9973/0.9980/0.0012
0.9917/0.9911/0.0019
-0.0056
332
0.9783/0.9890/0.0334
0.9910/0.9947/0.0119
0.0127

96
which the averages of r~ values differed by 0.0366. While
p
in some cases the Ar~ values are negative, it should be
noted that the magnitude of these differences is generally
much smaller than that where positive values have been
found.
Furthermore, it should also be noted that correlation
coefficients found for log k* versus E^(30) regressions are
likely to be reduced in magnitude because of the nature of
the data being compared. Specifically, in the correlations
of log k' versus Eij(30) polarity, a certain amount of extra
variance, not present when correlating with percent organic
modifier, is introduced into the independent variable.
This is due to the "external" set of data, namely the
Erjn(30) polarity values for the solvent mixtures. Any extra
variance in the x values, e.g., E^(30) polarity, will lead
to a decrease in the r^ value, even though the overall
linearity of the correlation may not be different between
the two methods of treatment. It is possible to estimate
the relative uncertainty and hence the extra variance being
introduced, by examining the standard deviations for *max
determination with the diode array instrument. In separate
experiments, the E MeOH/ACN/f^O were determined and thus provide an excellent
set of data from which to estimate the standard deviation
of Xmax measurements. For each mixture, a total of ten
spectra were acquired, so a standard deviation can be

97
calculated for each set of ten. The pooled standard
deviation for the entire set of 620 measurements is then
given by
Spooled * - 1] (3-3)
where s^ is the standard deviation of set i, and n^ is the
number of *max determinations for each solvent mixture (n =
10 for all 62 sets). Using this equation the pooled
standard deviation was found to be 1.16 nra. Assuming that
Spooled representative of the uncertainty in Amax, the
uncertainty in ET(30) polarity will be given by
d(ET(30)) = (-28591/X )2(1.16 nra) (3-4)
X IU«d A
Thus, the total extra variance added by this uncertainty in
Xmax win be
sextra = (n (dET(30)-m)2)/(n-2) (3-5)
where m is the slope of log k' versus ET(30), n is the
number of log k’ values in the data set, and d(E^(30)) is
the uncertainty in the E.j(30) values. For example, where
the slope was found to be 0.400 and where *max had an
average value of 500 nm in six mobile phase mixtures, the
maximum contribution to the total variance (s2 of

98
regression) would be approximated by
s* . = (6)(0.133) (0.400)2 = 4.25 X 10"03 (3-6)
extra
In such a case, sox^ra would then be 0.0652. From
Table 3-1, typical s values for regression of log k' versus
S

previously calculated estimate of the extra variance
introduced by the ET(30) is likely to overestimate the true
value, it does show the extent to which the standard error
of estimate may be affected. Given this extra source of
error, it is impressive that the overall median r values
(as shown in the bottom line of Table 3-2), which are a
better way to compare two populations in which the
distributions are skewed, are so close (0.9945 and
0.9946). If this extra source of error were not present,
p
the median r^ value for log k' versus E^,(30) polarity plots
would be significantly increased.
Taken by itself, this high correlation between the
observed chromatographic retention and the Erp(30) polarity
values has little practical value. However, a wealth of
information about the effect of mobile phase polarity on
chromatographic retention is contained in the regression
coefficients that are tabulated in Table 3-1, as well as
information about the solvation of the stationary phase
alkyl chains. When properly interpreted, the data

99
contained in Table 3-1 are of great practical value. The
interpretation of these results is found in Chapter V.
Comparison with the "Carr Approach11
Sadek et al. (1985b) have recently reported
correlations between retention and solvatochromic
measurements of individual solutes. In terms of solute
properties, molecular volume, 8 hydrogen bond acceptor
ability, and tt* dipolarity-polarizability were found to be
the best predictors of chromatographic retention, as shown
below:
log k* = a + b*(V/100) + c*tt* + d*8 (3-7)
The constants a, b, c, and d are affected by the
particular column, mobile phase, and temperature. It
should also be pointed out that the w* and 8 parameters in
equation 3-7 were adjusted with what is termed the
"polarizability correction factor."
This equation is of the same form that Kamlet and
coworkers have used to correlate a variety of
solute/solvent properties, such as gas/liquid or
octanol/water partition cofficients (Kamlet et al., 1982,
1984). However, in this particular application (Sadek et
al., 1985b), solutes which might interact strongly with
residual silanols present on the stationary phase (such as

100
amines, phenols, or anilines) were deliberately excluded
from consideration. It is likely that if these solutes
were included in the correlation equation, a dependence on
solute a hydrogen bond donor ability would also be found
(see "Suggestions for Future Research," Chapter V).
In
theory,
equation
3-7
could be used
to predict
solute
retention
on the
basis
of it* polarity,
molecular
volume,
and 8
hydrogen
bond
basicity. In
practice,
however, this is rather difficult for many compounds.
Liquid chromatography is often the analytical technique of
choice for compounds which are thermally labile and/or are
of low volatility, rendering them unsuitable for gas
chromatographic analysis. These compounds are often solids
at room temperature. Thus, it is not possible to measure
their dipolarity/polarizability, since this is based on
a solvatochromic measurement in solution. This also means
that it is impossible to determine ct or 8 values, since
these are also based on solvatochromic measurements.
Therefore, this approach is severely limited by the
lack of available data based on the solvatochromism of test
solutes. Of course, one could evaluate ** and 8 values by
"back-calculating" from their retention, once the constants
in equation 3-7 have been determined for solutes with known
tt* and 8 parameters (for liquids; a comprehensive list is
found in Kamlet et al., 1933).

101
The approach of Sadek et al. (1985b) is distinctly
different from that discussed here, in that solvato-
chromically measured solute properties are being compared
with retention rather than solvent mixture properties. In
a sense these two approaches are complementary in nature,
since retention is a function of both solvent and solute
properties. While not the main purpose of this research,
it is worthwhile to briefly examine an alternative, multi-
parameter approach to solute retention, based on the
measured solvent properties (ct, g, and it* values; tabulated
in Appendix D). In a sense, this approach would be the
"mirror image" of that used by Sadek et al. (1985b), with
the addition of the a hydrogen bond donor parameter.
To investigate the utility of this approach, a set of
five retention data sets (of log k' versus percent organic
modifier) were used to carry out a multiple linear
regression, with log k' (at a given composition) as the
dependent variable and solvent mixture a, g, and it* values
(for the same composition) as the independent variables.
Since acetonitrile/water systems offer the most unusual
variation in solvent properties, this system offers the
best test of such an approach. The five sets were picked
such that a variety of solute properties were included
(protic, aprotic, nonpolar, polar). Retention data for
benzene, toluene, and chlorobenzene are for a C-3 Sepralyte
LC column, with acetonitrile as the mobile phase (Woodburn,

102
1985; also found in Appendix A), while the data for 4-
nitrophenol and phenol are for a C-18 Unisil Q LC column
(Hanai and Hubert, 1983; also found in Appendix A). The
regression results are shown in Table 3-3, where the
multiple correlation coefficients and regression
coefficients are shown.
In view of the results in Table 3-3, this approach may
be potentially useful. It should be noted, however, that
the data sets for benzene, toluene, and chlorobenzene
contained only 5 points; this is probably an insufficient
quantity to make definite conclusions. The sets for 4-
nitrophenol and phenol contained 7 points. It is apparent
that all three coefficients vary widely with the different
solutes. This is especially so for the coefficient, where
phenol and nitrophenol are seen to be less retained in
highly basic solvents. That is, as the basicity of the
mixture increases, these solutes (which are strong hydrogen
bond donors) will be more strongly solvated by the mobile
phase, leading to a decrease in log k' values. With the
exception of these two negative 8 coefficients, all other
solutes are more highly retained by an increase in either
the it*, a, or 8 value of the mobile phase.

Table 3-3.
Multiple linear
regression between
log k' values
and a,
B, and it*.
Compound
Multiple
Correlation
Coefficient
a
e
TT*
Constant
Benzene
0.9983
1.317
7.44
6.26
-1 .08
Toluene
0.9993
0.756
8.27
7.76
-1.16
Phenol
0.9993
3.02
-1.35
1.68
-3.02
4-Nitrophenol
0.9997
4.07
CO
o
•
CM
1
2.00
-3.73
Chlorobenzene
0.9996
2.27
6.84
7.26
-1.17
103

CHAPTER IV
CORRELATIONS BETWEEN CHROMATOGRAPHIC SELECTIVITY
AND MOBILE PHASE POLARITY
Experimental
For retention data other than that reported in the
literature, the apparatus used is described in the
experimental section of Chapter III. Methylene selectivity
(log aQj^) is defined as the change in the logarithm of the
capacity factor for a given solute caused by the addition
or subtraction of one methylene group (CH2). The usual way
to evaluate this is to measure the capacity factors for a
homologous series (for example, alkylbenzenes, n-alcohols,
or 1-nitroalkanes). One then plots the logarithm of these
capacity factors with respect to carbon number of the alkyl
chain, and the slope corresponds to log <*CH2* In the
literature, log «CH2 values have either already been
calculated and reported or can be calculated based on the
published capacity factors for homologous series. In cases
where the log values were calculated from retention
data, the program "Curve Fitter" was used, as is described
in the experimental section of Chapter III.
In sharp contrast to log k' values, the variance of
log “ch2 values does not change significantly as a function
of the organic modifier concentration.
104

105
Introduction
The description of methylene selectivity in RPLC has
traditionally been more difficult than that of retention.
In a sense, the methylene selectivity is quite similar to
the retention of normal alkanes, since it is based on the
measurement of the capacity factors for a homologous
series. It has also been referred to as the "hydrophobic
selectivity," or "nonspecific selectivity," owing to the
large hydrophobicity of the methylene group. Methylene
selectivity serves as a convenient measure of elution
strength. Thus, knowledge of this for a given system is
quite useful, since the mobile phase strength can be held
constant for different organic modifiers, while the
selectivity of other interactions is exploited to maximize
the separation between two or more solutes.
From an energetic standpoint, the methylene
selectivity (log directly related to the change in
the free energy of transfer caused by adding a methylene
group to a molecule by the following equation:
log aCH2 = " aag/2-303RT
(4-1)
Of course, equation 4-1 applies to any form of
selectivity; any two solutes that possess different free
energies of transfer will be differentially retained.
Methylene selectivity is thus only one aspect of

106
chromatographic separations. In terms of research on
retention mechanisms, there are at least two distinct
advantages to the study of chromatographic selectivity.
First, it can be seen that log a values are not
affected by the phase ratio of the column. Different phase
ratios lead to changes in capacity factors (as shown by
equation 3-2). These phase ratios are a function of the
bonded group chain length, the degree of surface coverage,
the pore structure of the original silica, as well as the
manner in which the column bed was packed. Thus, drawing
conclusions about the variation in capacity factors for
different columns is hindered by the number of variables to
be considered. Since the methylene selectivity (or any
selectivity, for that matter) is not affected by the phase
ratio, any differences seen between columns are due to
actual differences in the nature of the bonded phase
structure.
A second advantage, obtained only in the study of
methylene selectivity, is that of lack of sensitivity to
the presence of residual silanols on the bonded phase
surface. Residual silanols lead to anomalous retention
behavior of many solutes which possess highly polar and/or
hydrogen bond donor/acceptor groups. While the individual
solutes that comprise the homologous series may be
susceptible to these effects, the change in the capacity
factor caused by additional methylene groups will still be

107
measurable and largely unaffected by specific interactions
that each member may undergo with residual silanols.
Moreover, log acn2 values ar9 generally independent of
the specific column used, such that all C-18 type bonded
phases will exhibit similar behavior, implying that only
the most fundamental aspects of the retention process are
being probed.
Though there have been many papers published with
regard to methylene selectivity, two of these are key
papers and are summarized briefly in the following
paragraphs. The first was published by Karger and
coworkers (1976) in which the variation in log k' values
for solutes such as n-alcohols were correlated with a
measure of solute surface area known as the "molecular
connectivity." Methylene selectivity was also discussed; a
linear relationship between log <*0^2 anc* percent methanol
was noted, while the behavior of acetonitrile/water
mixtures was found to be more complex. This behavior was
ascribed to the differing natures of the two modifiers, in
that methanol is a proton acceptor/donor, which leads to
less disruption in the overall solvent mixture structure as
the concentration is varied. The structure of
acetonitrile/water mixtures is of much greater complexity,
since acetonitrile does not associate with water to any
extent in comparison with methanol (see Chapter II for a

108
discussion of this effect with the E in acetonitrile/water mixtures).
Colin et al. (1933) carried out an extensive
investigation of methylene selectivity, in which a total of
seven binary systems and one ternary system were
explored. These measurements were then used to derive an
elutropic scale of solvent strength. These new values were
found to correlate quite well with Snyder's elutropic
values for RPLC solvents (Snyder et al., 1979).
It is also worth noting here that homologous series
have also been used in the determination of t0 (Berendsen
et al., 1930). In essence, this method involves the
adjustment of the tQ used to calculate the capacity
factors, such that the highest correlation is obtained in a
plot of log k' versus carbon number for the homologous
series when the "true" tQ is reached. However, this method
is subject to errors, in that the calculated tQ is in fact
quite dependent upon which members of the homologous series
are used to calculate tQ.
Results
In the experiments described herein, the methylene
selectivity was evaluated for a C-18 bonded phase column
(Ultrasphere ODS) and a styrene-divinylbenzene (polymeric;
Hamilton PRP-1) reversed phase column, with methanol and
acetonitrile as the organic modifiers. Also, a large body

109
of methylene selectivity data have been extracted from the
literature, either directly from tabulated log values,
or calculated from the slope of log k' versus carbon
number. The entire body of methylene selectivity discussed
here appears in Appendix A. Initially, the results for the
bonded phase data will be discussed; the methylene
selectivity was measured by using the homologous series of
benzene, toluene, ethylbenzene, and n-butylbenzene.
Ultrasphere OPS Column
In Figures 4-1 through 4-6, the results of experiments
with the Ultrasphere ODS column are shown for the two
organic modifiers. For methanol as an organic modifier,
methylene selectivity decreases in a linear manner as the
percentage or organic modifier is increased (r2 = 0.9972
for a straight line fit of the data in Figure 4-1), while
O
definite curvature is evident in Figure 4-2 (r_ = 0.9897
for a linear fit). The squared correlation coefficient
does decrease to 0.9884 in Figure 4-3 (versus E^(30)
polarity), though this may be due in part to an increase in
scatter; it is likely that the E.j(30) values have contri¬
buted some extra variance (as discussed in Chapter III).
The regression line drawn through the data in Figure 4-3 is
given by
log ctCH2 = -4.82+0.37 + 0.08817±0.0065 X ET(30) (4-2)
(n = 5, s = 0.0107)

110
% Methanol
Figure 4-1. Chromatographic selectivity measurements as a
function of percent methanol. Ultrasphere ODS
column; flow rate 1.0 mL/min. Alkylbenzenes
were used as the homologous series.

