<%BANNER%>

Dissolution and Surface Proximity Effects of Low Energy, Amorphizing Germanium Implants into Silicon

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DISSOLUTION AND SURFACE PROXIMITY EFFECTS OF LOW ENERGY, AMORPHIZING GERMANIUM IMPLANTS INTO SILICON By ANDREW C. KING A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2003

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Copyright 2003 by Andrew C. King

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For Mom, Dad and Devin

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iv ACKNOWLEDGMENTS I would first like to thank my advisor, Dr. Kevin Jones, for his guidance, patience, commitment to science, and sense of humor. I would also like to thank Dr. Mark Law for answering all of my questions and giving me excellent suggestions throughout my research. Appreciation is also given to Dr. David Norton for support on my committee. I am sincerely grateful to Mark Clark, Tony Saavedra, Andres Gutierrez, Russ Robison, Ljubo Radic, and Carrie Ross for taking time to help me. Without their help I would not have been able to complete this work. Finally, I would like to thank everybody in the SWAMP Group for their friendship and support. The Semiconductor Research Corporation supported this work.

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v TABLE OF CONTENTS Page ACKNOWLEDGMENTS..............................................................................................iv LIST OF TABLES........................................................................................................vii LIST OF FIGURES......................................................................................................viii ABSTRACT..................................................................................................................xi CHAPTER 1INTRODUCTION....................................................................................................1 1.1 Background and Motivation...............................................................................1 1.2 Ion Implantation................................................................................................4 1.3 Solid Phase Epitaxy............................................................................................8 1.4 End-of-Range Damage.......................................................................................9 1.4.1 Defect Evolution.....................................................................................10 1.4.2 Transient Enhanced Diffusion.................................................................12 1.5 Effect of the Free Surface on End-of-Range Damage........................................14 1.6 Scope and Approach of this Study....................................................................16 2EXPERIMENTAL AND DATA EXTRACTION PROCEDURES.........................18 2.1 Transmission Electron Microscopy...................................................................18 2.1.1 Plan-view Transmission Electron Microscopy Sample Preparation.........19 2.1.2 Cross-Section Transmission Electron Microscopy Sample Preparation...20 2.1.3 Extraction of Defect Parameters from PTEM..........................................22 2.1.3.1 Extraction of defect densities from PTEM.....................................22 2.1.3.2 Extraction of trapped interstitial concentrations from PTEM.........23 2.2 Variable Angle Spectroscopic Ellipsometry......................................................24 2.3 UT – Marlowe..................................................................................................25 2.4 5 keV Ge+ Defect Dissolution Study.................................................................26 2.4.1 5 keV Defect Dissolution Activation Energy Experiment........................27 2.4.2 Surface Lapping Experiment...................................................................28 2.6 Surface Proximity Experiment..........................................................................29 2.7 Ellipsometry Experiment..................................................................................30

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vi 35 keV Ge+ DEFECT DISSOLUTION STUDY.......................................................31 3.1 Overview..........................................................................................................31 3.2 Defect Dissolution Activation Energy...............................................................32 3.2.1 TEM Results...........................................................................................32 3.2.2 Extraction of Defect Dissolution Activation Energy................................34 3.3 Surface Lapping Experiment............................................................................35 3.3.1 Amorphous Layer Lapping Results.........................................................35 3.3.2 Defect Evolution.....................................................................................36 3.4 UT-Marlowe Simulations.................................................................................36 3.4.1 Simulation Results..................................................................................37 3.4.2 NEI calculation.......................................................................................37 3.5 Discussion........................................................................................................38 3.6 Conclusion.......................................................................................................39 4SURFACE PROXIMITY EXPERIMENT..............................................................60 4.1 Overview..........................................................................................................60 4.2 Experimental Results........................................................................................60 4.3 Discussion........................................................................................................62 4.4 Conclusion.......................................................................................................63 5LOW TEMPERATURE ANNEAL EFFECT ON ELLIPSOMETRY ACCURACY FOR SHALLOW AMORPHOUS SILICON LAYERS..........................................75 5.1 Overview..........................................................................................................75 5.2 Experimental Results........................................................................................75 5.3 Conclusion.......................................................................................................76 6CONCLUSIONS AND FUTURE WORK..............................................................83 6.1 5 keV Ge+ Defect Dissolution Study.................................................................83 6.2 Surface Proximity Experiment..........................................................................84 6.3 Low Temperature Anneal Effect on Ellipsometry Accuracy for Shallow Amorphous Silicon Layers...................................................................................85 6.4 Implications of Findings...................................................................................85 LIST OF REFERENCES..............................................................................................87 BIOGRAPHICAL SKETCH.........................................................................................91

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vii LIST OF TABLES Table page 1.12002 ITRS doping technology requirements ..........................................................4 3.1 Time range where defect dissolution occurs at each annealing temperature as observed by PTEM...............................................................................................33 3.2 Ellipsometry measurements of amorphous layer thickness for the 5, 10, and 10 keV lapped specimens..........................................................................................36

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viii LIST OF FIGURES Figure page 1.1Cross-sectional schematic of a MOSFET................................................................3 1.2 EOR damage created from an amorphizing implant .............................................10 1.3 Defect evolution of excess interstitials resulting from ion implantation into silicon and subsequent annealing ....................................................................................11 1.4 Defect evolution reported by Gutierrez for Ge+ implanted at energies of 5, 10, and 30 keV at a constant dose of 1015 cm-2 annealed at 750 C....................................13 3.2 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 725 C for (a)15 min, (b) 60 min, (c) 65 min, (d) 70 min, and (e) 80 min........................................40 3.2 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 750 C for (a) 5 min, (b) 15 min, (c) 45 min, (d) 60 min, and (e) 65 min........................................41 3.3 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 775 C for (a) 15 min, (b) 35 min, (c) 40 min, and (d) 45 min..........................................................42 3.4 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 825 C for (a) 15 min, (b) 30 min, and (c) 35 min............................................................................43 3.5 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 875 C for (a) 5 min, (b) 10 min, and (c) 15 min............................................................................44 3.6 PTEM micrograph of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 775 C for 35 min imaged at the g040 condition..................................................................................45 3.7 Defect density trends for 5 keV, 1x 1015 Ge+ cm-2 implant over time annealed at 725, 750, 775, 825, and 875 C.............................................................................46 3.8 Trapped interstitial trends for 5 keV, 1x 1015 Ge+ cm-2 implant over time annealed at 725, 750, 775, 825, and 875 C.........................................................................47 3.9 Average defect diameter over time for the 5 keV, 1 x 1015 Ge+ cm-2 implant annealed at 725, 750, 775, 825, and 875 C..........................................................48

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ix 3.10 Defect dissolution rates versus inverse temperature, plotted in Arrhenius form. The trend is show as a least square exponential curve fit..............................................49 3.11 High-resolution cross section TEM micrographs of the amorphous layer thickness for (a) 10 keV, (b) 10 keV-lapped, and (c) 5 keV samples.....................................50 3.12 PTEM micrographs of the 10 keV Ge+, 1 x 1015 cm-2 Ge+ control implant annealed at 750 C for (a) 5 min, (b) 15 min, (c) 30 min, (d) 45 min, (e) 60 min, and (f) 360 min.......................................................................................................................51 3.13 PTEM micrographs of the 10 keV Ge+, 1 x 1015 cm-2 Ge+ implant whose amorphous layer was polished to 80 and annealed at 750 C for (a) 5 min, (b) 15 min, (c) 30 min, (d) 45 min, (e) 60 min, and (f) 360 min.........................................................52 3.14 Defect evolution of the 5 keV, 10 keV, and 10 keV-lapped specimens annealed at 750 C..................................................................................................................53 3.15 UT-Marlowe .rbs output for the 5 keV, 1 x 1015 Ge+ cm-2 implant.........................54 3.16 UT-Marlowe simulated interstitial and vacancy profiles for the 5 keV, 1 x 1015 Ge+cm-2 implant.........................................................................................................55 3.17 UT-Marlowe .rbs output for the 10 keV, 1 x 1015 Ge+ cm-2 implant.......................56 3.18 UT-Marlowe simulated interstitial and vacancy profiles for the 5 keV, 1 x 1015 Ge+cm-2 implant.........................................................................................................57 3.19 NEI profile for the 5 and 10 keV, 1 x 1015 Ge+ cm-2 implants................................58 3.20 Trapped interstitial concentrations from 5, 10 and 30 keV, 1 x 1015 cm-2 Ge+implants annealed at 750 C, as reported by Gutierrez..........................................59 4.1 XTEM images of 10 keV 1 x 1015 Ge+ cm-2 specimens whose amorphous layers were lapped to (a) 155 , (b) 125 , and (c) 40 ................................................64 4.2 PTEM micrographs of the 155 specimen at (a) 15 and (b) 45 min, the 125 specimen at (c) 15 and (d) 45 min, and the 40 at (e) 15 min and (f) 45 min upon annealing at 750 C..............................................................................................65 4.3 Defect densities for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.66 4.4 Trapped interstitial concentrations for the 180, 155, 125, 80, and 40 specimens annealed at 750 C................................................................................................67 4.5 Dislocation loop component of the overall defect density for the 180, 155, 125, 80, and 40 specimens annealed at 750 C................................................................68

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x 4.6 {311} defect component of the overall defect density for the 180, 155, 125, 80, and 40 specimens annealed at 750 C......................................................................69 4.7 Dislocation loop component of the overall trapped interstitial concentration for the 180, 155, 125, 80, and 40 specimens annealed at 750 C...................................70 4.8 {311} defect component of the overall trapped interstitial concentration for the 180, 155, 125, 80, and 40 specimens annealed at 750 C..........................................71 4.9 Average dislocation loop diameter for the 180, 155, 125, 80, and 40 specimens annealed at 750 C................................................................................................72 4.10 Average {311} defect length for the 180, 155, 125, 80, and 40 specimens annealed at 750 C................................................................................................73 4.11 Trapped interstitial concentration with respect to amorphous layer depth for the 10 keV Ge+ implant following a 750 C anneal for 15 and 45 min.............................74 5.1 Comparison of amorphous layer depth measurements between ellipsometry and high resolution transmission electron microscopy following a 400 C anneal over time......................................................................................................................78 5.2 Reduction in amorphous/crystalline interface roughness as measured by highresolution transmission electron microscopy following a 400 C anneal...............79 5.3 High-resolution transmission electron microscopy cross section images of 5 keV, 1 x 1015 Ge+ cm-2 implant annealed at 400 C for (a) 0 min, (b) 40 min, and (c) 80 min.......................................................................................................................80 5.4 High-resolution transmission electron microscopy cross section images of 10 keV, 1 x 1015 Ge+ cm-2 implant annealed at 400 C for (a) 0 min, (b) 40 min, and (c) 80 min.......................................................................................................................81 5.5 High-resolution transmission electron microscopy cross section images of 30 keV, 1 x 1015 Ge+ cm-2 implant annealed at 400 C for (a) 0 min and (b) 40 min..............82

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xi Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science DISSOLUTION AND SURFACE PROXIMITY EFFECTS OF LOW ENERGY, AMORPHIZING GERMANIUM IMPLANTS INTO SILICON By Andrew C. King December 2003 Chair: Kevin S. Jones Major Department: Materials Science and Engineering As CMOS device dimensions are scaled laterally to increase the density of transistors per die, they also must be scaled vertically. Thus, it becomes increasingly important to understand the interactions of the silicon surface with point defects. Preamorphization is a common method for preventing channeling of implanted ions deep into the silicon crystal. Reducing the preamorphization implant energy effectively places the end-of-range (EOR) damage closer to the surface. How the EOR damage evolves has a critical effect on the amount of dopant diffusion that occurs. Speculation remains over how the excess interstitial population in the EOR is affected by the surface as the preamorphization energy is reduced. The first experiment in this thesis characterizes the damage created by a 5 keV, 1 x 1015 Ge+ cm-2 implant into silicon, which evolves much differently than higher energy implants. Using plan-view transmission electron microscopy, it was found that small, unstable dislocation loops formed in the EOR with a dissolution activation energy of 1.13

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xii xii 0.14 eV. The defects were shown not to coarsen significantly, but rather just decrease in number before the rapid dissolution took place. A surface lapping experiment showed that the defect dissolution energy is not attributed to the increased proximity of the surface, but was in fact implant energy related. The amorphous layer of a 10 keV, 1 x 1015 Ge+ cm-2 implant, which forms {311} defects and later stable dislocation loops, was reduced to less than that of the 5 keV implant and annealed at 750 C. The defect evolutions were then quantified for the 5, 10, and 10 keV-lapped samples. It was found that the defect evolution for the 10 keV-lapped specimen strongly resembles that of the control, un-lapped 10 keV sample. In the second experiment in this thesis, the effect of surface proximity for shallow amorphous layers was further studied. The amorphous layer of a 10 keV, 1 x 1015 Ge+cm-2 implant was reduced from 180 to depths of 155, 125, 80, and 40 . The samples were then annealed at 750 C for 15 and 45 min, and the defect populations were analyzed using plan-view transmission electron microscopy. Results show that increased surface proximity on amorphizing implants does not cause a significant reduction in the trapped interstitial concentration even down to amorphous layer depths of 40 . The final experiment examines the effect of a low temperature anneal on the accuracy of ellipsometry measurement of shallow amorphous silicon layers on the surface of crystalline silicon substrates. It was shown that a 400 C anneal significantly improves the accuracy of the ellipsometry measurements and does not regrow the amorphous layer. A reduction in the amorphous/crystalline interface roughness from the anneal was correlated to the increase in accuracy.

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1 CHAPTER 1 INTRODUCTION 1.1 Background and Motivation Modern day computing power is based on the integrated circuit (IC), which is a large number of transistors, resistors, capacitors, and other devices wired together on a the same substrate to perform a designated circuit function. The invention of the IC is attributed to Jack Kilby of Texas Instruments and Robert Noyce of Fairchild Semiconductor in 1959 [1]. Since then, the number of components on a typical IC has gone from the tens to the tens of millions. In 1965 Gordon Moore [2], an executive at Intel, made the observation that in order for the semiconductor industry to meet market demands, the number of transistors on the IC would have to double every 1 to 2 years. This observation has since come to be known as “Moore’s Law,” and has served as the industry trend and key indicator in predicting cutting-edge semiconductor technology for the past 30 years. In the late 1990’s experts in the semiconductor industry from Europe, Japan, Korea, Taiwan, and the USA developed the International Technology Roadmap for Semiconductors (ITRS) [3], which presents a semiconductor industry-wide consensus on the research and development needs for the industry over a 15 year time span. The primary focus of the ITRS is to maintain the continued scaling trends of ICs that require increasing the packing density, speed, and power efficiency of devices on the scale of

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2 Moore’s Law. These trends are ultimately responsible for decreasing the cost-perfunction of ICs, which has led to significant improvements in productivity and quality of life through the proliferation of computers and other electronic devices. The metal-oxide-semiconductor field-effect-transistor (MOSFET) is the basic building block of the IC (Figure 1). The scaling trends established by the ITRS require reducing the feature size of the MOSFET with every new generation of devices to meet performance requirements. One of the most challenging problems of device scaling is forming highly doped, ultra-shallow source/drain junctions and extensions with low sheet resistance. With each successive technology node, the junction depths are required to scale with the gate length to avoid short channel effects. These effects result when the drain’s electric field penetrates through the channel region and affects the potential barrier between the source and the channel regions. These effects diminish the ability of the gate to control the channel charge. ITRS also requires increasingly higher doping concentrations of the junctions to account for the inverse relationship between sheet resistance and junction depth. Shallower junctions will ultimately have higher resistivity. In physical terms, a deeper junction has a larger volume and therefore can incorporate a larger dose of electrically active carriers than a shallow junction with the same concentration, thus achieving a lower sheet resistance. Table 1 shows the 2002 ITRS junction-doping requirements projected to the 2016 technology node. Currently ion implantation is the preferred method of forming shallow junctions due its precision in controlling dopant concentrations and profiles. Implanting arsenic into the crystalline silicon forms shallow n+-p junctions with relative ease due to arsenic’s

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3 heavy atomic mass and small projected range. However, shallow p+-n junctions are difficult to form due to the p-type dopant’s small atomic mass, boron. When boron is implanted into silicon, channeling of the boron ion occurs. This results in a dopant profile channeling tail and a much deeper junction [4]. Figure 1.1 Cross-sectional schematic of a MOSFET. Amorphizing the silicon substrate by implanting isoelectric species such as silicon [5] or germanium [6] prior to dopant implantation (preamorphization) has been shown to reduce the channeling tail of boron. In fact, the channeling tail can be completely eliminated if the entire boron profile is within the amorphous region [7]. Subsequent recrystallization of the amorphous layer by solid phase epitaxy (SPE) [8] has been found to result in high dopant activation as well as reduced diffusion of dopant [9,10]. The major drawback to the preamorphization technique is the formation of extended defects below the original amorphous/crystalline ( /c) interface following SPE. These defects are referred to as end-of-range (EOR) damage since they reside at the end of the projected range of the implanted species. EOR damage can have detrimental

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4 affects on junction performance. If the EOR region is located within the depletion region of the device, large leakage currents will result [11]. Also, the supersaturation of interstitials in the EOR region can lead to transient enhanced diffusion (TED) [12] of the dopant profile, resulting in a deeper junction. Table 1.1 2002 ITRS doping technology requirements [3]. Year of Production200120042007201020132016 Technology Node (nm)1309065453222 MPU, Functions per chip (Gbits)0.541.074.298.5934.3668.72 Physical Gate Length (nm)65372518139 Contact Xj (nm)48-9527-4518-3713-2610-197-13 Drain extension Xj (nm)27-4515-2510-177-125-94-6 Max Drain extension RS (PMOS) (_/sq.) 4006607608309401210 Max Drain extension RS (NMOS) (_/sq.) 190310360390440570 Extension lateral abruptness (nm/decade) 7.24.12.82.01.41.0 Despite the difficulties presented by EOR damage, preamorphization is a necessary process step in novel dopant activation techniques that are being developed to meet future ITRS technology nodes, such as solid phase epitaxy regrowth (SPER) [13], laser thermal processing (LTP) [14], and flash lamp annealing [15]. Therefore it important to understand the parameters involved in EOR damage evolution in order accurately model dopant diffusion in silicon, which is a key factor in the continued scaling of junctions. 1.2 Ion Implantation Ion implantation is the primary technology for introducing impurities into semiconductors to form devices and IC circuits. The ion implantation process is highly flexible in the selection of dopant species, in choosing the spatial location to implant the

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5 species, and in its superior concentration profile control. The process consists of accelerating a beam of ions with sufficient energy to penetrate the target material. As the incident ions enter the substrate they under go two stopping processes, nuclear and electronic stopping [16]. Nuclear Stopping (Sn) occurs from collisions of the incident ion and the core electrons of the substrate atoms. Sn interactions usually involve an energy transfer during the collision between the ions and the atoms large enough to displace the substrate atoms from their lattice positions. This can lead to a damage collision cascade where many nuclear events can be produced by one primary ion. The large amount of damage produced by collision cascades from Sn can form continuous amorphous layers in silicon substrates. Electronic stopping (Se) arises from collisions between the incident ions and the outer electron shells of the substrate atoms. Seinteractions are similar to a drag force exerted on the implanted ions, transfer much less energy, and produce negligible damage to the substrate. The depths that the ions reach, or travel before they come to rest, in the target substrate follows an approximate Gaussian form, where the peak of the distribution corresponds to the most probable projected ion range. This is referred to as the projected range (Rp), and the standard deviation of the distribution is called the straggle ( Rp). Rp depends mainly on the energy and mass of the implanted species, while Rp depends on the ratio of the mass of the implanted ion to the mass of the substrate atom. During the ion implantation process, combinations of interstitial and vacancy pairs are created. These are called Frenkel pairs. A Frenkel pair is created during an individual ion collision event when the implanted ion collides with a lattice atom and knocks it out of position. The removed atom becomes an interstitial while a vacancy is

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6 created in the lattice position where the atom was removed. Additionally, if the interstitial produced by the initial collision has sufficient energy, it may knock off other atoms from lattice position creating additional Frenkel pairs in a multiplying nature. Mazzone [17] used Monte Carlo calculations to show that the vacancies and interstitials in the Frenkel pairs reside at different regions of the ion-depth profile. The calculations predict that the forward peaking nature of the momentum of an incoming ion produces a vacancy-rich zone in the region extending from the surface down to about 0.8Rp while between Rp and 2Rp, there should be a interstitial-rich zone. Due to nonconservative nature of ion implantation, meaning that substitution atoms are introduced into the lattice in far excess of available unoccupied lattice sites, the interstitial component dominates the point defect distribution for low to medium implant energies (< a few hundred keV) [18]. During a post-implant anneal in non-amorphized silicon, excess interstitials in the lattice have been observed due the damage created during implantation [19-21]. During annealing, vacancies are recombined with interstitials, but the non-conservative nature of implantation creates excess interstitials. Giles [19] proposed the “+1” model, which suggests that one interstitial, is created for each implanted ion during annealing and their diffusion is limited to either the surface or further into the substrate. During the ion implantation process, the irradiation of silicon can produce a crystalline-to-amorphous phase transition if a critical dose for amorphization is achieved. As mentioned previously, amorphizing silicon eliminates channeling of boron, and the SPE regrowth of the amorphous layer enhances electrical activation of the implanted dopant. The amorphization phase transition begins when sufficient irradiation from the

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7 ion beam produces a defected crystalline lattice with the same free energies as an amorphous silicon network. Holland et al. [22] proposed a model that considers the amorphization of silicon as critical-point phenomenon where the onset of amorphization leads to a cooperative behavior among various defects types that results in a greatly accelerated transition. Through their experiment with silicon self implants, a dose dependence of damage production was determined with two different regimes: an initial regime where growth is constrained by the formation simple point defects, followed by a regime of unconstrained growth which results in the complete amorphization of the lattice. In the latter regime, the onset of amorphization is precipitated by the rapid growth of damage that results from a cooperative mechanism where amorphous regions preferentially sink interstitial point defects which promotes more damage and leads to further amorphization. Another mechanism of amorphization from ion implantation proceeds by gradual changes occurring to the lattice over a range of doses. The process starts by the formation of small, isolated pockets of amorphous material. As the dose increases the pockets increase in number and overlap until eventually all the pockets have overlapped and a continuous amorphous layer is present. Typically amorphization of silicon is done with 28Si+ or 73Ge+ [6] since they are isoelectric and do not interfere with electrically active dopants. Clark [23] studied the effect of increasing the preamorphizing species’ mass on the formations of ultra-shallow junctions. It was determined that ions with larger atomic mass units are more efficient in amorphizing silicon, which results in less interstitial injection in the EOR region following SPE and less TED.