111
logo<
Figure 4-2. Chromatographic selectivity measurements as a
function of mole fraction of methanol.
Ultrasphere ODS column; flow rate 1.0
raL/min. Alkylbenzenes were used as the
homologous series.

112
logcx
Figure 4-3.
Et(30)
Chromatographic selectivity measurements as a
function of Em(30) polarity of methanol/ water
mixtures. Ultrasphere ODS column; flow rate
1.0 mL/rain. Alky lbenzenes were used as the
homologous series.

113
logoc
Figure 4-4
% Acetonitrile
Chromatographic selectivity measurements as a
function of percent acetonitrile. Ultrasphere
ODS column; flow rate 1.0 mL/rain.
Alkylbenzenes were used as the homologous
series.

114
l og <=<
Figure 4-5.
Chromatographic selectivity measurements as a
function of mole fraction of acetonitrile.
Ultrasphere ODS column; flow rate 1.0
mL/min. Alky lbenzenes were used as the
homologous series.

115
log<=<
Figure 4-6.
Et(30)
Chromatographic selectivity measurements as a
function of E.j(30) polarity of acetonitrile/
water mixtures. Ultrasphere ODS column; flow
rate 1.0 mL/min. Alkylbenzenes were used as
the homologous series.

116
In Figuras 4-4 through 4-6, the methylene selectivity
results for acetonitrile/water mixtures are plotted with
respect to percent acetonitrile, mole fraction, and E-j.(30)
polarity. As shown in Figure 4-4, the methylene
p
selectivity varies in a nonlinear manner; r- for a straight
line regression is 0.9655. Plotting the data with respect
to mole fraction (Figure 4-5) only serves to accentuate the
curvature (r- = 0.9173), while plotting with respect to the
Et(30) polarity yields the best linear correlation (r2 =
0.9919). The regression equation for the line in Figure
4-6 is given by
iog ctCH2 = -3.24*0.16 + 0.06116±0.0028 •E.T(30) (4-3)
(n = 6, s = 0.0068)
The ratio of the two slopes found in equations 4-2 and
4-3 is 1.44. That is, selectivity in the raethanol/water
system is more greatly affected by overall changes in
mobile phase polarity than with acetonitrile as the organic
modifier. It should also be noted that the value of this
ratio is the same as that found for slopes of log k' versus
ET(30) (see discussion of slope ratios in Chapter V).
Literature Data
A wealth of methylene selectivity has been published
in the literature by various workers. In some cases, the

117
log aCH2 values have been tabulated (with respect to
percent organic modifier), while in other cases the log
aCH2 values can be calculated from the reported capacity
factors for a homologous series. As discussed in Chapter
III, in many instances the method used to measure tQ is not
reported. Regression was carried out for data reported in
six references.
The results of the various correlations with all data
sets discussed are shown in Table 4-1. Squared correlation
coefficients are reported for each of the three comparisons
(versus percent organic modifier, versus mole fraction,
versus E.j(30) polarity). This provides a way in which the
general trends of the data may be viewed. The main purpose
of these comparisons is to evaluate whether the methylene
selectivity correlates best with percentage of organic
modifier; in Figure 4-7 the results of Table 4-1 are shown
graphically. Squared correlation coefficients for log
versus percent organic modifier are plotted with respect to
those found for log cxq^ versus Erj(30) polarity. The line
drawn through Figure 4-7 corresponds to "iso-r-" values.
That is, all points would fall along this line if all
correlation coefficients were equivalent for the two
comparisons. Thus, a point appearing above the line
denotes a better correlation when the log 2 data are
plotted with respect to percent organic modifier. Of the

Table 4-1.
Squared correlation coefficients (r¿) for log a data with respect to percent organic
modifier (OM), mole fraction OM, and Erp(30) polarity.
2
r versus
Reference/OM
n
Cone.
Range
% OM
Mole
Fraction
Et(30)
This work/MeOH
5
50-80
0.9972
0.9397
0.9884
This work/ACN
6
32-68
0.9655
0.9173
0.9919
Karger et al. (1978)/MeOH
13
0-100
0.9943
0.9337
0.9782
Karger et al. (1978)/ACN
8
5-30
0.9186
0.7777
0.9921
Petrovic et al. (1985)/MeOH
7
40-100
0.9945
0.9501
0.9858
Schoenmakers et al.
(1981)/MeOH
6
10-100
0.9903
0.9488
0.9902
Schoenmakers et al.
(1981)/ACN
7
10-80
0.9102
0.8032
0.9859
Colin et al. (1983)/MeOH
11
0-100
0.9923
0.9592
0.9486
Colin et al. (1983)/ACN
9
0-80
0.9492
0.8829
0.9776
Dufek (1984)/MeOH
10
55-100
0.9983
0.9738
0.9936
Hanai and Hubert (1985)/ACN
6
20-70
0.9855
0.9684
0.9439
118

119
r2 vs. Et(30)
Figure 4-7. Comparison between r^ values for plotting
methylene selectivity data with respect to
either percent organic modifier or E-j(30)
polarity.

120
11 data sets, in seven cases the correlation is clearly
equal to or better than the "versus Erp(30) polarity"
comparisons.
There are a number of conclusions that can be reached
regarding the data in Table 4-1 . One interesting pattern
that is apparent is that for every data reference where the
methylene selectivity was measured with both organic
modifiers, the correlation coefficients for "versus percent
organic modifier" and "versus E That is, in methanol/water mixtures, the methylene
selectivity varies most closely with the percent organic
modifier, while in the acetonitrile/water system, Erj,(30)
polarity values yield the highest correlation. In contrast
to the excellent correlations seen between log k' and
Et(30) polarity (Chapter III), here there is a clear-cut
distinction between the two organic modifiers.
Of course, the variation with respect to percent
organic modifier is also quite complex, especially with
acetonitrile/water mixtures. Colin et al. (1983) found
that, except for methanol/water mixtures, every system
studied exhibited a nonlinear variation in log aQ^2 with
respect to percent organic modifier.
Hamilton PRP-1 Column Selectivity Measurements
While RPLC is typically done with chemically bonded
silica, there are other materials that may serve as a
suitable stationary phase. In recent years, a number of

121
polymeric reversed phase columns have become commercially
available. Polymeric columns are normally prepared by the
polymerization of styrene with divinylbenzene. In this
manner, a highly crosslinked co-polymer is created. If the
degree of crosslinking is sufficient, swelling effects will
be minimized, and the column can be used under a wide
variety of mobile phase conditions with minimal changes in
back pressure. The polymer matrix offers a highly
hydrophobi surface consisting of both aromatic ring
systems and saturated alkyl chains and thus can be used in
a RPLC sense.
Polymer based RPLC columns offer a number of potential
advantages over their more traditional counterparts. Among
these advantages is stability to a wide range of pH.
Conventional bonded phases are not usable under extreme pH
conditions. At pH values less than 2, hydrolysis of the
siloxyl bonds leads to cleavage of the bonded chains from
the silica surface, resulting in lowered retentivity and an
increase in surface silanols. At a pH of greater than 8,
the solubility of the silica in the mobile phase increases
dramatically, ultimately leading to a degradation of the
packing structure of the column and resultant lowered
efficiencies and retentivity. Unlike silica based columns,
polymer based columns are stable to pH levels of 1-13 or
high concentrations of buffer salts, with no degredation in
performance.

122
Another aspect of these columns that can be of use is
their preferential retention of the aromatic compounds.
Apparently the presence of aromatic n-electron orbitals
leads to preferential retention of aromatic solutes,
leading to different chromatographic selectivity than that
found with conventional RPLC columns.
A final advantage is the lack of any silanol groups
whatsoever. As mentioned in Chapter I, the presence of
these groups on the surface of conventional bonded phases
can be a problem with highly polar solutes, which will in
effect be retained by a dual adsorption/partitioning
mechanism. Thus, polymeric columns are, by virtue of their
composition, entirely free of these troublesome residual
silanols.
Given the above factors, one might logially inquire as
to whether polymeric columns are likely to replace the
(currently) more popular bonded phases. This is not likely
in the immediate future, owing to their generally lower
efficiencies. Though small particle sizes (5 and 10 micron
mean diameter) are now available, the number of plates
delivered per unit length is still significantly less than
conventional columns, and thus in situations where large
plate numbers must be generated, their utility is
diminished. This lowered efficiency is most likely due to
an increase in the resistance to mass transfer, since the
entire volume of the particles comprises the stationary

123
phase, and thus diffusion of the solute into the interior
of the particles is much slower than the corresponding open
pores found with silica based matrices.
The experiments carried out with a Hamilton PRP-1
column are discussed in the following text and involved
measuring the methylene selectivity over 0-100# methanol
and 0-80# acetonitrile. Owing to the high retentivity of
the polymer matrix with respect to aromatic compounds, it
was found that the homologous series of alkylbenzenes is
unsuitable at low concentrations of organic modifier (i.e.,
less than 60# v/v). Therefore, nitroalkanes (nitromethane
through nitrohexane) were used to measure log values,
and were found to be usable over the entire range of
organic modifier concentration.
In light of the fact that the polymeric column has a
preferential retentivity toward aromatic compounds, it was
necessary to insure that the use of a different homologous
series would not significantly affect the measurement of
log agj-i2* Both nitroalkanes and alky lbenzenes were used to
measure this at three different concentrations in the two
organic modifiers. Concentrations were chosen such that
the alkylbenzenes could still be used to measure the
methylene selectivity (>60# organic modifier). The results
of these comparisons are found in Table 4-2 and are plotted
in Figure 4-8. The slope of the line drawn through the

124
lOgo Figure 4-8. Comparison between methylene selectivity
results obtained with either 1-nitroalkanes or
alkyIbenzenes as the homologous series.
Hamilton PRP-1 (polymeric) column; flow rate
1.0 mL/rain.

125
data was 1.02±0.17 with a y-intercept of -0.005±0.04.
Based on these results, it does not appear that the
measurement of methylene selectivity is significantly
biased by the homologous series used to measure it and is
consistent with results published for conventional bonded
phases.
Table 4-2.
Comparison of log « values as measured by
nitroalkanes and alkylbenzenes for a Hamilton
PRP-1 column.
Mobile Phase
50$ ACN
65$ ACN
80$ ACN
70$ MeOH
80$ MeOH
90$ MeOH
i°g aCH2
Alkylbenzenes
0.22
0.17
0.13
0.32
0.24
0.17
Nitroalkanes
0.23
0.16
0.13
0.31
0.24
0.17
One distinct disadvantage of the use of nitroalkanes
is their generally low absorption of light in the UV
region. For
example,
the
molar
absorptivity
of
nitromethane is
only 18.6
in
ethanol,
with a Xmax
of
271 nm. Nevertheless, it was found that by increasing the
concentration of nitroalkanes in the injected standards to
approximately 5 mg/mL (20 raicroliter sample volume; 100 ug
injected), a 254 nm UV detector could still be used to
detect the nitroalkanes. The peak shapes did not appear to

126
be distorted by the large amount of injected solute; this
may be a reflection of the nature of the polymeric
stationary phase, since a higher loading level should (in
theory) be tolerated.
A representative example of the measurement of the
methylene selectivity is shown in Figure 4-9, where data
for 80# methanol have been plotted. "Carbon #" denotes the
size of the nitroalkane (1 = nitroraethane, 2 = nitroethane,
etc.). Correlation coefficients for the three comparisons
discussed herein appear in Table 4-3.
Table 4-3.
Correlations between log a and percent organic modifier
(OM), mole fraction organic modifier (MF OM), or E^(30)
polarity for a Hamilton PRP-1 polymeric column.
Mobile Phase n versus % OM versus MF OM versus E^(30)
Methanol 11 0.9989 0.9498 0.9692
Acetonitrile 9 0.8816 0.7352 0.9731
The results of the measurements of log acH? f°r
raethanol/water mixtures appear in Figures 4-10 through
4-12. Figure 4-10 shows that the methylene selectivity
decreases in a highly linear fashion as the percent (v/v)
of methanol is increased. The regression line corresponds
to

127
log a = -5.24*0.34 + 0.0970±0.0058 *ET(30) (4-4)
(n = 11, s = 0.0468)
Plotting log a with respect to mole fraction leads to
strong curvature. Also, as shown in Figure 4-12, plotting
with respect to the Erp(30) also results in curvature,
though at higher Erj(30) polarities (lower methanol
concentrations) the behavior is nearly linear.
The results for the same measurements with
acetonitrile as an organic modifier appear in Figures 4-13
to 4-15. Here the curve shapes are distinctly different
than those seen with methanol. Instead of linearity versus
percent organic modifier, strong curvature is seen; this
behavior in the two organic modifiers is quite similar to
that seen with standard bonded phase columns. The change
in log aQ^2 -*-s most pronounced at low concentrations of
organic modifier. Finally, in Figure 4-15, the selectivity
increases in a nearly linear manner, with strong curvature
seen at high E.j.(30) polarity values (low acetonitrile
concentration). If the data in Figures 4-15 are fitted to
a straight line model, the resultant regression line is
given by
log « = -4.53*0.31 + 0.0847*0.0053 ^(30) (4-5)
(n = 9, s = 0.0411)

128
Figure 4-9. Example of the measurement of methylene
selectivity with nitroalkanes as the
homologous series. Hamilton PRP-1 column;
flow rate 1.0 raL/min; 80$ methanol as the
mobile phase.