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8 1.3 Solid Phase Epitaxy The recrystallization mechanism of implanted amorphized silicon is called solid phase epitaxy (SPE). SPE proceeds epitaxially on an underlying crystalline silicon substrate. It is layer-by-layer laminar growth with atomic step edges as growing sites. Typical SPE regrowth begins to occur at temperatures as low as ~400-450 oC [24, 25] and on up to temperatures just below the melting point of amorphous silicon with regrowth rates dramatically increasing for increasing temperature. This is due to the fact that SPE recrystallization rates follow and Arrhenius expression determined by Csepregi et al. [8, 26] kT E oae v v1.1 where v is the regrowth velocity, vo is the pre-exponential factor, Ea is the activation energy, k is Boltzmann’s constant, and T is temperature in degrees Kelvin. Their work also showed that the orientation of the silicon also heavily determines recrystallization rates, reporting that <100> silicon regrows at a rate about 3 times faster than <110> silicon and about 25 times faster than <111> silicon. Experiments on determining the activation energy and pre-exponential factor have produced varied results. Licoppe and Nissim [27] report values of 3x108 cm/sec and 2.7 eV for vo and Ea respectively, while Olson [28] found values of 3.07x108 cm/sec and 2.68 eV for vo and Ea respectively. In general, amorphous silicon regrows at a rate of 10 / s at 600 C [13]. After the amorphous layer has regrown, the resulting recrystallized material is largely defect free and better quality than irradiated silicon that was not amorphized. The SPE process also produces high electrical activation of dopants because during regrowth

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9 impurities may become trapped onto substitution lattice sites allowing metastable conditions to be met. However, after regrowth the region just below the original amorphous/crystalline interface will have a supersaturation of interstitials and will probably form extended defects depending on the annealing conditions. 1.4 End-of-Range Damage The regrowth of amorphized silicon leaves a supersaturation of interstitials in the region just beyond the original amorphous/crystalline interface, which consolidates into extended defects during annealing. There are two sources of the interstitials that lead to the formation the extended defects. The first source is transmitted ions, which are the ions that come to rest below the amorphous/crystalline interface. The second source is the recoiling of excess interstitials deeper into the material due to the forward momentum of the ion beam. Jones et al. [29, 30] classifies this form of ion implantation induced damage as Type II or end-of-range (EOR) damage. The concentration of interstitials in the EOR region is sufficient to form both dislocation loops and {311} defects, which are described below. One interesting aspect of EOR damage is that the concentration of defects is not strongly dependant on dose [29, 30], but does change with implant energy [6, 31]. Dislocation loops in the EOR region are either {111} faulted Frank dislocation loops, or {111} perfect prismatic dislocation loops [32]. These loops are metastable defects consisting of interstitial silicon atoms. {311} defects, or rod-like defects, consist of silicon interstitials condensed on the {311} habit plane and elongated in the [110] direction.

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10 Figure 1.2 EOR damage created from an amorphizing implant [30]. 1.4.1 Defect Evolution The excess interstitials in the EOR created by the ion implantation process are mobile at high temperatures, and undergo extensive diffusion during annealing where they can coalesce into either dislocation loops or {311}’s in order to conserve free energy. Robertson et. al [33] used transmission electron microscopy (TEM) to observe that EOR defects formed by a 20 keV 1 x 1015 / cm2 Si+ implant undergo an evolution during annealing at 750 C over an extended period of time (10-370 min). The study showed that after 10 minute, both {311} defects and small dislocation loops are present,

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11 and as annealing times progressed the {311} defects followed two evolutionary pathways; faulting to form dislocation loops or dissolving releasing interstitials. Figure 1.3 shows a defect evolution tree from Jones [34]. Figure 1.3 Defect evolution of excess interstitials resulting from ion implantation into silicon and subsequent annealing [34]. The {311} defect evolution shows that compared to dislocation loops, {311}’s are metastable and become unstable at lower interstitial supersaturation. Therefore when the supersaturation of interstitials fall below a critical point, dislocation loops become energetically favorable and {311}’s undergo unfaulting to form dislocation loops [20, 35]. Also, the dissolution of {311} defects release interstitials that were trapped, which can lead to TED [36]. Dislocation loops have a formation threshold higher than {311} defects making loops less favorably during early annealing times. However, dislocation loops are more

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12 thermodynamically stable than {311}’s, therefore they can exist at longer times and higher temperatures. Stolk et al. [37] reported an activation energy for {311} dissolution to 3.8 0.2 eV while previous studies of dislocation loop dissolution in silicon have always shown an activation energy of 4 5 eV [38]. During the anneal the defect evolution of dislocation loops undergoes four stages: nucleation, growth, coarsening, and dissolution [39]. For short times during the nucleation stage, a large portion of interstitials precipitate to form dislocation loops while a small percent diffuses down the gradient. In the pure growth stage the supersaturation of interstitials is too low to form new loops, so loops grow but the density of defects remains unchanged. For long annealing times Ostwald ripening occurs, where the dislocation loops are in dynamic equilibrium with the surrounding excess interstitials, resulting in the growth of large dislocation loops at the expense of smaller ones [40, 41]. Gutierrez [42] examined the EOR defect evolution of 5-30 keV 1 x 1015 Ge+ cm-2 at 750 C using TEM and observed similar results as Robertson [33] for the 10 and 30 keV implant energies, interstitials evolving from small clusters to {311} defects and then to loops. However, for the lowest energy, 5 keV, the interstitials form small, unstable dislocation loops that dissolve within a narrow time window, with no {311} formation. This result suggests that for low energy amorphizing implants there may be a different defect evolution. 1.4.2 Transient Enhanced Diffusion In addition to forming extended defects, the excess interstitials created by ion implantation causes an enhancement [40, 43] of the diffusion of the dopant profile which is a major challenge in the formation of ultra-shallow junctions. An excellent review of

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13 TED is provided by Jain et al. [44] The origin of TED is based on the results of annealing a boron implanted silicon sample at ~ 800 C. During the anneal boron in the tail of the implanted profile diffuses very fast, faster than the normal thermal diffusion by a factor of 100 or more. After annealing for a while, the enhanced diffusion saturates. The enhanced diffusion is temporary, on annealing the same sample again after the saturation, enhanced diffusion does not occur again, hence transient enhanced diffusion. 1061071081091010101110121101001000104105 30 keV 10 keV 5 keVDefect Density (#/cm2)Time (sec.) 750 oCFigure 1.4 Defect evolution reported by Gutierrez [42] for Ge+ implanted at energies of 5, 10, and 30 keV at a constant dose of 1015 cm-2 annealed at 750 C. For the case of amorphizing implants, the enhanced diffusion is limited to the interactions between interstitials in the EOR region and the boron atoms [12, 20]. Both {311} defects and dislocation loops can drive TED in amorphizing implants. Eaglesham

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14 et al. [20] and Jones [45] found the dissolution of {311}’s in the EOR region correspond to the same time interval as TED, which is consistent with assertion that {311} defects are the source of the interstitials. Also, Lampi et al. [39] proposed that the evolution process of dislocation loops not only affects the time interval of TED, but also implies that loops are a source of interstitials as well. Robertson et al. [46] suggested that the dissolution rate of {311} defects alone is not sufficient to drive TED and loop growth, but is assisted by the dissolution of sub-microscopic interstitial clusters. Therefore, the dissolution of interstitials from different defect morphologies affect TED, but the degree of to which defect contributes is dependent on dissolution rate and activation energy of a given interstitial precipitate. The dissolution rate of the defect will determine the rate at which interstitials are released, while the activation energy of a defect will determine the whether or not the interstitial precipitate will dissolve at a given temperature. 1.5 Effect of the Free Surface on End-of-Range Damage As mentioned above, the excess interstitials introduced from ion implantation are believed to have two annealing sites, either the wafer surface or the bulk. It has widely been proposed that the wafer surface is an infinite interstitial recombination sink; therefore, as device scaling trends require shallower amorphous layers, the excess interstitials in EOR damage will be in ever increasing proximity to the surface. Surface effects on the formation and evolution of extended defects in the EOR and on TED are a controversial topic and have produced studies with contradicting results. Meekinson [47] using controlled etching reduced the thickness of a 3900 amorphous layer to 2000 and 800 and then annealed the samples in nitrogen ambient

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15 at 1100 C. TEM showed that the number of interstitials in EOR dislocation loops decreased with a decrease in amorphous layer thickness. The study also reported dislocation loops in the shallower amorphous layers lost interstitials from dislocation loops at a faster rate than in the sample with the original amorphous layer thickness. A similar study by Narayan et al. [48] reported a similar effect. They attributed this effect to either the reduced distance between interstitials and the surface or glide of the loops to surface due to an image force. Raman et al. [49] created EOR dislocation loops 2600 deep after annealing an amorphizing dual implant of 120 keV and 30 keV 1015 Si+/ cm2 at 850 C for 30 min. A CMP procedure was used to remove various amounts silicon in order to reduce loop depth in samples to 1800 and 1000 . They found that the proximity to the surface significantly affected dissolution kinetics of dislocation loops, and that loops dissolution is diffusion limited to the surface. However, in this experiment the effect of amorphous layer thickness was not a variable since the CMP procedure was performed after the amorphous layer was recrystallized. A model proposed by Omri et al. [50] considers the amorphous/crystalline interface as a diffusion barrier for interstitials during the nucleation state of extended defects, when the supersaturation is high. Then, according to their model, only after SPE regrowth during the coalescence of loops when the supersaturation of interstitials is high the surface can act as a recombination sink. In their experiment a 150 keV 2 x 1015 Ge+ cm-2implant was used to create a 175 nm thick amorphous layer. Anodic etching was used to vary the thickness of the amorphous layer from 17530 nm that were annealed at 1000 and 1100 C for 10s. Using TEM they observed that despite the varied amorphous layer

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16 thickness, the population of loops were the same. It was concluded that only after the amorphous layer has fully regrown interstitials can recombine at the surface. However, when this occurs the defects are already involved in the coarsening process and the supersaturation is small which tends to diminish the effect of the surface. Ganin and Marwick [51] observed similar results to Omri. They compared the EOR damage created by a 40 keV and 200 keV amorphizing In+ implants and then reduced the depth of the amorphous layer of the 200 keV implant to the sample thickness of the 40 keV sample. This enabled them to study the effect of surface proximity on EOR damage upon annealing. It was concluded that the damage created from the implants was strongly energy dependent since the 200 keV sample with reduced amorphous layer had the same EOR damage as a normal 200 keV implant. 1.6 Scope and Approach of this Study The work in this thesis is divided into three experimental sets. In the first experiment, the defect dissolution observed by Gutierrez for the 5 keV, 1 x1015 Ge+ cm-2implant condition will be further investigated. This investigation will entail determining the defect dissolution activation using a time – temperature study, qualifying the role of increased surface proximity on the dissolution, and simulating implant conditions using UT-Marlowe. The second experiment in this thesis is a surface lapping experiment which will help to enhance the understanding of increased surface proximity on interstitials in the EOR region for low energy implants. In this experiments the amorphous layer of a 10 keV, 1 x1015 Ge+ cm-2 implant will be lapped to various thicknesses and annealed. Influence of surface proximity will then be quantified using plan-view TEM.