129
% Methanol
Figure 4-10. Chromatographic selectivity measurements as a
function of percent methanol. Hamilton PRP-1
column; flow rate 1.0 mL/min. Nitroalkanes
were used as the homologous series.

130
Figure 4-11. Chromatographic selectivity measurements as a
function of mole fraction of methanol.
Hamilton PRP-1 column; flow rate 1.0
mL/min. Nitroalkanes were used as the
homologous series.

131
E-j- (30)
Figure 4-12. Chromatographic selectivity measurements as a
function of Ej,(30) polarity of methanol/
water mixtures. Hamilton PRP-1 column; flow
rate 1.0 mL/min. Nitroalkanes were used as
the homologous series.

132
% Acetonitrile
Figure 4-13. Chromatographic selectivity measurements as a
function of percent acetonitrile. Hamilton
PRP-1 column; flow rate 1.0 raL/min.
Nitroalkanes were used as the homologous
series.

133
Figure 4-14. Chromatographic selectivity measurements as a
function of mole fraction of acetonitrile.
Hamilton PRP-1 column; flow rate 1.0
mL/min. Nitroalkanes were used as the
homologous series.

134
Et(30)
Figure 4-15. Chromatographic selectivity measurements as a
function of E^(30) polarity of acetonitrile/
water mixtures. Hamilton PRP-1 column; flow
rate 1.0 mL/min. Nitroalkanes were used as
the homologous series.

135
At 100$ organic modifier concentration, the log
values are 0.0350 and 0.0754 for methanol and acetonitrile,
respectively. This is as one .might expect, owing to the
greater "strength" of acetonitrile as an organic modifier
in RPLC. Lastly, it should be noted that log values
for this column are significantly higher at a given percent
organic modifier than that of the Ultrasphere ODS bonded
phase column. This shows that the polymeric surface is
even more "hydrophobic" than the bonded phases, since the
free energy of transfer of a methylene group is larger in
magnitude.

CHAPTER V
DISCUSSION AND CONCLUSIONS
The purpose of the research described here is to
examine the exact role that the polarity of the mobile
phase plays in the retention of solutes in reversed phase
liquid chromatography. Study of chromatographic retention
mechanisms can involve examination of the stationary phase
(e.g., FTIR and NMR experiments), the mobile phase (as
discussed herein), or some combination of the two (i.e.,
retention measurements). In general, the E^(30) polarity
serves as a good measure of the strength of the binary
aqueous/organic mobile phases used in RPLC. Specifically,
plots of log k' versus Erj(30) polarity are better
descriptors of chromatographic retention than commonly used
plots of log k* versus percent organic modifier.
Plotting log k' versus E,p(30) yields two coefficients
(slope and y-intercept); the slope has the most physical
significance, in that it measures the change in free energy
of transfer of the solute as a function of changes in
Ef(30) polarity. Y-intercepts signify the log k' value
where the E-p(30) polarity is zero. Of course, an E^(30)
polarity of zero is meaningless; this would correspond to
136

137
equivalence of energy of the ground and excited states of
the ET-30 molecule. A more useful intercept would be
calculable if the UV/VIS absorption spectrum of ST-30 could
be measured in the absence of any solvation (i.e., in the
gas phase). If this were known, then the log k' value for
a completely inert mobile phase could be established,
providing information about the stationary phase.
Unf ortunately, the Erp(30) molecule is quite nonvolatile,
with an indefinite melting point in the region of 273°C
(Dimroth et al., 1963a). Gas-phase tt* values have been
reported (Abboud et al., 1934; Essfar et al., 1982); this
was possible since the solutes that define the tt* scale are
much more volatile (e.g., 4-ethylnitrobenzene, which is a
liquid at room temperature). Despite the lack of a gas-
phase E-p(30) polarity value, there is still much
information provided by the slope of log k' versus ET(30)
polarity.
With regard to these slope values, if the change in
the free energy of the retention process were exactly the
same as the change in the E.p(30) polarity, the slope of the
resultant line would be 0.73 at 25°C (it would be exactly
1.0 if instead of log k', 2.303 RT*log k' were being
plotted).
The slope and y-intercept values shown in Table 3-1
for the 332 sets of chromatographic retention data examined
here provide much information about the effect of changing

138
mobile phase polarity on retention. There are systematic
trends in the slope based on the size or type of molecule
being examined. Also, information about the stationary
phase solvation is also provided indirectly, as will be
discussed later in this chapter. Although all slope and y-
intercept values have been tabulated in Table 3-1 , it is
instructive to discuss small subsets of this master table,
in order to highlight the effects of increasing solute size
and nature of the column upon sensitivity to changes in
mobile phase polarity.
As the size of the molecule is increased, the
magnitude of the slope and y-intercept also increase. This
effect is demonstrated in Table 5-1 , in which the
regression results for alkylbenzenes in the two solvent
systems have been tabulated. In Table 5-1, "Data set
refers to the line number of Table 3-1 from which the data
are taken. This increase in sensitivity to changes in
E alkyl chain, as demonstrated in Figures 5-1 and 5-2, where
the slopes for the two systems are plotted with respect to
carbon number. The regression equations for the two lines
are
(in MeOH) slope = 0.383±0.002
+ 0.0884±0.0008«Carbon # (5-1)
(n = 4, s = 0.00074)

Table 5-1 .
Effect of increasing
alkylbenzenes.
solute size upon sensitivity to
changes in E.j(30)
polarity for
Data Set #/Solute
Column/Mobile Phase
Slope (X 10-2)
-(y-int)
5/Benzene
A/ACN (C—18)
34.5
19.0
12/Toluene
ft
40.9
22.5
7/Ethylbenzene
fl
47.2
25.8
8/Isopropylbenzene
II
52.3
28.5
6/n-Buty1benzene
II
60.2
32.7
328/Benzene
B/MeOH (C-18)
38.2
21.4
331/Toluene
II
47.4
26.5
332/Ethylbenzene
II
55.8
31.0
330/Isopropylbenzene
II
63.0
35.0
329/n-Butylbenzene
II
73.7
40.8
139

140
(in ACN) slope = 0.345±0.001
+ 0.0642±0.0002«Carbon # (5-2)
(n = 4, s = 0.00087)
An interesting effect shown by equations 5-1 and 5-2
is that the slope in methanol is 1.37 times that found for
acetonitrile. This finding suggests different solvation of
the stationary phase in the two systems (see discussion in
the following section of this chapter). In a sense, this
type of plot is a correlary to the measurement of methylene
selectivity, where log k' is plotted versus carbon number
at a single organic modifier concentration (Chapter IV;
Figure 4-9). However, in this instance the organic
modifier concentration is being changed, so a plot of the
slope versus carbon number corresponds to something
different. This is perhaps best termed the "methylene
polarity selectivity." That is, what is being measured is
the effect of the overall mobile phase polarity on the
methylene group selectivity.
Another illustration of the effect of increasing
solute size is shown in Table 5-2, where the regression
coefficients for halobenzenes in the two solvent systems
are tabulated. As with the alkylbenzenes, the magnitude of
the slope and y-intercept increase in a regular fashion as
the halogen atom attached to benzene increases in size.
This general effect seen for all solutes is consistent with

Table 5-2.
Effect of increasing solute size upon sensitivity to changes in E^(30) polarity for
halobenzenes.
Data Set #/Solute
Column/Mobile Phase
Slope (X 10~2)
-(y-int)
179/Fluorobenzene
D/ACN (C-8)
36.2
20.2
177/Chlorobenzene
ii
40.7
22.6
176/Bromobenzene
it
42.0
23.2
180/Iodobenzene
it
44.5
24.6
291/Fluorobenzene
D/MeOH
50.8
29.0
289/Chlorobenzene
ii
57.1
32.4
288/Bromobenzene
ti
59.1
33.5
292/Iodobenzene
it
62.5
35.3

142
Slope
Figure 5-1.
Slope of log k' versus Erp(30) polarity as a
function of carbon number for methanol/water
mixtures. Ultrasphere ODS column; alkyl-
benzenes .

143
0.7
0.6
Slope 05
0.4
0.3
0 1 2 3 4 5
Carbon #
Figure 5-2. Slope of log k* versus ET(30) polarity as a
function of carbon number for acetonitrile/
water mixtures. Ultrasphere ODS column;
alkylbenzenes.

144
the solvophobic theory of Horvath, in which increasing size
(referred to as "hydrocarbonaceous surface area") would be
expected to increase retention (Horvath et al., 1976).
Another aspect, to be examined here is the dependence
on the sensitivity on the nature of the column. Again, as
with the molecular size, the length of the carbon chain of
the bonded phase appears to also increase the sensitivity
of the retention process to changes in the ET(30)
polarity. This is shown in Table 5-3 where the slope and
y-intercept values for phenanthrene for various columns
(C-2 through C-18) have been tabulated. In Table 5-4, the
same information is shown for ethylbenzene. The magnitude
of the slope appears to increase at the highest rate when
going from C-2 through C-8 type bonded phases, while the
increase is much less in going from C-8 to C-18. This
suggests that beyond a certain length (between 4 and 8
carbon atoms) of the alkyl chain, a steady state of
solvation is achieved, so that only the outer atoms in the
chain are solvated by the mobile phase. This is consistent
with the work of Berendsen and De Galan (1980), who found
that there is a "critical carbon number" for the chain
length beyond which retention is not greatly affected. It
was found to be slightly dependent on the solute size, with
an average of approximately eight. Croo et al. (1985)
reported similar results for some pharmaceutical compounds.

145
Tabla 5-3.
Comparison of slope and y-intercept values for
log k' versus E,p(30) polarity for phenant'nrene.
Column/Solvent Slope (X 10~2) -(y-int)
A/ACN (C-18)
60.0
32.9
B/ACN (C-2)
43.9
27.2
C/ACN (C-4)
50.2
27.8
D/ACN (C-8)
53.6
32.2
E/ACN (C-18)
57.6
31.4
B/MeOH (C-2)
69.2
39.6
C/MeOH (C-4)
73.9
41.3
D/MeOH (C-8)
80.7
45.4
Table 5-4.
Comparison of slope
and y-intercept
values for
log k’ versus £^(30)
polarity for e
thylbenzene.
Column/Solvent
Slope (X 10*2)
-(y-int)
A/ACN (C-13)
47.2
25.8
B/ACN (C-2)
34.4
19.1
C/ACN (C-4)
37.8
20.9
D/ACN (C-8)
45.6
25.2
E/ACN (C-18)
48.9
26.8
B/MeOH (C-2)
46.1
26.5
C/MeOH (C-4)
51.8
31.1
D/MeOH (C-8)
64.0
36.2
Finally,
aromatic
substitutional
isomers appear
to
have nearly
identical
sensitivity to
changes
in
the
polarity of
the mobile
phase. This is
illustrated quite
clearly with
the isomers of ethylphenol
(sets 27,
35,
and
40), in which the 2-, 3-, and 4-ethylphenols have slope and
y-intercepts of 0.342/0.339/0.341 and -18.8/-18.6/-13.7,
respectively.

146
Chromatographic retention is, from a thermodynamic
standpoint, the result of differences in free energy of the
solute as it transfers between the mobile and stationary
phases. This can be expressed quantitatively by the
following equation:
log k' = -2.303 ag/RT + log (♦) (5-3)
where <}> is the phase ratio of the column (V„/V_). Of
course, the AG term can be separated into the individual
contributions of AH and AS, resulting in the following
equation:
log k’ = -2.303 AH/RT + 2.303 AS/R + log () (5-4)
Thus, plotting log k' versus 1/T yields the enthalpic
change for the retention process. These plots can also be
used to assess whether the retention process occurs by a
dual mechanism, which is indicated by nonlinearity.
It can be seen in equation 5-4 that the ah is
unaffected by the phase ratio of the column. Woodburn
(1985) has reported the enthalpies of transfer for a wide
variety of solutes and columns as a function of mobile
phase composition. Linear regression was done for these
values versus the E-j(30) values for the same solvent
mixtures. These results are summarized in Table 5-5, where

147
the r^ values for plots of AH versus E^(30) polarity have
been tabulated.
Table 5-5.
Correlations between enthalpy of transfer (AH)
and E"j(30) polarity values. Enthalpic data from
Woodburn (1985).
p
Column Type/Mobile Phase n Mean r^ Value
C-2/ACN
21
0.9608
C-4/ACN
22
0.9848
C-8/ACN
22
0.9538
C-2/MeOH
21
0.8406
C-4/MeOH
21
0.9706
C-8/MeOH
22
0.9439
In general, the correlation coefficients are much
lower than the corresponding plots of log k' versus E^(30)
polarity (Table 3-2). Sander and Field (1980) have studied
the variation in enthalpic and entropic contributions to
retention as a function of mobile phase composition for a
C-18 yBondapack column. For isopropylbenzene, the enthalpy
of transfer was found to increase in a nearly linear
fashion as the concent ration of methanol was increased from
45 to 100$, while N,N-diethylaniline exhibited less
predictable behavior.
There are only a handful of reports in the literature
regarding the correlation between chromatographic and
spectroscopic properties of solutes. One example is the
work of Fetzer and Biggs (1985), in which the spectral

143
properties of peropyrene polycyclic aromatic hydrocarbons
(PAHs) were correlated with anomalous retention behavior.
Anomalous retention behavior in this instance is defined as
not being consistent with molecular size. The retention of
PAHs can usually be predicted on the basis of molecular
size. It was found that the electronic spectra of PAHs in
different solvent mixtures were not significantly changed,
except in cases where anomalous retention behavior (such as
early elution with respect to similar-sized PAHs) was
observed. For these cases, there was evidence that changes
in the planarity of the ring system were induced by the
solvent. These changes in planarity then led to decreased
retention as well as a change in the spectral peak shapes.
Wirth et al. (1983) reported correlations between the
bandwidth of electronic 0-0 bands of the first excited
singlet states of dimethylnapthalenes and their relative
retention. As a measure of the repulsive/attractive forces
between the mobile phase and the test solute, the bandwidth
for each solute was measured in two different mobile phases
(n-dodecane and 85# acetonitrile/water). The difference in
bandwidths in the
two
systems
was then
compared to
retention times of
the
various
solutes,
and
a linear
relationship was found.
Solutes with
the
greatest
bandwidth difference
were
found
to be the
most highly
retained.

149
These two papers clearly demonstrate that there is a
relationship between spectroscopically observable solvation
of a test probe and its chromatographic retention. It
follows then that there should also be a relationship
between spectroscopically observable mobile phase
properties and chromatographic retention. With regard to
the E-j(30) polarity scale, one is observing (primarily)
changes in the solvation of the ground electronic state of
the molecule caused by changes in the solvent
environment. According to the Franck-Condon principle, the
time scale of optical absorption is such that the solvent
molecules do not have sufficient time to re-orient
themselves around the excited molecule. Thus, since the
ground state orbital electrons of E-j. (30) are much more
unequally distributed (shown by a dipole moment of
approximately 15 Debye) than that of the excited state (2
Debye), the solvation of the ground state is more sensitive
to the surrounding solvent (Reichardt et al., 1930).
Qualitatively, this is probably the most accurate way in
which to measure the mobile phase polarity (as opposed to
bulk properties such as dielectric constant, viscosity,
etc.), since chromatographic retention is directly related
to the free energy of solvation (ground state property) of
the solute in the two different phases.

150
Stationary Phase Effects
As mentioned previously, the slopes of log k' versus
Et(30) polarity are different for the same solute and
column in the two mobile phase systems. For the retention
data sets examined here, there were 89 cases in which data
for a given solute was available in both methanol/water and
acetonitrile/water mixtures. Thus, a slope ratio can be
calculated for each of these 89 cases. These slopes for
the two organic modifiers vary in a sytematic manner, in
that the ratio of the slopes found in the methanol/water
mixtures are consistently greater than those found with
acetonitrile/water mixtures. In Table 5-6 the average
ratios of the slope for a given solute and column are
shown. Overall, the average ratio was found to be 1.43 (s
= 0.06).
Table 5-6.
Ratio of slopes for a given solute and column with
methanol and acetonitrile as organic modifiers.
>lumn (type)
n
Average Ratio
Slope (MeOH)/Slope (AON)
s
A (C-18)
5
1.18
0.045
F (C-8)
25
1.49
0.083
B (C-2)
19
1.41
0.051
C (C-4)
20
1.49
0.041
D (C-8)
20
1.40
0.028
Initially, the higher slope found with methanol/water
mixtures would appear to be at odds with the general notion

151
of acetonitrile being a "stronger" solvent for reversed
phase liquid chromatography. However, this observation is
in fact entirely reasonable, if one considers the effect of
solvation of the stationary phase. That the slope is
different for the two organic modifiers is evidence of the
importance of the stationary phase in the retention
process. If the stationary phase was truly "inert," the
slopes should be equal, as the E^(30) measures the actual
solvating power of the mobile phase, and iso-E should have equivalent elution strengths. An example of
ET-30 measuring a solution property was published by Elias
et al. (1981), in which the ET(30) polarity values were
correlated with a reaction rate constant. Also, heats of
solution at infinite dilution have been correlated with the
Et(30) polarity of some pure solutes (as discussed in
Chapter I). Here, actual retention is a result of the free
energy change as a solute transfers from the mobile to
stationary phases. Thus different slopes of log k' versus
E.^OO) must indicate that the solute is experiencing a
different environment in the stationary phase as the
organic modifier is changed from methanol to
acetonitrile. The greater slope in methanol water shows
that for an equal change in mobile phase polarity,
retention is affected to a greater extent in methanol/water
systems.

152
This is entirely consistent with results of earlier
workers who have measured the distribution isotherms for
organic modifiers used in reverse phase chromatography. In
particular, McCormick and Karger (1930a, 1980b) showed that
at all concentrations of organic modifier, the stationary
phase contains a higher concentration of acetonitrile.
Thus, the higher slope (versus polarity) found in
methanol/water systems is a reflection of the fact that
there is much less methanol in the stationary phase, so a
change in the mobile phase polarity will influence
chromatographic retention to a much greater degree than in
acetonitrile/water systems, where a change in overall
mobile phase polarity is compensated by more or less
solvation of the stationary phase. Herein lies one of the
advantages of plotting retention versus Efj>(30) polarity, in
that the effect of the stationary phase can be deconvoluted
from that of the mobile phase. Chromatographic retention
is a function of the nature of both the stationary and
mobile phases, while the polarity measurements are a
function of the mobile phase only.
Another way in which the regression coefficients for
log k' versus E^(30) polarity can be applied is by
calculating intersection points of the lines defined by log
k* versus percent organic modifier. That is, the
intersection points for the lines described for various

153
solutes can provide information about the polarity of the
stationary phase.
There are two distinct groups of intersection points
that can be described for each column. The first,
involving the lines described for one solute and column in
the two mobile phase systems, provides very little
information. That is, the two lines will intersect at the
point where the log k' values are equivalent, which will
occur only when the mobile phase is pure water, i.e.,
E^(30) = 63.1 kcal/raole.
The second type of intersection point is that for
different solutes with the same organic modifier and
column. In this instance, the intersection point
corresponds to the Erj(30) solvent polarity where the log k'
values are equal. In other words, it is at this polarity
where the solutes "see" the same difference between the
stationary and mobile phases, and hence the ET(30) polarity
of this point provides a measure of the polarity of the
stationary phase. Of course, for each set of n lines,
there will be a total number of intersection points given
by
Ntotal = (n"1) + (n-2) + (n_3) + *•* 1 (5-5)
A problem arises when comparing lines of very similar
slope, since the intersection point for lines that are

154
nearly parallel will be extremely susceptible to minor
fluctuations in the slope values. One way in which to
address this problem is to use lines which differ
significantly in their slopes, and thus will provide better
estimates of the true point of intersection. Thus,
homologous series lend themselves to this type of
calculation, since the slopes change in a regular fashion
with the size of the alkyl chain. Moreover, use of only
one family of compounds reduces the effect of any specific
interactions with the stationary phase.
The results of calculations of the intersection points
for the homologous series of alkylbenzenes are shown in
Table 5-7. Confidence limits reported are for the 95#
level. A general trend can be seen in that the E.j(30)
Table 5-7.
Intersection points for log k* versus E.j(30) for
alkylbenzenes.
Column/Mobile Phase
Erjl( 30) *
n
A (C—18)/ACN
53.3±0.8
6
" /MeOH
54.5±0.6
6
B (C-2)/ACN
54.S±0.3
10
" /MeOH
55.3±0.1
10
C (C-4)/ACN
54.2±0.5
15
" /MeOH
55.6+0.1
10
D ( C-8)/ACN
53.6±0.3
15
" /MeOH
54.6±0.6
6
E (C—18)/ACN
52.6±0.3
15
♦Average E alkylbenzenes is equivalent, obtained from
intersection points of log k' versus E.j(30)
lines. Confidence intervals are based on t
statistic, n-1 degrees of freedom.

155
polarity
for
equivalent re
tention
is always
greater
when
methanol
is
used as the
organic
modifier
for a
given
column.
For
columns B,
C, and
D, this
difference is
statistically significant at the 95% confidence level.
In addition, as the length of the bonded phase chain
increases, a mobile phase that is less polar (stronger) is
required to achieve equivalent retention. This trend makes
physical sense, in that as the length of the carbon chain
is increased, the stationary phase surface behaves more
like an alkane, and thus one would need a less polar mobile
phase (hence stronger) to achieve equivalence of
polarity. Moreover, the volume of stationary phase (Vs) is
increased by lengthening the carbon chain, also leading to
increased retention.
It is also interesting to note that in raethanol/water
systems, this point of equivalent retention is difficult to
reach, since the Erj,(30) polarity of pure methanol is 55.6
kcal/raole, while with acetonitrile this is easily done,
i.e., E-j.(30) = 45.6 kcal/mole for pure acetonitrile.
Therefore, these results suggest that the effective
polarity of the stationary phase is different when in the
presence of the two organic modifiers and that it is
intermediate in polarity between methanol and acetonitrile.

156
Application of These Results
In Snyder's formulation of solvent P' values (Snyder,
1978), it was stated that the effective P' value for a
mixture of two solvents, A and B, is given by
where is the volume fraction of the two components.
Since the two volume fractions must add up to one, the P"
is then given by
(5-7)
Also, in terras of chromatographic retention of a given
solute in two mobile phases of different P' values, the
following expression can be written:
log k¿ - log = (P¿ - P¿)/2
(5-8)
The constant "2" in equation 5-8 has no fundamental basis
other than the observation by Snyder and Kirkland that
. a change in P' by two units causes (very roughly) a
10-fold change in k' values ..." (Snyder and Kirkland,
1979, p. 258). Both of these equations are consistent with
the statement "log k' will vary in a linear manner with the
volume fraction of the organic modifier."
As has been

157
discussed, this assumption is generally not warranted.
Moreover, the magnitude of P' values for methanol and
acetonitrile implies that k’ values should actually
increase when going from methanol to acetonitrile (as
discussed in Chapter II). In view of these problems,
better results could be obtained by using the Ep(30)
polarity values for the solvent mixtures themselves. This
leads to the following expression:
log - log kjj = [E^(30) - eJ(30)]*s (5-9)
where s is a constant for a given solute and column. Of
course, this is precisely what one is doing when plotting
log k' versus E-p(30) polarity values. In this case the
slope of such a line would correspond to the parameter s.
There is another way in which this approach may be
extended, by using the equation that Langhals proposed to
account for the variation in Ep(30) polarity as a function
of solvent mixture composition (see also the discussion of
this equation in Chapter I).
The "Langhals equation" relates the Ep(30) polarity
value to the molar concentration (Cp) of the most polar
component in a binary mixture as shown below:
ET(30) = Ed ’ ln [(Cp/C*) + + E°(30) (5-10)

158
In the above equation, E^, C*, and E^(30) are constants,
and have been reported for 46 solvent systems (Langhals,
1982a). Thus, it is possible to derive an expression
relating a change in the concentration of organic modifier
to a change in the log k' value for a given compound.
First, the concentration of water in moles per liter is
changed to percent organic modifier by
Cp = (100 - % organic) . a (5-11)
where a is a constant incorporating the density and
molecular weight of water. At 20°C, this constant has a
value of 0.5541. Substituting equation 5-11 into 5-10
leads to the following equation for a change in Eji(30)
polarity with changing percentage of organic modifier:
[(100 - % organic,.).a] + C*
AE (30) = E ,.ln( ! ) (5-12)
[(100 - % organic2)*a] + C*
The change in log k' can then be calculated by using
equation 5-9.
Equation 5-9 is also quite useful for predicting
changes in retention when the organic modifier is changed
between acetonitrile and methanol. As discussed previously
in this chapter, there is evidence that the slope of log k'
versus Erp(30) polarity varies in a systematic manner in the
two solvent systems examined here. Therefore, if the slope