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17 The final section of this thesis is a quick experiment that will measure the effect of a low temperature pre-anneal on the accuracy of shallow amorphous layer thickness measurements using ellipsometry. The results of all three of these experimental sections as well their contributions to understanding of extended defect formation in ion implanted silicon will be discussed. Finally, avenues of future experiments will be discussed.

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18 CHAPTER 2 EXPERIMENTAL AND DATA EXTRACTION PROCEDURES In this chapter, and overview of the sample preparation, characterization techniques, and data extraction procedures for the three experiments will be given. 2.1 Transmission Electron Microscopy Transmission electron microscopy (TEM) is a very useful technique for imaging extended defects created from the ion implantation process. Both diffraction and imaging information can be obtained with TEM based on the interactions between the electron beam and a thinned specimen as the beam transmits through that specimen. Specimens can be viewed from both the top down orientation or in cross section to give a threedimensional perspective on the damage created. Viewing specimens from the top down orientation is referred to as plan-view transmission electron microscopy or PTEM. PTEM allows the imaging of extended defects (dislocation loops and {311} defects and quantification of defect evolution. Defects are visible in PTEM according to diffraction contrast if g b x u 0 where g is the reciprocal lattice vector corresponding to the diffraction plane, b is the dislocations Burgers vector, and u is the dislocation line direction. All PTEM specimens were viewed on JEOL 200CX operating at 200 keV in the g 3 g centered weak beam dark field (WBDF) condition using a g220 two-beam imaging condition at a magnification of 50,000 X. The WBDF field condition is very useful in imaging defects since it only resolves the

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19 region of the highest strain around an extended defect, which is the core of the dislocation [52]. Viewing specimens in cross section is appropriately referred to as cross section transmission electron microscopy (XTEM). A JOEL 2010 high-resolution TEM operating at 200 keV as well as a JOEL 200CX operating at 200 keV were used to measure amorphous layer thickness down the [110] zone axis. 2.1.1 Plan-view Transmission Electron Microscopy Sample Preparation Plan-view transmission electron microscopy (PTEM) samples are prepared in order to view the TEM specimen from the top-down orientation. The samples are made according to the following procedure: 1. A 3 mm disc is cut out of experimental material with a Gatan ultrasonic disc cutter using silicon carbide (SiC) powder abrasive and water. The sample is mounted on a glass side with the top side (implanted side) down with crystal bond. Crystal bond is a thermoplastic that softens with the application of heat and hardens at room temperature. For all application involving crystal bond a hot plate is used as the heat source (set to ~ 200 C) and acetone is used to remove the crystal bond from the specimen. The glass side is then adhered to the disc cutters stage using double-sided tape. 2. The sample is then thinned to approximately 100 m using abrasive slurry of 15 m aluminum oxide (Al2O3) powder and water on a glass plate. The sample is mounted top-down on a metal stage using crystal bond. The stage is attached to a handheld lapping fixture from South Bay Technology and

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20 lapped in figure eight motions until the sample is deemed thin enough by finger touch. 3. The sample is then further thinned using a wet drip etch of 25% hydrofluoric acid (HF) and 75% nitric acid (HNO3). The sample is etched by mounting it top side down on a Teflon stage with paraffin wax. The wax is melted on a hot plate and is used coat the top side to prevent etching of the implanted surface. The sample is then adhered to the stage by coating the perimeter of the sample with wax leaving the center of the sample uncovered to allow preferential etching of the sample center. Etching is deemed complete when a hole is created and a red transmission under a light source can be observed around the edges of the etch pit. 4. The sample is then removed from the Teflon mount and soaked in nheptane for 15 min – 24 hr or until all wax has been removed. The sample is now ready for PTEM. 2.1.2 Cross-Section Transmission Electron Microscopy Sample Preparation Cross-section transmission electron microscopy (XTEM) samples are prepared using either two techniques of the following techniques. The first technique is performed according to the following procedure: 1. Two 20 milli-inch wide strips are cut with a high speed wafer dicing saw from the experimental material. 2. The two strips are glued together using a thermally activated twocomponent epoxy with the surfaces of interest facing each other. Then two dummy strips of the same width are glued to both sides of the experimental

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21 strips making 6 strips total glued together. The epoxy is then cured on a hot plate at ~200 C for 10 minutes to ensure proper cross-linking. 3. A 3 mm disc is cut from the glued strips using the same procedure outlined in the above section. 4. The disc is then mechanically thinned on both sides using a progressive sequence of gritted carbide lapping papers. The lapping is performed in an up and down motion using a handheld lapping fixture. 5. The sample is further thinned using a VCR Dimpler. In this procedure the disc is mounted on a thin sapphire disc with crystal bond and mounted on the Dimpler stage. The sample is first flattened using the appropriate flattening polishing wheel and 3 m slurry to 100 m. The center of the sample, or the interface of the two center strips, is then dimpled using the dimpling polishing wheel and 1 m slurry until a red transmission under light can be observed on the interface. Then a fine polishing wheel is used with a 0.1 and 0.05 m slurry to remove scratches on the dimpled surface created during the thinning process. 6. The sample is then ion milled using Ar+ in a dual-gun Gatan ion mill set at 12-14 tilt until a small hole created on the interface of the center strips is created. The sample is now thin enough for XTEM. The second technique uses a Strata Dual Beam 235 FIB (focused ion beam) from FEI, Inc to cut out a XTEM specimen that is approximately 18 m long, 3 m deep, and 1500 thick using a gallium ion source. The sample is first coated with carbon followed by a layer of platinum that is approximately 1 m thick. Once the specimen is cut out, it

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22 is mounted on a copper specimen ring with carbon mesh. The FIB XTEM is now ready for TEM. 2.1.3 Extraction of Defect Parameters from PTEM Determining defect parameters from PTEM images, such as defect density, trapped interstitial concentration, and defect sizes, allows for the quantification of how interstitials evolve over time at a specific annealing temperature. Understanding the influence of implant energy, implanted species, annealing temperature, annealing time and other factors on the damage created helps provide experimental results to assist dopant diffusion models, such as FLOOPS [53], to correlate TED and the evolution of EOR damage. There is an intrinsic 20 % error associated with the following methods for extracting defect parameters [54]. 2.1.3.1 Extraction of Defect Densities from PTEM Defect density is simply the number of defects observed in PTEM in the area that they were observed in. The defect densities in this study are determined by the following procedure adapted for one set forth by Bharatan [54]: 1. PTEM negatives are enlarged to 3X (making total magnification now 150 kX) and printed onto 8” x 10” photographic paper. 2. A transparent film with a grid of 4 cm x 4 cm squares printed on it is laid on top of the print. All resolvable defects (defect clusters, dislocation loops, {311}’s) within a given square are carefully traced onto the transparency with a fine tip marker. 3. The defect density is then determined by dividing the total number of defects counted by the area of the square, 16 cm2, and multiplying by the magnification to the second power. This is done from at least three of the

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23 squares on the transparency in random areas and the results are averaged together. This process is adapted to counting only specific defects as well. To determine the {311} defect density, only {311} defects are traced and counted in the given area, and to determine the dislocation loop density only dislocation loops are counted. The detection limit of defects for PTEM is considered to be 107 defects / cm2 2.1.3.2 Extraction of Trapped Interstitial Concentrations from PTEM The trapped interstitial concentration gives a quantity of the number of silicon interstitial atoms present in the defects observed. The PTEM detection limit of trapped interstitials is considered to be 6 x 109 interstitials / cm2. The first steps are the same as in the procedure for determining defect density. Dislocation loops and {311} defects are traced separately on transparencies. Then the following steps are taken: 1. The traced transparencies are scanned into .pict -formatted files using Adobe Photoshop software. 2. The scanned file is imported into an image analysis program developed by the National Institute of Health called NIH Image v.1.6.1. The software measures the length sum of {311} and the total area of dislocation loops. 3. The {311} defect trapped interstitial concentrations are determined by calculating a modified length sum by the linear density of interstitials (26 interstitials / nm) contained in the {311} defect and dividing by the scanned area. The modified length sum is used for {311} type defects imaged at a 45 angle to the imaging plane because the length observed is a projected length of the defect and not the actual length. In order to account for the discrepancy, these defects’ lengths are multiplied by a factor of 1.4.

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24 4. Dislocation loop trapped interstitial concentrations are calculated by dividing the total area of the loops by the area of the scanned image and multiplying the result by the planar atomic density of the {111} plane which is 1.6 x 1015 atoms / cm2. At this point it is important to note that in his thesis, Gutierrez [42] assumed the small defects created by the 5 keV energy to be dislocation loops and extracted trapped interstitial concentrations using the above method. In this present work this assumption is made also. Support for the assumption that the small defects observed in the TEM from the 5 keV implant are dislocation loop – like will be shown in Chapter 3. 2.2 Variable Angle Spectroscopic Ellipsometry Ellipsometry is an optical technique that measures the change in polarized light as it is reflected off a sample. Variable angle spectroscopic ellipsometry (VASE) is used in this work as a fast, nondestructive technique for measuring amorphous silicon layer thickness, in contrast to XTEM. In VASE a linearly polarized light is reflected off the surface of the sample into a detector. As the polarized light reflects off the surface the light changes from plane-polarized light into elliptically polarized light. The elliptically polarized light is characterized as having two electric field components perpendicular to one another and a phase difference, It is r which is the azimuth of the reflected light, and that are characteristic of the material under study and are measured for sample analysis. Once the optical constants ( r and ) are measured, a computer program constructs a model to solve for layer thickness based on a library of previously measured constants.

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25 All VASE measurements were performed using a J. A. Woolmam multiwavelength spectroscopic ellipsometer with a 75 W xenon light source at a fixed angle of 75 The system is first calibrated by measuring the silicon dioxide thickness on a calibration wafer. The only sample preparation required in VASE is a careful cleaning of the sample’s surface with methanol. The sample area must be larger than 1 cm x 1 cm to eliminate edge effects from the light source’s beam, which is about 3 mm in diameter. During measurements a fixed 20 oxide layer was assumed for samples to account for the native oxide of silicon. A minimum of three measurements is taken from different areas on the sample for all measurements. The VASE technique produces very precise measurements, but the accuracy may some time be questionable. Scanning over a larger range of wavelengths of light also increases accuracy of measurements. Overall the VASE system normally yields an accuracy of 10-20% of actual thickness determined from TEM, however Lindfors[10] showed that very shallow amorphous layer the accuracy may be worse. In his work he measured an amorphous layer thickness of a 2.5 keV 1 x 1015 Si+ / cm2 to be 26 with high-resolution TEM compared to 13 with VASE. 2.3 UT – Marlowe UT – Marlowe [55] is a binary collision approximation simulator that considers crystal structure, therefore it is used for the simulation of ion implantation into crystalline and amorphous material. This modeling predicts both the impurity profiles as a function of depth of implant parameters and also damage profiles, which can be used as input files for TED simulators, such as FLOOPS (see section below).

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26 During this work UTMarlowe has been used to simulate the 5 and 10 keV 1 x 1015Ge+/cm2 amorphizing implants in order to give a qualitative under standing of the initial implant conditions and the difference of the net excess interstitials (NEI) in the EOR region created between to the two energies. UT-Marlowe can simulate amorphous layer depths by using the filename.rbs output file, which simulates a rutherford backscattering spectrometry (RBS). The amorphous layer depth is determined by finding the depth at which the percentage of amorphization decreases most rapidly on a linear linear plot. The NEI is calculated by using two separate output files. The first output file used is the filename.ist output file. It is the concentration of silicon interstitials formed during implantation at a given depth. When the concentration of interstitials reaches 5 x 1021cm-3 or 10% of the lattice density at a given depth the lattice is considered amorphized. The second output file used is the filename.vac file. It provides a concentration of concentration profile of the number of silicon vacancies formed during implantation. Subtracting the concentration profile of interstitials from the concentration profile of the vacancies in the EOR region and taking the integral of the area underneath the difference calculate the NEI. The NEI is the difference between two very large numbers therefore the simulation was performed with 300,000 input ions. 2.4 5 keV Ge+ Defect Dissolution Study The goal of this study is to gain further understanding of the defect dissolution observed by Gutierrez [42] for the 5 keV 1 x 1015 Ge+ cm-2 implanted silicon wafers. The first experiment in this study was performed to calculate the activation energy of the observed defect dissolution. The second experiment was performed to determine if the

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27 increased surface proximity for the 5 keV energy (amorphous layer thickness = 100 )1compared to the 10 keV energy (amorphous layer thickness = 220 ) 2 has a role in the dissolution process. For both experiments the source material used is Czochralski grown (100) Si wafers implanted by Varian, Inc. at room temperature with a constant does of 1 x 1015 Ge+ cm-2 at 5 and 10 keV energies with a 7 tilt. These wafers have only a native oxide layer, approximately 20 thick. Finally, UT – Marlowe was used to obtain a qualitative understanding of the difference in the NEI difference between the two energies in the EOR region. 2.4.1 5 keV Defect Dissolution Activation Energy Experiment To investigate the defect dissolution process observed for the 5 keV energy implants, specimens were annealed at multiple temperatures to calculate the activation energy of the dissolution. PTEM was used to identify times when the dissolution process occurs at temperatures of 725, 750, 775, 825, and 875 C. The times and corresponding temperatures were plotted in an Arrhenius-type chart to calculate the activation energy. The annealing was performed in a Lindberg tube furnace under nitrogen ambient with the sample placed in a quartz boat. All annealing procedures were performed in this furnace. Usually, samples are annealed first before they are thinned for TEM analysis, however Li[56] et al. showed once samples are thinned they can be annealed as well without producing a measurable effect on defect evolution. Based on this, many PTEM samples 1 Values obtained from Gutierrez’s work. The amorphous layer thickness for both energies are measured again in this work.2 Values obtained from Gutierrez’s work. The amorphous layer thickness for both energies are measured again in this work.

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28 in this work are annealed after they have been thinned to reduce the labor of sample preparation for every annealing time. 2.4.2 Surface Lapping Experiment In the second part of this experiment the effect of increased surface proximity between the 5 and 10 keV implants was studied by using a mechanical lapping technique to bring the EOR region in the 10 keV implant to the same proximity to the surface as the 5 keV implant. In this experiment the amorphous layer of a 2 cm x 2 cm 10 keV Ge+sample was reduced to 80 , which is less than that of the amorphous layer of the 5 keV implant. The lapped sample was then annealed at 750 C and the defect evolution was characterized using PTEM and compared to control samples of the 5 keV and 10 keV implants. The mechanical lapping procedure used in the surface lapping experiment removes measured amounts of amorphous silicon in order to increase the surface proximity between the EOR region (and excess interstitials) to surface. The procedure used is based on the one developed by Herner et al [57]. The lapping procedure in this experiment was performed according to the following steps: 1. A 2 cm x 2 cm sample is cut from experimental material using a high speed wafer dicing saw. 2. The square sample is then mounted on a lapping stage using crystal bond and lapped using a hand lapping fixture from South Bay Technology and polished on 12 in rayon polishing pads with Syton as the polishing agent. Syton is colloidal silica with particle sizes from 0.2 – 0.6 m. The sample is lapped in a figure eight motion. The lapping procedure removes about

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29 10-12 per lap once the native oxide has been removed by the lapping procedure or by a buffered oxide etch (BOE). 3. Once the appropriate number of laps has been performed the sample is removed from the stage and the crystal bond is removed with acetone. 2.6 Surface Proximity Experiment This experiment is a continuation of the surface lapping experiment described in the section above. The goal of this experiment is to determine what effect increased surface proximity has on excess interstitials in the EOR region. Three 10 keV, 1x 1015Ge+ cm-2 specimens with reduced amorphous layer depths of 155, 125, and 40 will be produced for this experiment in addition to the 80 specimen from the section above. The procedures of this experiment is described below: 1. 2 cm x 2 cm samples are cut from experimental material using a high speed wafer dicing saw and their amorphous layers are lapped using the procedure described in the above section. 2. Ellipsometry is then used to gain a quick measure of the lapped amorphous layer depths. 3. A 3 mm core is taken from the center of each of the 2 cm x 2 cm square samples and these cores are annealed at 750 C for 15 min. The cored, annealed specimens are then thinned for PTEM. XTEM specimens are made from each of the square samples using a FIB to cut out a thin sample very close to area on the sample where the core was taken. The amorphous layer depths are then measured using XTEM.

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30 4. PTEM is used to quantify the extended defects in the samples after the 15 min anneal, and then the samples are annealed for another 30 min making the total anneal time 45 min and examined with PTEM again. The effect of increased surface proximity on interstitials in the EOR will be determined by comparing the defect parameters obtained by PTEM versus amorphous layer depths. 2.7 Ellipsometry Experiment In this experiment, the effect of a low temperature anneal on the accuracy of ellipsometry measurements for shallow amorphous layers will be determined. The experimental material used in this experiment is 5, 10, and 30 keV, 1 x 1015 Ge+ cm-2implanted Si wafers from Varian, Inc. Samples from the wafers will be annealed at 400 C for times ranging from 5 – 80 min in a conventional tube furnace with nitrogen ambient. Amorphous layer depths will then be measured using ellipsometry for each annealing time. Ellipsometry measurements will be performed on a J. A. Woolmam multiwavelength spectroscopic ellipsometer described in section 2.2. Three measurements will be performed on each sample. XTEM samples will be prepared for as-implanted specimens for the three implant energies as well as samples that have been annealed for 40 and 80 min. The XTEM specimens will be images on a JEOL 2010 high resolution TEM to image the amorphous layer depth as well as the amorphous/crystalline interface roughness. The amorphous/crystalline roughness will be determined by averaging peakto-valley distance from five different positions along the interface from enlarged XTEM images.

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31 CHAPTER 3 5 keV Ge+ DEFECT DISSOLUTION STUDY 3.1 Overview The work in this chapter was performed to gain a better understanding of the defect dissolution observed by Gutierrez [42] for the 5 keV Ge+ implant energy when compared to higher energies shown previously in Figure 1.4. In his thesis, Gutierrez reported the low energy implant created small unstable dislocation loops that dissolved rapidly after 60 min annealing time at 750 C. Gutierrez concluded that the excess interstitials resulting from the 5 keV implant condition have an alternate evolutionary pathway than higher energy implants. The work in this chapter was performed to further characterize the previously unreported small unstable dislocation loops created from the low energy, amorphizing implant condition. The first experiment in this chapter was performed to find the defect dissolution activation energy of the small defects created from the 5 keV implant. Since these small defects dissolve after shorter annealing times than ones created by the higher 10 and 30 keV implants, they must have a different dissolution energy threshold. The second experiment in this chapter was performed to determine the effect of increased surface proximity to the EOR region between the 5 and 10 keV implants. The 5 keV implant, reported by Gutierrez, forms a 100 amorphous layer compared to the 220 amorphous layer formed by the 10 keV energy. Therefore the diffusion distance to the surface for the interstitials created in the 5 keV implant is roughly half as far as it is for the

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32 interstitials in the 10 keV case. If the surface acts like an infinite interstitial recombination sink then increased interstitial annihilation at the surface will lower the supersaturation and may account for the dissolution observed in the 5 keV implant. Finally in this chapter, initial implant conditions and the difference between the net excess interstitials (NEI) in the EOR will be calculated using UT-Marlowe simulations for the 5 and 10 keV energies. 3.2 Defect Dissolution Activation Energy The defect dissolution activation energy for the 5 keV 1 x 1015 Ge+ cm-2 implant condition was calculated by obtaining the times when all defects dissolved at 725, 750, 775, 825, and 875 C using PTEM. 3.2.1 TEM Results Figures 3.1 – 3.5 show WBDF PTEM micrographs of the extended defects created by the 5 keV 1 x 1015 Ge+ cm-2 implant at each of their respective times and temperatures until dissolution. As the micrographs show, the exact time when the defects dissolve is not determined since they are not annealed in-situ in the TEM, instead the dissolution time is determined by finding the range in time when the last point defects are present and next time where they are no longer present as observed by TEM. For example, at 725 C the final annealing time defects were observed was at 70 min. At the next annealing time of 80 min, there are no observable defects and therefore they assumed to be dissolved. The time of defect dissolution at 725 C is then to occur at a time between 70 and 80 min. Table 3.1 show the range of dissolution times determined by PTEM at each respective temperature.

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33 Table 3.1 Time range where defect dissolution occurs at each annealing temperature as observed by PTEM.Temperature 725 C750 C775 C825 C875 C Range70 – 80 min60 – 65 min40 45 min30 – 35 min10 – 15 min Figure 3.6 shows a WBDF PTEM image of a 5 keV implant annealed at 775 C for 35 min imaged at the g040 condition in contrast to the normal g220 condition. The defect is faint, but shows two lobes with a line of no contrast through the middle that is parallel to g This is characteristic to dislocation loop contrast in TEM [58]. This observation supports the assumption that the small defects created by the 5 keV energy implant are dislocation loops – like in nature. Figures 3.7 and 3.8 show the defect density and trapped interstitial concentration trends over time at the five annealing temperatures, respectively. As the figures show, the defect densities and trapped interstitial concentrations decrease for increasing temperatures, as expected. Another trend that is clearly shown by the three lowest temperatures of 725, 750, and 775 C is that the number of defects remains plateaued relatively high, in the 1010 defect/cm2 range until they approach their dissolution window where the trend decreases rapidly. The trapped interstitial concentration also shows this trend. Figure 3.9 shows the average defect diameter over annealing at each of the five respective temperatures. The error bars represent the standard deviation of the averages. As annealing temperature increases, the average defect size increases. For the lowest annealing temperature, 725 C, the defects do not increase in diameter or ripen over time significantly. At 15 min the average defect size is 5.89 nm and at the last point before

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34 dissolution the average defect size has only increased to 8.92 nm. In general, the defects for all annealing times do not increase in average diameter greater than 40% before dissolution. The defects reduce in number more significantly than grow in size or coarsen. 3.2.2 Extraction of Defect Dissolution Activation Energy The activation energy for the 5 keV, 1 x 1015 Ge+ cm-2 implant defect dissolution was determined by applying an Arrhenius relationship to the time ranges and temperatures where the dissolution was observed, shown in Figure 3.10. The mid-point of the time ranges were plotted as a rate (s-1) on the y-axis with error bars reflecting the max and min of the time range. The inverse of temperature (K-1) was plotted on the xaxis multiplied by a factor of 104 for clarity. Using a least square exponential curve fit to the data, the defect dissolution was found to follow the trend; = 99.845 e^(-1.3091x) 3.1 The correlation coefficient, r, of the curve was determined to be 0.97091, which shows a strong fit to the data. The activation energy is determined by multiplying the fitted exponential value, 1.3091, by Boltzmann’s Constant (8.65 x 10-5 eV/K) and 104 to correct for the x-axis factor of the same value. Performing these operations reveals the ultimate trend of the defect dissolution, shown by the relationship; = e^ -(Ea/kT) 3.2 where Ea is 1.13 eV and is 99.845 s-1. The error that is associated with the experimentally determined Ea was determined to be 0.14 eV. This was calculated by fitting a line to plot in accordance with the maximum error represented by the error bars.