159
is known for one of the solvent systems, the ratio of the
slopes for the column can then be used to calculate the
slope for the other solvent system. Then using equations
5-9 and 5-12, the change in log k' can be predicted for the
second solvent system without making any additional
measurements.
Herein lies one of the great strengths of these
polarity measurements, in that changes in chromatographic
separations can be predicted with minimal need for
collection of experimental data. For a given column, only
three experiments need be done for a prediction to be made
with regard to the retention in the two solvent systems and
at various concentrations. These three experiments can be
summarized as follows:
1) measure k’ in solvent system A at a low
concentration of organic modifier
2) measure k' in solvent system A at a high
concentration of organic modifier
3) measure k' in solvent system B at any single
concentration of organic modifier.
Experiments 1 and 2 serve to establish the slope of
Erj-i(30) versus organic modifier (parameter "s" in equation
5-9). Experiment 3 establishes one point on the line for
system B, which when combined with the slope ratio for the
two systems and using equation 5-12 allows prediction of

160
changes in retention as a function of organic modifier and
its concentration.
In conclusion, the predictive ability of these types
of experiments can be applied in a number of ways;
optimization of separation conditions for complex mixtures
can be undertaken with a minimum amount of initial
experimental work, involving as little as three retention
measurements for each compound.
Interfacial Tension Effects
One aspect of chromatographic retention that will also
be discussed briefly is that of the role of interfacial
tension in solute retention. A number of investigators
have shown that retention may be viewed as a result of the
interfacial tension between the mobile and stationary
phases. Therefore, the surface tension of the mobile phase
is likely to play a major role in determining solute
retention. As the surface tension of the mobile phase is
lowered, the distribution coefficient of the solute should
also be lowered, leading to a decrease in retention. Of
course, since water has a very high surface tension with
respect to organic modifiers, the observed decrease in
retention is consistent with the predicted effect. In
Figures 5-3 through 5-6, the variation in surface tension
in binary raethanol/water and acetonitrile/water mixtures is

161
Surface
Tension
(dyne/cm)
Figure 5-3. Variation in surface tension as a function of
percent methanol.

162
y
Methanol
Figure 5-4. Variation in surface tension as a function o
mole fraction of methanol.

163
Surface
Tension
Figure 5-5. Variation in surface tension as a function of
percent acetonitrile.

164
Surface
Tension
(dyne/c
Figure 5-6.
Variation in surface tension as a function of
mole fraction of acetonitrile.

165
shown with respect to volume percent and mole fraction. In
both cases, the surface tension is a highly nonlinear
function of composition. In the case of acetonitrile,
there is a rapid drop at the lower concentrations, followed
by a plateau, while methanol exhibits a steady, almost
linear decrease at higher concentrations.
The effect of interfacial tension in solute retention
has been illustrated by Deming and co-workers (Stranahan
and Deming, 1982; Wu and Deming, 1935), who derived a four-
parameter thermodynamic model of solute retention. In
particular, the effect of surfactant concentration was
examined; it was shown that capacity factors of uncharged
solutes could be related to the concentration of a
surfactant in the mobile phase by
k. = k . • (1 + c./b.)_b (5-13)
-1 U f 1 J J
where Cj is the concentration of the surfactant, and b^ and
b are constants that are related to the ability of the
surfactant to lower the interfacial tension of the
system. Taking the logarithm of equation 5-13 then leads
to the following expression:
In k. =
i
In k . + -b*ln(1 + c./b.)
o,i j' J
(5-14)

166
What is especially interesting is that the previously
discussed Langhals equation is of the exact same form (see
equation 5-10; this equation is also discussed in Chapter
I). In. the Langhals equation, the correlary to the Cj
J
surfactant concentration terra of equation 5-14 is Cp, which
is the concentration of the most polar component of a
binary mixture. Since there is such a strong correlation
between E.p(30) polarity and retention, it is worthwhile to
construct plots of E^(30) versus surface tension in the two
organic modifier systems.
In Figures 5-7 and 5-8, the surface tension for binary
mixtures is compared with the E-p(30) polarity for the
methanol and acetonitrile systems, respectively. Data
points for 90 and 100% acetonitrile have been omitted from
Figure 5-3, in order to avoid compressing the axes (the
Et(30) polarity changes by >10 in this range). For
raethanol/water mixtures, the relationship is nearly linear
if 100% water is excluded (E^(30) = 63.1 kcal/mole), while
in acetonitrile/water mixtures strong curvature is noted.
Suggestions for Future Research
A number of potential extensions of this research have
been identified. The present research has dealt with the
retention and selectivity of solutes in reversed phase
systems, since it is the most widely used LC technique.

167
Figure
64
62
60
58
56
54
20 30 40 50 60 70 80
Surface Tension (dyne/cm)
5-7. Comparison between surface tension and E>j.(30)
polarity for methanol/water mixtures.

168
Et(30)
Figure 5-8. Comparison between surface tension and Em(30)
polarity for acetonitrile/water mixtures
(0-80# v/v).

169
However, there are still many separations for which normal
phase chromatography is the method of choice. This is
especially true for highly polar compounds which are poorly
retained by typical bonded phases. Normal phase liquid
chromatography (NPLC) involves the use of either silica or
bonded phases with polar groups such as nitrile or amino
groups. Typical mobile phases are nonaqueous binary or
ternary solvent mixtures (for example, hexane/chloroform or
heptane/ethanol), whose strength is adjusted by varying the
proportion of the components.
It should, therefore, be possible to determine the
Erj(30) polarity of these mixtures as has been done with the
water/organic systems described in this dissertation and to
then compare these measurements with chromatographic
retention, as well as Snyder's e° eluent strength
parameters for NPLC solvents. A potential problem with
NPLC mobile phases (and one that can be solved) is the low
solubility of the ET-30 in pure nonpolar solvents such as
hexane or heptane. As described in Chapter I, the use of
the penta (tert-butyl) derivative of ET-30 allows one to
measure the ET(30) polarity of such solvents. Thus, by
using this more lipophilic betaine dye, one may measure the
effective E>j(30) polarity of the mixture, since there is a
linear correlation between its absorption maximum and that
of ET-30 in solvents of mutual solubility (Reichardt and
Harbusch-Gornert, 1933).

170
Another potentially fruitful area is that of examining
the surface polarity of stationary phases with the ET-30.
Pyrene has been used to a large extent as a probe of the
surface
polarity
(see Chapter I)
, but its
use at
high
organic
modifier
concentrations
has been
hindered
by
solubility in the
mobile phase.
On the other hand,
the
ET-30 dye may be an ideal probe molecule for the surface
polarity measurement of bonded phases. Attempts to measure
the capacity factor of the ET-30 dye were unsuccessful; it
was found that ET-30 is completely retained by a reversed
phase column packing, even with a mobile phase of 100$
acetonitrile. Thus, it is likely that this dye would be
ideally suited as a probe molecule, since it has a high
affinity for the stationary phase and appears to remain
sorbed to the packing even in the presence of 100$ organic
modifier. It should be possible to sorb the dye onto a
reversed phase packing and then to measure its (UV/VIS)
diffuse reflectance spectrum, using the packing with no
sorbed ET-30 as the reference. It should also be possible
to obtain these spectra in the presence of various
concentrations of organic modifier and thus obtain surface
polarity data that cannot be obtained with pyrene as the
probe. Using this approach, one could then compare the
variation in stationary phase polarity as a function of
organic modifier concentration with that of the mobile
phase. That is, the same probe molecule would be used to

171
measure the polarity of the two phases, helping to minimize
specific solvent association effects for the ET-30 dye.
A potential problem is that of overloading the column
packing, in which case the results would not be indicative
of the true condition of the stationary phase. In fact,
this problem is implied by the work published by Lindley et
al. (1985), who carried out experiments of this type with
dry samples of silica (discussed in Chapter I). The ET(30)
polarity was found to be a function of its concentration,
which implied that more than a monolayer of the dye had
been applied and/or dimerization had occurred.
The solvatochromic comparisons recently reported by
Sadek et al. (1985b; equation 3-7) included no solutes with
significant hydrogen bond donating ability (a value of
zero). The a values are measured by the enhanced
solvatochroraisra of ET-30 with respect to 4-nitroanisole.
It would be worthwhile to attempt correlations of the type
used by Sadek and Carr, with the inclusion of the a value
as a parameter in equation 3-7 (in addition to those
already used--molar volume, 3, and it*). The a values may
be found in the literature (Kamlet et al., 1983), or
experimentally determined.
To further clarify the meaning of the observed slope
of log k* versus ET(30) polarity in the different solvent
systems, it would be useful to measure retention and E^(30)
polarity for a homologous series of organic modifiers.

172
That is, by using a homologous series, such as methanol,
ethanol, n-propanol, etc., one could better interpret the
different slopes in log k' versus E^(30) polarity, since
these modifiers would be expected to solvate the stationary
phase in direct proportion to their size. Therefore, any
change in the slope would add further evidence to the
argument that a change in the nature of the stationary
phase is actually being measured. Also, use of a
homologous series as a mobile phase will limit specific
solvent association effects with the E^(30).
In addition, ternary solvent systems could be explored
in the same manner as the binary systems previously
discussed in this dissertation. For a system such as
MeOH/ACN/^O, there should be a gradual change in the
slopes of log k' versus E^(30) polarity as the ternary
mixtures are varied between the two binary extremes. This
would provide additional information about the solvation of
the bonded phase alkyl chains.
Lastly, these results can be applied to gradient
elution schemes, in which the strength of the mobile phase
is changed during the separation. Snyder and Dolan have
derived a number of useful equations in which the optimum
gradient can be selected (Dolan et al., 1979; Snyder et
al., 1979). However, in the derivations of what
constitutes an optimal gradient, it is assumed that log k'
values vary as a linear function of the organic modifier

173
concentration. Since the Erp(30) polarity values represent
a better measure of mobile phase strength, it should be
possible to substitute the concentration dependence of
2^(30) values for the portion of these equations in which
the function log "k1 = f()" is incorporated. This
function could be obtained from either a polynomial least-
squares fit of Eip(30) versus percent organic modifier, or
from the Langhals equation (Langhals, 1982a). In this
manner, it should be possible to derive more optimum
gradients which reflect the true variation in retention as
a function of the strength of the mobile phase.

APPENDIX A
CHROMATOGRAPHIC RETENTION AND
SELECTIVITY DATA

175
Reference: This Work
Column: Ultrasphere ODS
Mobile Phase: acetonitrile/water
Compound
10
20
30
2-Nitroaniline
15.950
7.178
3.664
4-Nitroaniline
7.917
3.940
2.105
4-Nitroanisole
48.435
19.218
8.478
4-Nitrophenol
12.452
5.263
2.490
k1 at % ACN
40
50
60
2.279
1.377
0.592
1.417
0.921
0.872
4.491
2.415
1.479
1.547
0.929
0.601
80
0.891 0.497

176
Reference: This Work
Column: Hamilton PRP-1
Mobile Phase: methanol/water
k' for
nitroalkanes
(NCx)*
%MeOH
NC1
NC2
NC3
NC4
IMC6
0
3.2192
21.5225
10
2.6168
15.3288
95.7718
—
—
20
2.1532
10.0736
51.9280
—
—
30
1.7178
6.7628
29.4204
—
—
40
1.3123
4.4429
15.7417
—
—
50
1.0308
3.0691
8.6171
—
—
60
0.7455
1.8679
4.2665
10.6629
—
70
0.5728
1.2335
2.4047
5.0586
—
80
0.6367
1.0495
1.6877
2.9039
8.3344
90
0.5090
0.7267
0.9921
1.4444
—
100
0.4001
0.5015
0.5856
0.7230
1.0753
Mobile
Phase: acetonitrile/water
k' for nitroalkanes
(NCx)
$ACN
NC1
NC2
NC3
NC4
NC6
0
4.5122
31.5203
10
2.1382
7.5122
29.2439
—
—
20
1.5203
4.1057
11 .8130
34.3537
—
30
1.1138
2.5528
5.9268
13.7304
—
40
0.7642
1.4797
3.2520
6.3984
23.1463
50
0.6992
1.1789
2.0163
3.4472
9.4553
60
0.5447
0.8374
1.2850
1.9756
4.4309
70
0.4285
0.6081
0.8659
1.2358
2.4545
80
0.3610
0.4675
0.6154
0.8133
0.6041
90
0.2138
0.2813
0.3455
0.4374
0.7098
100
0.1756
0.2089
—
—
—
*
( i • 0 • |
NCx denotes nitroalkane of carbon chain
NCI = nitromethane).
length x