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35 3.3 Surface Lapping Experiment This experiment was performed to evaluate the effect of increased surface proximity on the dissolution of the defects created by the 5 keV, 1 x 1015 Ge+ cm-2implant. If the surface is a source for interstitial recombination, than the increased surface proximity in the 5 keV case may explain the rapid defect dissolution. In this experiment the amorphous layer of a 10 keV, 1 x 1015 Ge+ cm-2 was lapped to thickness less than the thickness of 5 keV, 1 x 1015 Ge+ cm-2 implant. Both the 5 and 10 keV energy implants were annealed at 750 C for times ranging from 5 – 360 min and the defect evolution was characterized using PTEM. 3.3.1 Amorphous Layer Lapping Results Ellipsometry was used to determine if the 10 keV-lapped specimen’s amorphous layer was polished to a thickness less than that of the 5 keV implant. Table 3.2 shows the ellipsometry measurement results for the 5, 10, and 10 keV-lapped specimens. Based on the ellipsometry results, the amorphous layer thickness for each specimen was verified using high resolution transmission electron microscopy (HTREM). Figure 3.11 shows the HRTEM results. The amorphous layer thickness for the 5, 10, and 10 keV lapped specimens was determined to be 100, 180, and 80 , respectively. The lapping procedure reduced the 10 keV-lapped specimen’s amorphous layer thickness by 100 , 20 less than the 5 keV amorphous layer thickness.

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36 Table 3.2 Ellipsometry measurements of amorphous layer thickness for the 5, 10, and 10 keV lapped specimens. Amorphous layer thickness 5 keV10 keV-lapped10 keV 1st measurement144.24 120.86 209.54 2nd measurement144.64 118.20 220.39 3rd measurement144.04 110.72 226.25 3.3.2 Defect Evolution Figures 3.12 and 3.13 show PTEM micrographs of the defect evolution for the 10 keV specimen and the 10 keV-lapped specimen annealed at 750 C. For micrographs of the 5 keV energy at 750 C the reader is referred to Figure 3.2. It was found that the defect evolution of the 10 keV-lapped specimen strongly resembled that of the control, unlapped 10 keV specimen. Figure 3.14 shows the defect evolutions for the 5, 10, and 10 keV-lapped specimens. The 10 keV lapped specimen did not exhibit dissolution of defects, stable dislocation loops were still present after the longest annealing time of 360 min. The defect evolution for the 10 keV control and 10 keV-lapped followed that of the one reported by Gutierrez, small cluster defects evolved into {311} defects and dislocation loops, then [311} defects dissolved leaving stable dislocation loops. 3.4 UT-Marlowe Simulations UT-Marlowe simulations were performed to obtain pre-experimental conditions of for the 5 and 10 keV, 1 x 1015 Ge+ cm-2 implants. A 300,000-ion simulation was run for the two energies at a 7 tilt to match the implant conditions. The predicted amorphous

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37 layer depths, vacancy profiles, interstitial profiles, and the net excess interstitial (NEI) profiles for the two energies were obtained. 3.4.1 Simulation Results UT-Marlowe simulations for the 5 keV energy implant calculated a Rp of 70 and a Rp of 32 . Figure 3.15 shows the .rbs output for the 5 keV implant. The profile predicts the amorphous layer depth to be 108.3 compared to that of 100 measured by HRTEM. Figure 3.16 shows the vacancy and interstitial profile of the 5 keV implant. Note that the noise level in the data increases dramatically at concentrations below 1 x 1019 cm-3. UT-Marlowe simulations for the 10 keV energy implant calculated a Rp of 114 and a Rp of 53 . Figure 3.17 shows the .rbs output for the 10 keV implant. This profile predicts the amorphous layer depth to be 195.48 in contrast to 180 measured by HRTEM. Figure 3.18 shows the vacancy and interstitial profile of the 10 keV implant. Again, note that the noise level in the data increases dramatically at concentrations below 1 x 1019 cm-3. 3.4.2 NEI calculation The NEI profiles for the 5 and 10 keV implants were obtained by normalizing the depth by eliminating the amorphous layer from the calculation and subtracting the interstitials from the vacancies in the profiles. The area under the curves up to a concentration of 1 x 1019 cm-3 was then integrated to get the NEI concentration. Figure 3.19 shows the NEI profile for the two energies. The NEI concentration in the EOR region for the 5 keV implant was calculated to be 3.47 x 1014 cm-2. The NEI concentration in the EOR region for the 10 keV implant was calculated to be 3.30 x 1014cm-2.

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38 3.5 Discussion The 1.13 0.14 eV defect dissolution activation energy for the 5 keV implant is an intriguing result, especially if these defects are considered to have a defect morphology like dislocation loops. These defects clearly do not behave like any type of dislocation loops previously reported in silicon, which have always have had dissolution activation energies reported to be in the 4 – 5 eV range [59]. The explanation for this has always been that the Si self-diffusion was involved, which has an activation energy of ~4.5 eV [59, 60]. The low 1.13 eV activation energy may indicate that instead of the dislocations moving by a diffusion controlled climb process, the dissolve by a lower energy glide process. Also, Figure 3.9 shows that the defects do not coarsen significantly, which is a key characteristic of dislocation loops. One may propose that these defects are in fact spherical, or volumetric clusters of silicon interstitials, since that defect morphology would minimize the most energy. Calculating the trapped interstitial concentration assuming a sphere instead of plate will increase the value by a factor roughly of 103 interstitials/ cm2, which is an unreasonable value given the experimental conditions and results. Also, the appearance of the defect shown in Figure 3.6 is convincing evidence to the author that these defects are in fact plate-like, dislocation loops. The surface lapping experiment eliminated surface proximity as the main factor responsible for the defect dissolution. The defects formed in the EOR are clearly implant energy dependent in agreement with Omri [50] and Ganin and Marwick [51]. UTMarlowe simulations showed that there is no qualitative difference in the NEI in the EOR between the 5 and 10 keV energy implants, but the accuracy of these results are questionable. A simulation with a significantly larger amount of ions should be run to

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39 further verify theses results. Gutierrez [42] showed in his thesis using quantitative PTEM that there is almost an order of magnitude less trapped interstitials in the 5 keV case then in the 10 keV energy. Figure 3.20 shows his experimental results. The small, unstable defects may be a result from the implant condition that has a very small straggle, 32 , and a low supersaturation of excess interstitials. 3.6 Conclusion The small, unstable defects created by the 5 keV, 1 x 1015 Ge+ cm-2 implantation into silicon reported by Gutierrez [42] were found to have a dissolution activation energy of 1.13 0.14 eV. PTEM showed that these defects do not significantly coarsen, but rather just decrease in number. A lapping experiment which reduced the amorphous layer of a 10 keV implant with the same dose to less than that of the 5 keV implant showed that increased surface proximity is not responsible for the defect dissolution. It was found that the defects in the 5 keV energy case were strongly implant energy dependent. The author proposes that these small defects are dislocation loop-like and are result of the implant’s small straggle and low interstitial supersaturation.

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40 1000 (a) (b) (c) (d)(e) Figure 3.2 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 725 C for (a)15 min, (b) 60 min, (c) 65 min, (d) 70 min, and (e) 80 min.

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41 1000 (a) (b)(c) (d) (e) Figure 3.2 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 750 C for (a) 5 min, (b) 15 min, (c) 45 min, (d) 60 min, and (e) 65 min.

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42 1000 (a)(b)(c) (d) Figure 3.3 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 775 C for (a) 15 min, (b) 35 min, (c) 40 min, and (d) 45 min.

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43 1000 (a)(b)(c) Figure 3.4 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 825 C for (a) 15 min, (b) 30 min, and (c) 35 min.

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44 1000 (a)(b)(c) Figure 3.5 PTEM micrographs of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 875 C for (a) 5 min, (b) 10 min, and (c) 15 min.

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45 300 Figure 3.6 PTEM micrograph of 5 keV Ge+, 1 x 1015 cm-2 Ge+ annealed at 775 C for 35 min imaged at the g040 condition.

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46 1 x 1061 x 1071 x 1081 x 1091 x 10101 x 10111 x 1012010002000300040005000 C C C C CDefect Density (#/cm2) Time (s) TEM detection limit Figure 3.7 Defect density trends for 5 keV, 1x 1015 Ge+ cm-2 implant over time annealed at 725, 750, 775, 825, and 875 C.

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47 1x1091x10101x10111x10121x10131x1014010002000300040005000 725 C 750 C 775 C 825 C 875 CTrapped Interstitials (#/cm2 )Time (s) TEM detection limit Figure 3.8 Trapped interstitial trends for 5 keV, 1x 1015 Ge+ cm-2 implant over time annealed at 725, 750, 775, 825, and 875 C.

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48 0 5 10 15 20 25 30 35 40 010002000300040005000 725 oC 750 oC 775 oC 825 oC 875 oCAverage Defect Diameter (nm)Time (s)Figure 3.9 Average defect diameter over time for the 5 keV, 1 x 1015 Ge+ cm-2 implant annealed at 725, 750, 775, 825, and 875 C.

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49 1 x 10-41 x 10-31 x 10-28.599.510 y = 99.845 e^(-1.3091x) R= 0.97091 (s-1)104 / T (K-1)Figure 3.10 Defect dissolution rates versus inverse temperature, plotted in Arrhenius form. The trend is show as a least square exponential curve fit.

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50 (a) (b) (c) Figure 3.11 High-resolution cross section TEM micrographs of the amorphous layer thickness for (a) 10 keV, (b) 10 keV-lapped, and (c) 5 keV samples. Arrows point to the surface.

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51 (a)(b) (c)(d) (e)(f) Figure 3.12 PTEM micrographs of the 10 keV Ge+, 1 x 1015 cm-2 Ge+ control implant annealed at 750 C for (a) 5 min, (b) 15 min, (c) 30 min, (d) 45 min, (e) 60 min, and (f) 360 min.

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52 (a)(b) (c)(d) (e)(f) Figure 3.13 PTEM micrographs of the 10 keV Ge+, 1 x 1015 cm-2 Ge+ implant whose amorphous layer was polished to 80 and annealed at 750 C for (a) 5 min, (b) 15 min, (c) 30 min, (d) 45 min, (e) 60 min, and (f) 360 min.