177
Reference: Woodburn (1985)
Column: Sepralyte C-2
Mobile Phase: raethanol/water
log k1 at % methanol
Compound
Biphenyl
Napthalene
Phenanthrene
Anthracene
Pyrene
Chrysene
Fluoranthene
n-Butylbenzene
Benzene
Toluene
Ethylbenzene
n-Propylbenzene
p-Xylene
o-Xylene
m-Diethylbenzene
1,2,4-Trimethyl-
benzene
Fluorobenzene
Chlorobenzene
Bromobenzene
Iodobenzene
Nitrobenzene
35
40
1.3971
1.1868
0.9912
0.8276
1.6086
1.3616
1.5789
1.4328
1.9116
1.6294
1.9533
1.9072
1.6205
1.6746
1.4560
0.5335
0.2605
0.6222
0.5206
0.9229
0.7392
1.2816
1.1099
0.9430
0.8265
0.8784
0.7426
1.5479
1.5282
1.2103
1.0558
0.4452
0.5560
0.7064
0.5894
0.7815
0.6582
0.9181
0.7748
0.3026
0.2592
50
60
0.7572
0.1761
0.4657
-0.0595
0.8479
0.2539
0.9054
0.2815
1.0400
0.5753
1.2757
0.5554
1.0295
0.5675
0.9782
0.5865
0.0467
-0.5256
0.2569
-0.1586
0.4715
0.0071
0.7216
0.1984
0.4823
0.0164
0.4526
-0.0264
0.8950
0.5409
0.6570
0.1501
0.1162
-0.2730
0.5025
-0.1330
0.5478
-0.1140
0.4559
-0.0397
0.0169
-0.3736

173
Reference: Woodburn (1935)
Column: Sepralyte C-4
Mobile Phase: methanol
loo; k1 at & methanol
Compound
40
50
60
70
75
Biphenyl
1.1613
0.6889
0.2201
-0.0104
Napthalene
1.2568
0.8609
0.4717
0.0567
-0.1395
Phenanthrene
1.2757
0.7607
0.2562
0.029
Anthracene
1.3223
0.8007
0.2371
0.0398
Pyrene
1.7086
0.9154
0.3701
0.1255
Chrysene
1.7086
1.0714
0.4659
0.1956
n-Butylbenzene
1.4647
0.9423
0.4329
0.1891
n-Hexylbenzene
1.3944
0.7591
0.4574
Benzene
0.6405
0.4108
0.1453
-0.1775
-0.3159
Toluene
0.938
0.6486
0.3209
-0.0334
-0.1963
Ethylbenzene
1.2581
0.8944
0.5119
0.1111
-0.0733
n-Propylbenzene
1.1759
0.7272
0.2717
0.0562
p-Xylene
1.2465
0.8986
0.5108
0.1171
-0.0739
o-Xylene
0.0842
0.4752
0.0931
-0.0836
m-Diethylbenzene
1,2,4-Trimethyl-
1.3808
0.9014
0.3942
0.1537
benzene
1.5123
1.0948
0.6709
0.2376
0.0303
Fluorobenzene
0.7250
0.4684
0.6709
-0.1616
-0.3189
Chlorobenzene
0.9924
0.6852
0.3437
-0.0266
-0.1986
Bromobenzene
1.0677
0.7468
0.3966
0.0090
-0.1733
Iodobenzene
1.2172
0.8445
0.4621
0.0607
-0.1254
Nitrobenzene
0.6050
0.3437
0.0594
-0.2689
-0.4083

179
Reference: Woodburn (1935)
Column: Sepralyte C-8, 5 cm
Mobile Phase: methanol/water
lo°; k' at
% methanol
Compound
50
60
70
80
Anthracene
1.7629
1.1905
0.6736
0.1941
Pyrene
2.0105
1.3866
0.8446
0.3485
Chrysene
—
1.6004
0.9903
0.4377
n-Butylbenzene
1.7929
1.2241
1.7131
0.2177
n-Hexylbenzene
—
1.7403
1.0989
0.4962
Benzene
0.5736
0.2782
-0.0215
-0.3254
Toluene
0.8732
0.5178
0.1678
-0.1839
Ethylbenzene
1.1433
0.7330
0.3323
-0.0730
n-Propylbenzene
1.4672
0.9799
0.5194
0.0714
p-Xylene
1.1634
0.7602
0.3591
-0.0322
o-Xylene
1.1109
0.7087
0.3270
-0.0566
m-Diethylbenzene
1.7098
1.1783
0.6760
0.1952
1,2,4-Trimethyl-
benzene
1.4139
0.9617
0.5201
0.1444
Fluorobenzene
0.6263
0.3049
-0.0125
-0.3444
Chlorobenzene
0.8981
0.5346
0.1678
-0.1892
Broraobenzene
0.9763
0.5903
0.2151
-0.1486
Iodobenzene
1.1008
0.6951
0.2957
-0.0875
Nitrobenzene
0.4821
0.1810
-0.1163
-0.4173

180
Reference: Woodburn (1935)
Column: Sepralyte C-2
Mobile Phase: acetonitrile/water
log k1 at % acetonitrile
Compound
Biphenyl
Napthalene
Phenanthrene
Anthracene
Pyrene
Chrysene
Fluoranthene
n-Butylbenzene
Benzene
Toluene
Ethylbenzene
n-Propylbenzene
p-Xylene
o-Xylene
m-Diethylbenzene
1,2,4-Triraethyl-
benzene
Fluorobenzene
Chlorobenzene
Broraobenzene
Iodobenzene
Nitrobenzene
25
30
1.5805
1.3616
1.2347
1.0705
1.7216
1.4693
1.7826
1.5675
1.9169
1.6252
—
1.8772
1.6431
1.0870
1.7942
1.5516
0.6590
0.6035
0.9252
0.8211
1.1980
1.0569
1.4949
1.3148
1.1754
1.0463
1.1327
1.0042
1.7128
1.4997
1.4034
1.2165
0.7588
0.6782
0.9660
0.8552
1.0315
0.8991
1.1574
1.0129
0.6587
0.5843
40
50
0.9107
0.4245
0.7082
0.2895
0.9716
0.4665
1.0104
0.4346
1.0755
0.5326
1.2435
0.6456
0.5433
1.9350
1.0754
0.5717
0.3890
0.0830
0.5519
0.1966
0.7211
0.3137
0.9042
0.4445
0.7238
0.3067
0.6810
0.2849
1.0353
0.5251
0.8319
0.4124
0.4404
0.1032
0.5865
0.2056
0.6024
0.2264
0.6767
0.2790
0.3561
0.0460

181
Reference: Woodburn (1985)
Column: Sepralyte C-4
Mobile Phase: acetonitrile/water
lop; k1 at % acetonitrile
Compound
Biphenyl
Napthalene
Phenanthrene
Anthracene
Pyrene
Chrysene
Fluoranthrene
n-Butylbenzene
n-Hexylbenzene
Benzene
Toluene
Ethylbenzene
n-Propylbenzene
p-Xylene
o-Xylene
m-Diethylbenzene
1,2,4-Triraethyl-
benzene
Fluorobenzene
Chlorobenzene
Broraobenzene
Iodobenzene
Nitrobenzene
30
40
1.5463
1.0381
1.2330
0.8206
1.6648
1.0980
1.7007
1.1354
1.8270
1.2077
2.0831
1.3748
1.8203
1.2151
1.8148
1.2576
—
1.6561
0.7452
0.4861
0.9803
0.6719
1.2399
0.8631
1.5225
1.0694
1.2344
0.8413
1.1921
0.8101
1.7286
1.2216
1.4300
1.2216
0.8103
0.5271
1.0022
0.6751
1.0732
0.7199
1.1845
0.7995
0.6840
0.4229
50
60
0.6572
0.3197
0.4993
0.2059
0.6953
0.3801
0.7255
0.3714
0.7798
0.4130
0.8934
0.4936
0.7818
0.4122
0.7818
0.4122
1.1506
0.7244
0.2643
0.0347
0.3996
0.1412
0.5423
0.2510
0.6896
0.3714
0.5336
0.2453
0.5056
0.2231
0.8135
0.4785
0.6401
0.3404
0.2367
0.0476
0.4003
0.1339
0.4334
0.1597
0.4929
0.2121
0.1919
-0.0291

Reference: Woodburn (1985)
Column: Sepralyte C-8
Mobile Phase: acetonitrile
Compound
30
40
Biphenyl
1.8791
1.3100
Napthalene
1.5346
1.0692
Phenanthrene
1.4679
Anthracene
1.4878
Pyrene
1.6562
Chrysene
1.8531
Fluoranthrene
1.6384
n-Butylbenzene
1.5767
n-Hexylbenzene
2.0444
Benzene
0.6637
0.4213
Toluene
0.8929
0.5896
Ethylbenzene
1.5186
1.1057
n-Propylbenzene
1.8364
1.3437
p-Xylene
1.5235
1.0932
o-Xylene
1.4667
1.0695
m-Diethylbenzene
2.0636
1.5178
1,2,4-Trimethyl-
benzene
1.7523
1.2679
Fluorobenzene
1.0245
0.7037
Chlorobenzene
1.2773
0.9011
Broraobenzene
1.3471
0.9518
Iodobenzene
1.4961
1.0642
Nitrobenzene
0.9093
0.6066
log k* at % acetonitrile
50
So
65
80
0.8969
0.4778
0.3277
-0.0375
0.7220
0.3510
0.2169
-0.1091
1.0000
0.5769
0.4229
0.0361
1.0400
0.6040
0.4483
0.0497
1.1580
0.7193
0.5604
0.1646
1.2986
0.8193
0.6443
0.2006
1.1402
0.6882
0.5265
0.1210
1.1105
0.6716
0.5092
0.1177
1.4855
0.9692
0.7819
0.3242
0.1172
0.0121
-0.2418
0.9515
0.2413
0.1325
-0.1555
1.2307
0.7544
0.3784
0.2446
-0.0809
0.9386
0.5222
0.3766
0.0167
0.7457
0.3809
0.2525
-0.0719
0.7154
0.3582
0.2279
-0.0971
1.0768
0.6434
0.4865
0.0918
0.8851
0.4925
0.3565
0.0112
0.4439
0.1249
0.0121
-0.2406
0.5891
0.2534
0.1325
-0.1484
0.6410
0.2886
0.1699
-0.1272
0.7205
0.3582
0.2315
-0.1000
0.3447
0.0352
-0.0659
-0.3156
182

183
Reference: Woodburn (1935)
Column: Sepralyte C-18
Mobile Phase: acetonitrile/water
l0£ k.’ at %
acetonitrile
Compound
50
55
60
70
Biphenyl
1.0927
0.9084
0.7525
0.4691
Napthalene
0.8931
0.7295
0.5935
0.3383
Phenanthrene
1.2411
1.0467
0.8804
0.5906
Anthracene
1.2903
1.0922
0.9276
0.6283
Pyrene
1.4429
1.2395
1.0708
0.7673
Chrysene
1.6263
1.3996
1.2128
0.8803
n-Butylbenzene
1.3610
1.1659
0.9991
0.6933
n-Hexylbenzene
1.8049
1.5739
1.3778
1.0242
Benzene
0.5283
0.4124
0.3061
0.0965
Toluene
0.7362
0.5918
0.4703
0.2449
Ethylbenzene
0.9278
0.7655
0.6279
0.3746
n-Propylbenzene
1.1479
0.9661
0.8136
0.5349
p-Xylene
0.9407
0.7826
0.6410
0.3930
o-Xylene
0.8971
0.7428
0.6038
0.3583
m-Diethylbenzene
1.3018
1.1108
0.9479
0.6495
1,2,4,-Trimethyl-
benzene
1.1080
0.9371
0.7860
0.5189
Fluorobenzene
0.5408
0.4113
0.2953
0.0810
Chlorobenzene
Bromobenzene
0.2805
0.5174
0.6481
0.7942
Iodobenzene
0.8980
0.7416
0.6043
0.3583
Nitrobenzene
0.4113
0.2872
0.1746
-0.0347

184
Reference: Jandera (1985)
Column: Silasorb C-8
Mobile Phases: acetonitrile
lo
/water
g k.' at %
acetonitrile
Compound
50
60
70
30
Acetophenone
-0.1249
-0.301
-0.4949
-0.699
Anisóle
0.0792
-0.1249
-0.3979
-0.6021
Benzaldehyde
-0.1135
-0.3098
-0.5376
-0.7696
Benzonitrile
-0.0605
-0.2596
-0.5086
-0.7212
Benzophenone
0.3096
0.0253
-0.2441
-0.5086
Benzotrichloride
0.5999
0.2672
-0.0044
-0.301
Broraobenzene
0.3075
0.0645
-0.2076
-0.4437
n-Butyl bromide
n-Butyl phenyl-
0.3655
0.0934
-0.1611
-0.3979
carbamate
0.2672
-0.0088
-0.2757
-0.5528
Chlorobenzene
0.2788
0.0212
-0.2366
-0.4815
Chlorobromuron
0.2553
-0.0132
-0.284
-0.5376
m-Cresol
-0.3361
-0.699
-0.4202
-0.2291
o-Cresol
-0.2147
-0.4202
-0.6198
-0.8361
p-Cresol
-0.1675
-0.3979
-0.6198
-0.8861
Di-n-butyl ether
0.5647
0.2718
0.0044
-0.2291
Ether benzoate
0.2989
0.0607
-0.2218
-0.4635
n-Heptane
1.0141
0.6749
0.3856
0.0792
Linuron
0.2253
-0.041
-0.3098
-0.5686
Methyl benzoate
0.0414
-0.1487
-0.3872
-0.6193
Nitrobenzene
0.0212
-0.2007
-0.4437
-0.6576
n-Octane
1.2095
0.8331
0.5172
0.1987
Phenetole
0.1847
-0.0044
-0.3188
-0.5036
Phenol
-0.3279
-0.5528
-0.699
-1.0969
Phenyl acetate
n-Propyl phenyl
-0.1135
-0.284
-0.5086
-0.7212
ether
0.3284
0.0828
-0.1871
-0.4559
Styrene
0.3032
0.0374
-0.2366
-0.4685