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53 106107108109101010111012102103104 10 keV 180  10 keV 80  5 keV 100 Defect Density (#/cm2 )Time (s) TEM detection limit Figure 3.14 Defect evolution of the 5 keV, 10 keV, and 10 keV-lapped specimens annealed at 750 C.

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54 0 20 40 60 80 100 0100200300400500Percent Amorphization (%)Depth (A) Amorphous Crystalline Figure 3.15 UT-Marlowe .rbs output for the 5 keV, 1 x 1015 Ge+ cm-2 implant.

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55 1x10181x10191x10201x10211x10220100200300400500 Interstitials VacanciesConcentration (#/cm3 )Depth (A)Figure 3.16 UT-Marlowe simulated interstitial and vacancy profiles for the 5 keV, 1 x 1015 Ge+ cm-2 implant.

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56 0 20 40 60 80 100 0100200300400500Percent Amorphization (%)Depth (A) Amorphous Crystalline Figure 3.17 UT-Marlowe .rbs output for the 10 keV, 1 x 1015 Ge+ cm-2 implant.

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57 1x10181x10191x10201x10211x10220100200300400500 Interstitials VacanciesConcentration (#/cm3 )Depth (A)Figure 3.18 UT-Marlowe simulated interstitial and vacancy profiles for the 5 keV, 1 x 1015 Ge+ cm-2 implant.

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58 1x10181x10191x10201x10211x1022050100150200 10 keV NEI 5 keV NEIConcentration (#/cm3 )Normalized Depth (A)Figure 3.19 NEI profile for the 5 and 10 keV, 1 x 1015 Ge+ cm-2 implants.

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59 Figure 3.20 Trapped interstitial concentrations from 5, 10 and 30 keV, 1 x 1015 cm-2 Ge+implants annealed at 750 C, as reported by Gutierrez [42].

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60 CHAPTER 4 SURFACE PROXIMITY EXPERIMENT 4.1 Overview In Chapter 3 an amorphous layer lapping experiment showed that increased surface proximity was not the key factor responsible for the defect dissolution observed in the 5 keV case. This finding again raises the argument of the role of the surface on excess interstitials. Does increasing the surface proximity to excess interstitials in the EOR region cause increased annihilation of these interstitials as proposed by Meekinson [47], Narayan [48], and Raman [49]? To approach this question from a low energy standpoint a 10 keV, 1 x 1015 Ge+ cm-2 implant was used in a continuation of the amorphous layer lapping experiment from Chapter 3. In this present experiment, the amorphous layer of a 10 keV implant was reduced to various depths and annealed at 750 C for 15 and 45 min and the subsequent extended defects and trapped interstitial concentrations are studied using PTEM. By reducing the amorphous layer thickness, the EOR region and the excess interstitials that reside there are brought in closer proximity to the surface. 4.2 Experimental Results The 10 keV implant forms a continuous amorphous layer 180 deep, as shown in Figure 3.11. The lapping procedure produced specimens with 155, 125, 80, and 40 . Figure 4.1 shows the XTEM images of the amorphous layer depths for the 155, 125, and

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61 40 specimens. The 80 specimen is the same one from Chapter 3, and its XTEM image is also shown in Figure 3.11. Figure 4.2 shows PTEM micrographs of the 155, 125, and 40 specimens annealed at 750 C for 15 and 45 min. The reader is referred to Figure 3.12 and 3.13 for the PTEM micrographs for the 180 and 80 specimens. The micrographs show that the defect population for the 155, 125, and 80 specimens are very similar to the control, 180 specimen. On the other hand, the 40 specimen’s PTEM micrographs look a little different. There is a smaller population of small clusters or dislocation loops and no clear {311} defects are visible. The defect densities and trapped interstitial concentrations for the five specimens are shown in Figure 4.3 and 4.4, respectively. The defect densities show no clear trend that can be correlated to increased surface proximity. The 155 and 125 specimens have higher defect density values than the 180 specimen after 15 min. However, after 45 min the 80 specimen is the only specimen with a higher defect density than the control. With the shallowest amorphous layer depth of 40 the smallest the smallest concentration of trapped interstitials exists at 15 min, but this trend is does not hold at 45 min. After 45 min, the 180 control specimen maintains the largest concentration of trapped interstitials, which may support that at longer annealing times increased surface proximity may be responsible for increased interstitial annihilation, but overall the defect densities and trapped interstitial concentrations are within the intrinsic 20 % error associated with this method of counting for all specimens and no clear effect of the surface can be determined. Figures 4.5 and 4.6 show the defect densities separated by the defect type, dislocation loops and {311} defects, respectively. An important note here is that no clear

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62 {311} morphology was observed in the 40 specimen PTEM micrographs, showing that at the shallowest amorphous layer depths {311} defects may not form. Figures 4.7 and 4.8 show the trapped interstitial concentrations separated by the defect type, dislocation loops and {311} defects, respectively. The average dislocation loops diameter is shown in Figure 4.9. It shows that there is a slight increase in defect diameter for 40 specimen, but it is with in the error. The error bars reflect the standard deviation associated with the averaging of the diameters. Figure 4.10 shows the average defect length for the specimens, showing no clear trend. 4.3 Discussion The overall trapped interstitial concentration with respect to amorphous layer depth is shown in Figure 4.11. It is clear in Figure 4.11 that there is no trend related to surface proximity on trapped interstitial concentration after 15 min of annealing time, until the shallowest depth of 40 when the amorphous layer depth approaches that of the average dislocation loop diameter. At the longer annealing time of 45 min, the trend does not hold further showing that the trapped interstitial population is independent of amorphous layer depth and therefore surface proximity. The lapping experiment in Chapter 3, which only considered the 180 and 80 specimens quantified the defect evolution over 360 min of annealing time. At the longer annealing times, there was no evidence that the increased surface proximity, roughly half of the interstitials diffusion distance between the two specimens in this case, had any effect on the interstitial concentration. Figure 3.13 shows that after 360 min, large, stable dislocation loops are present in both specimens and Figure 3.14 shows that their defect densities are comparable throughout the annealing times. The totality of these findings

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63 show that the model proposed by Omri [50] is still valid with amorphous layers very close to the surface, in that the surface does not have an effect on defect evolution of EOR damage. These results also shed doubt on the concept of an image force exerted by the free surface onto dislocation loops as suggested by Narayan and Jagannagham [48]. In this theory the image force is proportional to the ratio of defect size divided by its distance to the surface (F d/L). Narayan and Jagannagham theorized that dislocation loops with diameters greater than 2L will move to the surface and there will be a band of defect free crystal in that region. The results in this thesis show that dislocation loops exist very close to the surface and are not drawn to the surface by an image force. 4.4 Conclusion In this chapter the amorphous layer of a 10 keV, 1 x 1015 Ge+ cm-2 implant was lapped to thicknesses reduced from 180 to 165, 125, 80, and 40 . The specimens were then annealed at 750 C for 15 and 45 min. The defect populations for the control180 , 165, 125, and 80 specimens were all very similar to each other at both annealing times. However, the 40 specimen formed slightly larger dislocation loops and had a smaller interstitial population than the other specimens but was within the error of TEM analysis. After 45 min the control specimen had the highest concentration of trapped interstitials, which may be evident that the surface does have some effect after longer annealing times, but is not clear from the error.

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64 250 (a) (b) (c) Figure 4.1 XTEM images of 10 keV 1 x 1015 Ge+ cm-2 specimens whose amorphous layers were lapped to (a) 155 , (b) 125 , and (c) 40 . 40

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65 1000 (a)(b) (c)(d) (e)(f) Figure 4.2 PTEM micrographs of the 155 specimen at (a) 15 and (b) 45 min, the 125 specimen at (c) 15 and (d) 45 min, and the 40 at (e) 15 min and (f) 45 min upon annealing at 750 C.

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66 1x1091x10101x10111x10121800200022002400 180  155  125  80  40 Defect Density (#/cm2 )Time (s)Figure 4.3 Defect densities for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.

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67 1x10121x10131x10141x10151800200022002400 180  155  125  80  40 Trapped Interstitials (#/cm2 )Time (s)Figure 4.4 Trapped interstitial concentrations for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.

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68 1091010101110121800200022002400 180 -DL 155 -DL 125 -DL 80 -DL 40 -DLDislocation Loop Density (#/cm2 )Time (s)Figure 4.5 Dislocation loop component of the overall defect density for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.

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69 1x1091x10101x10111x10121800200022002400 180  -{311} 155  -{311} 125  -{311} 80  -{311}{311} Defect Density (#/cm2 )Time (s)Figure 4.6 {311} defect component of the overall defect density for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.

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70 10121013101410151800200022002400 180 -DL 155 -DL 125 -DL 80 -DL 40 -DLDL Trapped Interstitial (#/cm2 )Time (s)Figure 4.7 Dislocation loop component of the overall trapped interstitial concentration for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.

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71 10121013101410151800200022002400 180 -{311} 155 -{311} 125 -{311} 80 -{311}{311} Trapped Interstitials (#/cm2 )Time (s)Figure 4.8 {311} defect component of the overall trapped interstitial concentration for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.

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72 0 5 10 15 20 25 30 1800200022002400 180  155  125  80  40 Average Dislocation Loop Diameter (nm)Time (s)Figure 4.9 Average dislocation loop diameter for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.

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73 0 10 20 30 40 50 60 70 1800200022002400 180  155  125  80 Average {311} Length (nm)Time (s)Figure 4.10 Average {311} defect length for the 180, 155, 125, 80, and 40 specimens annealed at 750 C.

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74 1012101310141015050100150200 1800 s 2400 sTrapped Interstitial Concentration (#/cm2 )Amorphous Layer Depth ()Figure 4.11 Trapped interstitial concentration with respect to amorphous layer depth for the 10 keV Ge+ implant following a 750 C anneal for 15 and 45 min.