185
Reference: Jandera (1985)
Column: Silasorb C8
Mobile Phase: methanol/water
los k' at
t methanol
Compound
60
70
80
90
Acetophenone
-0.2076
-0.4949
-0.7447
-1.000
Anisóle
-0.0223
-0.301
-0.585
-0.9208
Benzaldehyde
-0.234
-0.5229
-0.7959
-1.1549
Benzonitrile
-0.2518
-0.5376
-0.7959
-1.0969
Benzophenone
0.2625
-0.1192
-0.4685
-0.8239
Benzotrichloride
0.6123
0.1614
-0.2366
-0.6383
Broraobenzene
0.281
-0.0655
-0.4089
-0.7696
n-Butyl bromide
n-Butyl phenyl-
0.2833
-0.0555
-0.3372
-0.7696
carbamate
0.1732
-0.1938
-0.6021
-1.000
Chlorobenzene
0.2175
-0.1135
-0.4437
-0.7959
Chlorobromuron
0.248
-0.1367
-0.4315
-0.9208
m-Cresol
-0.2291
-0.4202
-0.699
-0.8861
o-Cresol
-0.3279
-0.6198
-0.8861
-1.301
p-Cresol
-0.1675
-0.3979
-0.6198
-0.3861
Di-n-butyl ether
0.5514
0.1239
-0.2366
-0.6193
Ethyl benzoate
0.2695
-0.1024
-0.4559
-0.7959
n-Heptane
1.1424
0.6405
0.1523
-0.3468
Linuron
0.2095
-0.1805
-0.5376
-0.8861
Methyl benzoate
0.0086
-0.3188
-0.6198
-0.9208
Nitrobenzene
-0.1249
-0.3979
-0.6773
-1.0458
Phenetole
0.1461
-0.2007
-0.4815
-0.8239
Phenol
-0.5376
-0.7212
-1.000
-1.5229
Phenyl acetate
n-Propyl phenyl
-0.2147
-0.4949
-0.7447
-1.000
ether
0.2695
-0.0862
-0.4318
-0.7959
Styrene
0.2601
-0.0862
-0.4202
-0.7696

Reference: Hanai and Hubert (1983)
Column: Unisil Q C18
Mobile Phase: Acetonitrile/water
log k* at % acetonitrile
Compound
90
80
70
60
50
40
30
20
10
Phenol
-0.052
-0.006
0.082
0.168
0.304
0.481
0.695
0.951
1.293
2-Methylphenol
0
0.064
0.184
0.298
0.481
0.704
0.985
1.327
—
3-Methylphenol
-0.018
0.047
0.156
0.263
0.441
0.661
0.935
1.291
—
4-Methylphenol
-0.117
0.052
0.160
0.266
0.440
0.662
0.936
1.292
1.729
2,3-Dimethylphenol
0.039
0.133
0.260
0.400
0.610
0.877
1.216
—
—
2,4-Dimethylphenol
0.044
0.176
0.268
0.413
0.624
0.893
1.236
—
—
2,5-Dimethylphenol
0.039
0.129
0.263
0.409
0.613
0.890
1.232
—
—
2,6-Dimethylphenol
0.059
0.158
0.297
0.442
0.646
0.923
1.249
—
—
3,4-Dimethylphenol
0.017
0.103
0.213
0.350
0.537
0.806
1.135
1.567
—
3.5-Dimethylphenol
2.3.5-Trimethyl-
0.023
0.114
0.230
0.372
0.570
0.845
1.184
1.621
—
phenol
2,3,6-Trimethy1-
0.084
0.199
0.349
0.520
0.751
1.071
1.468
—
—
phenol
2,4,6-Trimethyl-
0.107
0.229
0.386
0.558
0.789
1.105
1.484
—
—
phenol
2,3,5,6-Tetra-
0.116
0.240
0.400
0.574
0.807
1.126
1.515
—
—
methylphenol
0.211
0.358
0.534
0.704
0.935
1.244
—
—
—
2-Ethylphenol
0.028
0.121
0.244
0.387
0.587
0.870
1.221
1.675
—
3-Ethylphenol
0.023
0.109
0.234
0.331
0.581
0.861
1.208
1.648
—
4-Ethylphenol
0.031
0.116
1.244
0.384
0.587
0.870
1.221
1 .665
—
2-Chlorophenol
-0.003
0.067
0.172
0.302
0.430
0.724
1.021
1.397
—
3-Chlorophenol
0
0.089
0.209
0.349
0.538
0.809
1.146
1 .553
—
4-Chlorophenol
0.003
0.072
0.191
0.332
0.514
0.776
1.110
1.530
—
2,3-Dichlorophenol
0.047
0.144
0.280
0.448
0.670
0.968
1.393
—
—
2,4-Dichlorophenol
0.074
0.173
0.329
0.500
0.727
1.049
1.467
—
—
186

Reference: Hanai and Hubert (1983)—continued.
Column: Unisil Q C18
Mobile Phase: Acetonitrile/water
log k1 at
Compound
90
80
70
60
2,5-Dichlorophenol
0.054
0.162
0.310
0.488
2,6-Dichlorophenol
0.057
0.162
0.302
0.467
3,4-Dichlorophenol
0.062
0.166
0.318
0.493
3,5-Dichlorophenol
0.109
0.225
0.393
0.585
2,3,4-TrichlorophenolO.131
0.247
0.423
0.617
2,3,5-Trichlorophenol0.093
0.197
0.351
0.526
2,3,6-TrichlorophenolO.131
0.258
0.432
0.626
2,4,5-TrichlorophenolO.146
0.282
0.463
0.671
2,4,6-TrichlorophenolO.174
0.314
0.495
0.696
3,4,5-TrichlorophenolO.162
0.301
0.488
0.698
2,3,4,5-Tetra-
chlorophenol
0.229
0.390
0.603
0.835
2,3,5,6-Tetra-
chlorophenol
0.249
0.410
0.621
0.850
Pentachlorophenol
0.340
0.531
0.766
1.020
2-Chloro-5-methy1-
phenol
0.039
0.131
0.263
0.425
4-Chloro-2-methyl-
phenol
0.067
0.1660
.312
0.481
4-Chloro-3-methyl-
phenol
0.052
0.147
0.279
0.442
2-Bromophenol
0.011
0.091
0.202
0.34
3-Bromophenol
0.025
0.114
0.234
0.386
4-Bromophenol
0.023
0.105
0.224
0.370
2,4-Dibromophenol
0.112
0.227
0.389
0.575
2,6-Dibromophenol
0.109
0.227
0.383
0.560
% acetonitrile
50
40
30
20
10
0.724
1.046
1.453
0.684
0.975
1.336
—
—
0.731
1.061
1.497
—
—
0.841
1.193
1.644
—
—
0.891
1.268
—
—
—
0.755
1.068
1.466
—
—
0.893
1.247
—
—
—
0.958
1.340
—
—
—
0.971
1.331
—
—
—
0.990
1.388
—
—
—
1.158
1.595
—
—
—
1.165
1.584
1.366
—
—
—
—
0.638
0.925
1.290
—
—
0.712
1.026
1.427
—
—
0.660
0.962
1.355
0.531
0.781
1.104
1.504
—
0.592
0.868
1.222
1.664
—
0.567
0.843
1.201
1.647
—
0.835
1.181
1.640
—
—
0.802
1.119
1.515
—
—
187

Reference: Hanai and Hubert (1983)--continued.
Column: Unisil Q C18
Mobile Phase: Acetonitrile/water
log k1 at % acetonitrile
Compound
2-Nitrophenol
3-Nitrophenol
4-Nitrophenol
2.4-Dinitrophenol
2.5-Dinitrophenol
2.6-Dinitrophenol
3,4-Dinitrophenol
2-Hydroxyaceto-
phenone
4-tert-Butylphenol
4-Hydroxypropyl
benzoate
4-Hydroxybutyl
benzoate
4-Chloro-3,5-
dimethylphenol
1.3-Dihydroxy-
benzene
1,2-Dihydroxy-
benzene
1.4-Dihydroxy-
benzene
2-Hydroxy-
naphthalene
1-Hydroxy-
naphthalene
1-Hydroxy-2,4-
dinitronaphtalene
90
80
70
60
50
40
30
20
10
0.047
-0.059
-0.072
-0.046
-0.042
-0.042
-0.069
0.144
0.009
-0.012
0.047
0.054
0.052
-0.012
0.266
0.105
0.072
0.156
0.174
0.170
0.096
0.412
0.224
0.191
0.302
0.332
0.322
0.247
0.601
0.391
0.351
0.504
0.542
0.525
0.464
0.843
0.618
0.579
0.762
0.814
0.779
0.763
1.136
0.906
0.860
1.081
1.134
1.067
1.153
1.462
1.266
1.210
1.444
1.435
1.368
1.622
1.635
-0.033
0.105
0
0.232
0.033
0.392
0.98
0.585
0.195
0.851
0.332
1.214
0.518
0.792
1.232
0.023
0.112
0.235
0.390
0.611
0.924
1.350
—
—
0.074
0.187
0.344
0.532
0.801
1.171
1.679
—
—
0.107
0.218
0.378
0.559
0.808
1.153
1.608
—
—
-0.155
-0.135
-0.100
-0.055
0.025
0.129
0.256
0.441
0.748
-0.112
-0.086
-0.049
0.020
0.103
0.222
0.375
0.591
0.904
-0.042
-0.155
-0.104
-0.094
-0.040
0.054
0.158
0.277
0.481
0.023
0.116
0.234
0.389
0.603
0.905
1.294
—
—
0.044
0.140
0.276
0.443
0.669
0.986
1.389
—
—
0.121
0.265
0.450
0.653
0.946
1.314
—
—
188

Reference: Hanai and Hubert (1983)
Column: Hypersil ODS
Mobile Phase: Acetonitrile/water
Compound
80
70
4-Nitrophenol
-0.221
-0.153
2,4-Dinitrophenol
-0.158
-0.089
3-Bromophenol
-0.082
-0.021
4-Chloro-3-methy1phenol
-0.065
0.016
2,5-Dichlorophenol
4-Chloro-3,5-dimethyl-
-0.051
0.048
phenol
0.025
0.105
2.4.5-Trichlorophenol
2.3.4.5-Tetrachloro-
0.080
0.176
phenol
0.179
0.296
log k1
60
0.002
0.119
0.188
0.242
0.292
0.360
0.470
0.630
at % acetonitrile
50
40
0.160
0.373
0.313
0.570
0.385
0.659
0.454
0.752
0.525
0.842
0.402
0.943
0.746
1.131
0.943
1.387
30
20
0.667
1.006
0.900
1.255
1.025
1.470
1.156
—
1.256
—
1.401
—
189

Reference: Hanai and Hubert (1985)
Column: Hypersil ODS
Compound
70
60
Aniline
0.53
0.67
N-Methylaniline
0.87
1.23
N-Ethylaniline
1.15
1.71
N-Butylaniline
2.15
3.75
N,N-Dimethylaniline
1.50
2.26
N ,N-Diethylaniline
2.71
4.71
2-Methylani1ine
0.67
0.89
3-Methylani1ine
0.70
0.87
4-Methylaniline
0.67
0.87
2,4-Dimethylani1ine
0.86
1.18
4-Methoxyaniline
0.44
0.49
2,4-Diethoxyaniline
0.92
1.32
2-Chloroani1ine
0.84
1.18
3-Chloroani1ine
0.76
1.06
4-Chloroaniline
0.74
1.01
2,5-Dichloroaniline
1.25
1.94
3,4-Dichloroani1ine
1.01
1.52
4-Broraoaniline
0.80
1.13
2-Nitroaniline
0.67
0.91
3-Nitroani1ine
0.58
0.77
4-Nitroaniline
0.48
0.64
Pyridine
0.61
0.64
2-Aminopyridine
0.28
0.22
3-Aminopyridine
0.32
0.31
4-Aminopyridine
—
—
k' at % acetonitrile
50
0.91
1.91
2.90
7.72
5.89
9.71
1.31
1.30
1.27
1.86
0.69
2.22
1.90
1.73
1.60
3.57
2.72
1.83
1.41
1.22
0.99
0.77
0.24
0.35
40
1.35
3.29
5.46
19.06
7.63
24.13
2.09
2.12
2.07
3.25
0.99
4.24
3.41
3.15
2.84
7.67
5.69
3.40
2.56
2.10
1.69
1.01
0.28
0.44
30
2.09
6.04
11.22
16.29
3.67
3.85
3.77
6.61
1.59
9.61
6.76
6.50
5.82
19.52
14.55
7.29
5.09
3.98
3.17
1.46
0.38
0.61
20
3.51
11.74
24.56
7.25
7.82
7.69
15.79
2.95
27.19
14.32
14.79
13.33
17.82
11.22
8.07
6.53
2.45
0.59
1.02
10
6.98
16.96
18.79
18.79
7.06
27.94
17.54
14.80
5.64
1.28
2.40
190

Reference: Hanai and
Column: Hypersil ODS
Compound
2-Methylpyridine
3-Methylpyridine
4-Methylpyridine
4-Ethylpyridine
4-tert-Butylpyridine
2.4-Dimethylpyridine
2.5-Dimethylpyridine
2.6-Diraethylpyridine
Pyrazine
2-Methylpyrazine
2.5-Dimethylpyrazine
2.6-Dimethylpyrazine
Quinoline
8-Hydroxyquinoline
2-Methylquinoline
4-Methylquinoline
8-Methy1quino1ine
5-Aminoindan
1-Aminoindan
5-Aminoindole
1-Aminonaphthalene
2-Aminonaphthalene
1-Aminoanthracene
1-Aminopyrene
Hubert (1985)
70
60
0.78
0.88
0.86
0.98
0.86
0.99
1.12
1.40
1.70
2.41
1.06
1.42
1.03
1.29
0.94
1.09
0.36
0.32
0.44
0.41
0.53
0.52
0.52
0.52
0.93
1.14
1.07
1.40
1.26
1.63
1.29
1.75
0.95
1.31
0.36
0.38
0.86
1.24
0.85
1.21
1.54
2.53
2.01
3.41
k' at % acetonitrile
50
1.11
1.31
1.28
1 .98
3.80
1.92
1.76
1.49
0.34
0.45
0.60
0.52
1.64
2.09
2.47
2.73
2.11
0.54
2.09
2.05
5.05
7.11
40
1.57
1.84
1.84
3.15
7.17
3.01
2.75
2.27
0.38
0.53
0.74
0.72
2.68
3.65
4.39
4.92
3.86
0.78
3.99
3.93
15.52
18.96
30
2.55
3.17
3.04
6.04
17.95
5.73
5.08
4.05
0.48
0.73
1.06
1.03
5.40
8.02
9.94
11.17
8.46
1.26
9.06
9.36
42.18
20
5.05
6.34
6.33
15.44
12.29
9.30
0.69
1.16
1.94
1.86
14.53
24.26
24.36
32.10
22.16
2.32
24.43
26.14
10
15.77
18.92
19.40
34.48
1.29
2.75
5.86
5.51
5.34
191

192
Methylene Selectivity Data
Reference: This Work
Column: Ultrasphere ODS
Mobile Phase: methanol/water
SÉMeOH
lo£ aCH2
E^(30) interpolated
48.9
0.2993
58.40
60
0.4011
57.59
70.7
0.5157
56.80
75
0.5725
56.67
80
0.6410
56.41
Reference: This Work
Column: Ultrasphere CDS
Mobile Phase: acetonitril
e/water
£ACN
log. °CH2
Erp(30) interpolated
32
0.3348
58.81
35
0.3126
58.06
46
0.2422
56.99
50
0.2311
56.80
63
0.1867
55.89
68
0.1678
55.63
Reference
: This Work
Column:
Hamilton PRP-1
%ACN
l0£ aCH2
0
0.8442
10
0.5679
20
0.4539
30
0.3643
40
0.2983
50
0.2268
60
0.1823
70
0.1513
80
0.1191
90
0.1029
100
0.0754

193
#MeOH 1°JLÜCH2
0
0.8250
10
0.7812
20
0.6916
30
0.6167
40
0.5394
50
0.4610
60
0.3824
70
0.3127
80
0.2241
90
0.1538
100
0.0850
Reference
: Karger et al.
(1976)
Column:
Ultrasphere ODS
SÍACN
log aru?
Erp(30)
interpol
10
0.5046
20
0.4299
30
0.3177
40
0.2504
50
0.2056
60
—
70
—
80
0.1159
*MeOH
0
0.5415
5.2
0.5223
62.60
7.5
0.5185
63.37
12.7
0.5031
61.85
21.5
0.4685
60.97
29.7
0.4225
60.16
38.3
0.3495
59.35
49.5
0.2957
58.36
54.5
0.2804
57.94
64.9
0.2228
57.18
75.1
0.1651
56.56
88.2
0.1152
55.98
100
0.0691
55.73
^Interpolated for compositions not measured by
3rd degree polynomial fit of E-p(30) versus percent
modifier.
using a
organic

194
Reference: Petrovic et al. (1985)
ÍMeOH
los; a (alkylbenzenes)
log a (alkanes)
40
0.4702
_ _ __
50
0.3989
0.2921
60
0.3189
0.2432
70
0.2504
0.1944
80
0.1924
0.1422
90
0.1444
0.0897
100
0.0773
0.0377
Reference:
Hanai and Hubert (1985)
$ACN
log a
20
0.3206
30
0.2639
40
0.2568
50
0.2037
60
0.1627
70
0.1317
Reference:
Dufek et al. (1984)
¡¿Me OH
log a
55
0.2597
60
0.2323
65
0.2071
70
0.1792
75
0.1556
80
0.1281
85
0.1018
90
0.0792
95
0.0548
100
0.0373

195
Reference: Colin et al. (1983)
$MEOH
log a
0
10
20
30
40
50
60
70
80
90
100
0.0957
0.1457
0.1929
0.2433
0.2991
0.3600
0.4192
0.4722
0.5180
0.5619
0.5716
$ACN
l0£ a
0
10
20
30
40
50
60
70
80
90
100
0.1101
0.1354
0.1581
0.1780
0.1989
0.2293
0.2863
0.3653
0.4499
0.5460
0.5716

APPENDIX B
MODIFICATION OF CURVE FITTER PROGRAM
TO ALLOW CALCULATION OF CONFIDENCE INTERVALS
The following lines were added to the program "Curve
Fitter" in order to obtain confidence intervals for the
linear regression coefficients reported in this
dissertation. The additional lines comprise a short
subroutine which is entered at line 1465:
1465 GOSUB 4010
The subroutine is as follows:
4010 XB=C/NS
4020 Z3=T/NS
4030 SX=SQR(U-NS*XB*XB))
4040 Z5=SQR(V-(NS*Z3*Z3))
4050 Z4=W-(NS*XB*Z3)
4070 SS=Z5*Z5-(B*B*SX*SX)
4080 SS=SQR(SS/(NS-2))
4100 T5=3:T9=3.8
4200 B9=T9*(SS/SX)
4210 B5=T5*(SS/SX)
4220 A9=T9*S3*SQR((1/NS)+XB*XB)/(3X*SX)
4229 PR#3
4230 A5=T5*SS*SQR((1/NS)+(XB*XB)/(SX*SX))
4240 PRINT"SLOPE=";B;" +- ";B9;" / ";A5
4250 PRINT"Y-INT=";A;" +- ";A9;" / ";A5
4260 RETURN
The user must change line 4100, which contains the t-
statistic values for the 90# (variable T5) and 95#
(variable T4) levels of confidence.
196

APPENDIX C
MODIFICATION OF CURVE FITTER PROGRAM TO
INTERPOLATE SPECTRAL PEAK POSITIONS
By adding only a few lines to the program "Curve
Fitter," it is possible to automatically calculate the
interpolated position of the spectral peak of interest.
These additional lines were written with the assumption
that the absorbance data (absorbance versus wavelength)
have been fit with a three degree polynomial.
The first additional line follows line 1680, where the
coefficients were printed out:
1681 A=3*C(4) : B=2*C(3) : C=C(2)
Line 1681 is used to calculate the derivative of the
polynomial, which yields the three coefficients, A, B, and
C. Next, the quadratic equation is solved for these three
coefficients; this is equivalent to setting the derivative
equal to zero and solving for the roots:
1682 X1= (-B + SQR (B*B - 4*A*C))/2*A
1683 X2= (-B - SQR (B*B - 4*A*C))/2*A
Finally, the two roots are printed out:
1684 PRINT: PRINT: PRINT "MAXIMUM IS AT ";X1;" OR
";X2;" : PRINT
197

APPENDIX D
SOLVATOCHROMIC SOLVENT POLARITY MEASUREMENTS
£íj(30) polarity of binary and ternary mixtures of
water/methanol/acetonitrile.
HoO/MeOH/ACN ET(5Q) POLARITY (kcal/mole)
0/100/0
55.63
0/90/10
53.20
0/20/80
54.33
0/30/70
54.88
0/40/60
55.26
0/50/50
55.57
0/60/40
55.62
0/70/30
55.65
0/80/20
55.84
0/90/10
55.75
10/0/90
53.80
10/10/80
54.73
10/20/70
55.00
10/30/60
55.49
10/40/50
55.69
10/50/40
55.84
10/60/30
55.82
80/20/0
60.94
90/0/10
61.43
90/10/0
62.15
80/10/0
60.34
10/70/20
55.95
10/80/10
55.89
10/90/0
55.89
20/0/80
55.09
20/10/70
55.41
20/20/60
55.71
20/30/50
55.99
20/40/40
56.10
20/50/30
56.24
20/60/20
56.32
20/70/10
56.50
20/80/0
56.37
30/0/70
55.71
198

199
HoO/MeOH/ACN
Et(30) POLARITY (kcal/mole)
30/10/60
30/20/50
30/30/40
30/60/10
30/40/30
30/70/0
30/50/20
40/0/60
40/10/50
40/20/40
40/30/30
40/40/20
40/50/10
40/60/0
50/0/50
50/10/40
50/20/30
50/30/20
50/40/10
50/50/0
60/0/40
60/10/30
60/20/20
60/30/10
60/40/0
70/0/30
70/10/20
70/20/10
70/30/0
80/0/20
100/0/0
0/0/100
56.02
56.16
56.46
56.93
56.64
56.84
56.75
56.19
56.48
56.80
56.91
57.32
57.41
57.46
56.82
57.25
57.41
57.90
57.97
58.30
57.46
58.04
58.21
58.59
59.17
58.44
58.85
59.44
59.73
59.81
63.12
45.97
E,-p(30) polarity of binary tetrahydrofuran/water mixtures
%THF
Et(30) POLARITY (kcal/mole)
10
15
20
30
40
50
60
70
80
90
95
100
60.97
59.72
58.54
55.54
53.83
52.62
51.64
50.86
49.61
47.91
45.89
39.14

200
tt* , a, and g values for raethanol/water
acetonitrile/water mixtures.
$MeOH
TT*
a
g
0
1.081
1.067
0.470
10
1 .085
1.010
0.454
20
1 .047
0.969
0.500
30
1 .028
0.948
0.521
40
0.999
0.903
0.521
50
0.948
0.891
0.549
60
0.900
0.877
0.570
70
0.834
0.889
0.598
80
0.756
0.917
0.626
90
0.667
0.953
0.647
100
0.566
1.015
0.852
¡¿ACN
TT*
a
6
0
1.081
1.067
0.470
10
1.066
0.985
0.464
20
1.035
0.914
0.474
30
0.984
0.873
0.498
40
0.932
0.855
0.533
50
0.876
0.858
0.563
60
0.837
0.850
0.572
70
0.834
0.826
0.556
80
0.771
0.835
0.583
90
0.727
0.794
0.566
100
0.665
0.398
0.370
HoO/MeOH/ACN
TT*
50/10/40
0.908
50/20/30
0.924
50/30/20
0.938
50/40/10
0.950
60/10/30
0.955
60/20/20
0.974
60/30/10
0.968
70/10/20
0.980
70/20/10
1.009
90/10/10
1.041
33.3/33.3/33.4
0.857
S £
0.860
0.540
0.858
0.536
0.885
0.543
0.371
0.534
0.871
0.527
0.867
0.514
0.724
0.530
0.899
0.523
0.912
0.503
0.940
0.483
and

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BIOGRAPHICAL SKETCH
Bruce Philip Johnson was born in Detroit, Michigan, on
February 21, 1958 (at 3:37 AM, New Grace Hospital). He
attended public schools in Dearborn, Michigan, through the
eleventh grade, at which time his father retired (1975),
and his family moved to Tustin, Michigan. He graduated
from Pine River High School (Leroy, MI) in June, 1976 and
entered Central Michigan University (Mount Pleasant, MI) in
August of that year. While attending CMU he worked part-
time as a co-op student at the Dow Chemical Company
(Midland, MI). In December of 1980 he received a B.S.
degree in chemistry from CMU and entered graduate school at
the University of Florida in January, 1981. He was awarded
a three-year graduate fellowship from the Eastman Kodak
Company in May, 1982. He was married to his wife, Bonnie,
in December, 1982. Their son, Garrett Chase, was born on
April 22, 1986 (1:08 PM EST; The Birth Center, Gainesville,
FL). Upon completion of the requirements of the degree of
Doctor of Philosophy (August, 1986), he accepted a position
with the Eastman Chemicals Division of the Eastman Kodak
Company (Kingsport, TN).
212

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
A .
Anna FT Bra j tr/er-Toth
Assistant Professor of Chemistry
I certify that
opinion it conforms
presentation and is
as a dissertation f
I have read this study and that in my
to acceptable standards of scholarly
fully adequate, in scope and quality,
or the degree of Doctor of Philosophy.
Chr'istopneT yRiley
Assistant Professor of Pharmacy
I certify that
opinion it conforms
presentation and is
as a dissertation fo
I have read this study and that in my
to acceptable standards of scholarly
fully adequate, in scope and quality,
of Chemistry

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
Vaneica Y.
Assistan t
Yojün g
Profes
try
This dissertation was submitted to the Graduate Faculty of
the Department of Chemistry in the College of Liberal Arts
and Sciences and to the Graduate School and was accepted as
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August 1986
Dean, Graduate School

UNIVERSITY OF FLORIDA
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