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75 CHAPTER 5 LOW TEMPERATURE ANNEAL EFFECT ON ELLIPSOMETRY ACCURACY FOR SHALLOW AMORPHOUS SILICON LAYERS 5.1 Overview As results show in the previous chapters of this thesis, ellipsometry measurements of shallow amorphous silicon layers are not very accurate when compared to highresolution transmission electron microscopy (HRTEM) results. The roughness of the amorphous crystalline interface may be a factor which introduces error in the ellipsometry measurements. To test this hypothesis, silicon wafers with shallow amorphous layers were annealed at 400 C for times ranging from 5 – 80 min in an attempt to smooth out the phase transition between the amorphous layer and the crystalline substrate. The efficacy of the low temperature anneal will be determined by comparing ellipsometry results at each annealing time to HRTEM results. The roughness of the amorphous/crystalline interface is then measured using HRTEM to correlate to the improved accuracy of the ellipsometry measurements. 5.2 Experimental Results Figure 5.1 shows the ellipsometry results compared to HRTEM measurements for the range of annealing times at 400 C. Ellipsometry measurements were performed at 0, 5, 10, 20, 40, 60, and 80 min, while HRTEM specimens were only imaged at 0, 40, and 80 min of annealing time. In the Figure 5.1 the average of three ellipsometry

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76 measurements are plotted with error bars representing the standard deviation of the averages. However, the ellipsometry measurements are very precise with typical standard deviations in the measurements < 1.0 making the error bars indistinguishable in the figure. The influence of the anneal is clearly shown to improve the accuracy of the ellipsometry measurements for the 5 and 10 keV case. For the 5 keV implant before the anneal, ellipsometry measured the amorphous layer depth to 144 . After a 20 min anneal, the measured value changed to 105 , an improvement of accuracy when compared to HRTEM of ~ 40%. The same trend is shown with the 10 keV case. For the 30 keV case, the accuracy associated with the ellipsometry measurements was already good and did not improve over time. At 400 C, HRTEM showed no regrowth of the amorphous layer up to the longest anneal time of 80 min for any of the implant energy conditions. The roughness of the amorphous/crystalline interface over the annealing time as measured by HRTEM is shown in Figure 5.2. The figure shows that roughness did decrease from the anneal, the mean peak-to-valley distance decreased. Figures 5.3 – 5.5 show HRTEM images of the amorphous layers for each implant energy. The images show that 400 C was too low to regrow the amorphous layer. 5.3 Conclusion This experiment showed that the accuracy of ellipsometry measurements of shallow amorphous silicon layers on silicon substrates can be improved by decreasing the roughness of the amorphous/crystalline interface. At 400 C, the amorphous layer was shown not to regrow measurably at times ranging from 5 – 80 min. The implications of

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77 this work may help researchers obtain more accurate amorphous silicon layer measurements using the quick, nondestructive technique of VASE.

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78 0 100 200 300 400 500 020406080100 5 keV-ellipsometry 10 keV-ellipsometry 30 keV-ellipsometry 5 keV-XTEM 10 keV-XTEM 30 keV-XTEMAmorphous Layer Depth ()Time (min)Figure 5.1 Comparison of amorphous layer depth measurements between ellipsometry and high resolution transmission electron microscopy following a 400 C anneal over time.

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79 0 10 20 30 40 50 020406080100 5 keV Roughness 10 keV Roughness 30 keV roughnessa/c InterfaceRoughness () Time (mins)Figure 5.2 Reduction in amorphous/crystalline interface roughness as measured by highresolution transmission electron microscopy following a 400 C anneal.

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80 100 (a) 100 (b) 100 (c) Figure 5.3 High-resolution transmission electron microscopy cross section images of 5 keV, 1 x 1015 Ge+ cm-2 implant annealed at 400 C for (a) 0 min, (b) 40 min, and (c) 80 min. surface a/c interface surface a/c interface surface a/c interface

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81 Figure 5.4 High-resolution transmission electron microscopy cross section images of 10 keV, 1 x 1015 Ge+ cm-2 implant annealed at 400 C for (a) 0 min, (b) 40 min, and (c) 80 min. (a) (c) (b) 100 100 100 surface surface surface a/c interface a/c interface a/c interface

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82 Figure 5.5 High-resolution transmission electron microscopy cross section images of 30 keV, 1 x 1015 Ge+ cm-2 implant annealed at 400 C for (a) 0 min and (b) 40 min. 100 (a) (b) 100 surface surface a/c interface a/c interface

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83 CHAPTER 6 CONCLUSIONS AND FUTURE WORK 6.1 5 keV Ge+ Defect Dissolution Study The small, unstable defects formed as a result of a 5 keV, 1 x 1015 Ge+ cm-2implant into silicon were shown to have a dissolution activation energy of 1.13 0.14 eV, which a value much less than the energies reported for dislocation loops (4.0 – 5.0 eV) [38] and {311} defects (3.8 .02 eV) [37]. The low activation energy may suggest that the defects dissolve by a glide process rather than a diffusion-controlled climb process. In the PTEM, the small defects show contrast consistent with dislocation loop morphology. However, these defects do not coarsen significantly like dislocation loops and dissolve very rapidly at high temperatures, as evident from the 1.13 eV activation energy. It was shown that the 5 keV defect dissolution is strongly implant energy dependent. A lapping experiment reduced the amorphous layer of 10 keV implant, which forms {311} defects and later stable dislocation loops, to less than that of the 5 keV implant’s amorphous layer and then the defect evolutions were compared. The 10 keVlapped specimen’s defect evolution strongly resembled that of the un-lapped 10 keV specimen, eliminating increased surface proximity as possible explanation for the defect dissolution observed for the 5 keV energy. It is proposed that the 5 keV implant energy’s small straggle and the low supersaturation of interstitials are responsible for forming this new defect morphology.

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84 The results from this experiment have created as many if not more questions than they have answered. Possible future work in this area is needed to determine at what specific implant energy does the unstable dislocation loops form. This can be determined by obtaining implant of the same dose at energies between 5 and 10 keV and study the defect evolution. Another potential experiment is needed to determine the effect of germanium in the silicon on forming the defects, whether there is a strain or chemical influence. In addition, the results may indicate that there is a lower supersaturation of interstitials in the EOR for the 5 keV case. An experiment that solves for the supersaturation of excess interstitials by measuring the diffusion enhancement of a buried boron marker would help determine if this was true. Another experiment that may warranted is to determine to defect dissolution activation energy for the dislocation loops observed in for the 10 keV case to see if they dissolve with the 4-5 eV activation energy, or if there is a step function decrease in the stability of defects as the implant energy is reduced. A final experiment that may be warranted is to see what effect the presence of boron may have on the defect evolution and what extent the dissolution, if any would have on TED and boron diffusion in general. 6.2 Surface Proximity Experiment This experiment lapped the amorphous layer of a 10 keV, 1 x 1015 Ge+ cm-2implant into silicon from 180 to depths of 165, 125, 80 and 40 for four different specimens. The defect population was analyzed following anneals at 750 C for 15 and 45 min to determine if there is a measurable effect from increased proximity to the wafer’s surface on excess interstitials in the EOR. It was determined that there is no clear

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85 influence of the surface in the annihilation of interstitials for amorphous layers 80 or thicker. The specimen with a 40 thick amorphous layer showed showed a slight smaller defect and interstitial population than the thicker amorphous layer specimens at 15 min, but the trend did not hold after 45 min. This may suggests that there is somewhat of a surface effect at distances roughly equal to the radius of a dislocation loop. 6.3 Low Temperature Anneal Effect on Ellipsometry Accuracy for Shallow Amorphous Silicon Layers A low temperature anneal, at 400 C, was shown to improve the accuracy of ellipsometry depth measurements for amorphous silicon layers on silicon substrates. Measurements were performed on 5, 10, and 30 keV Ge+ implants all at a dose of 1 x 1015 cm-2 with no anneal and then compared to samples that had been annealed for times from 5 – 80 min. The error in amorphous layer depths was reduced from about 40 % to practically 0% after 20 min of annealing time. High – resolution cross sectional transmission electron microscopy measured a reduction in the amorphous/crystalline interface roughness over time in the anneal, which was correlated to the improved accuracy of the ellipsometry measurements. 6.4 Implications of Findings The defects created by the 5 keV implant show that there is different regime of damage associated with low energy, amorphizing implants that is not understood very well at this point. The simple assumption that the surface acts to reduce the excess interstitial supersaturation was shown to be invalid, or at least not significant. It is clear that more investigations are necessary to construct an accurate model of extended defect

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86 evolution associated within this regime. This will assist the semiconductors industry in its drive to meet scaling requirements by more accurately predicting dopant diffusion profiles as the implant energy is also scaled.

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87 LIST OF REFERENCES 1.Plummer, J.D., M.D. Deal, and P.B. Griffin, Silicon VLSI Technology 2000, Upper Saddle River, NJ: Prentice Hall. p. 11. 2.Moore, G.E., Electronics, 1965. 38 (8): p. 114 117. 3.SIA. International Technology Roadmap for Semiconductor (Semiconductor Industry Assocation, San Jose, Ca 2002). 2002. 4.Liu, T.M. and W.G. Oldham, IEEE Elec. Dev. Lett., 1983. EDL-4 : p. 59-62. 5.Ruggles, G.A., Hong, S. -N., Wortman, J. J., Ozturk, M., Myers, E.R., Hren, J. J., and Fair, R. B., MCNC, Technical Report, 1989. TR89-04 6.Ozturk, M.C., Wortman, J. J., Osburn, C. M., Ajmera, A., Rozgonyl, G. A., Frey, E., Chu, W.-K., and Lee, C., Trans. Elec. Dev., 1988. 35 : p. 659-667. 7.Simonton, R.B., Nucl. Inst. and Meth. in Phys. Res. B, 1987. 21 : p. 490-492. 8.Csepregi, L., Kennedy, E. F., Mayer, J. W., and Sigmon, T. W., J. Appl. Phys., 1978. 49 (7): p. 3906. 9.Narayan, J., O.W. Holland, and B.R. Appleton, J. of Vac. Sci. and Tech., 1983. B 1. : p. 871. 10.Lindfors, C., Ph. D. Dissertaion, Department of Materials Science and Engineering. 2003, University of Florida: Gainesville, FL. 11.Hong, S.-N., Ruggles, G. A., Wortman, J. J., and Ozturk, M. C., IEEE Trans. on Elect. Dev., 1991. 38 : p. 476-486. 12.Claverie, A., Laanab, L, Bonafos, C., Bergaud, C., Martinez, A., and Mathiot, D., Nulc. Instr. and Meth. in Phys. Res. B, 1995. 96 : p. 202-209. 13.Borland, J.O. Low Temperature Shallow Junction Formation for 70nm Technology Node and Beyond in Materials Research Society Symposium 2002, Warrendale, PA: Materials Research Society. 14.Talwar, S., Felch, S., Downey, D., and Wang, Yun., IEEE Electr. Dev. Lett., 2000: p. 175-177.

PAGE 100

88 15.McCoy, S.P., Gelpy, J., Elliot, K., Gable, K. A., Jain, A., and Robertson, L. S.., 7th Int. Conf. on USJ, 2003: p. 104. 16.Current, M.I., Ion Implantation for Bipolar-CMOS Device Fabrication in Ion Implantation for Bipolar-CMOS Device Fabrication M.I. Current, Editor. 1997, Yorktown, NY: Ion Beam Press. 17.Mazzone, A.M., Phys. Stat. Sol. (A), 1989: p. 149. 18.Gyulai, J., K.S. Jones, and P. Petrik, Radiation Damage and Annealing in Silicon in Ion Implantation Science and Technology J.F. Ziegler, Editor. 2000, Ion Implantation Technology Co.: Yorktown, NY. p. 245. 19.Giles, M.D., J. of the Electro. Soc., 1991. 138 : p. 1160-1165. 20.Eaglesham, D.J., Stolk, P. A., Gossmann, H.-J., Haynes, T. E., and Poate, J. M., Nucl. Intr. and Meth. in Phys. Res. B, 1995. 106 : p. 191. 21.Pelaz, L., Gilmer, G. H., Jaraiz, M., Herner, S. B., Gossmann, H.-J., et al., Appl. Phys. Lett., 1998. 73 : p. 1421. 22.Holland, O.W., S.J. Pennycook, and G.L. Albert, Appl. Phys. Lett., 1989. 55 (24): p. 2503-2505. 23.Clark, M.H., M.S. Thesis, Department of Materials Science and Engineering. 2001, University of Florida: Gainesville, FL. 24.Williams, J.S., Nucl. Inst. and Meth. in Phys. Res. B, 1983. 209/210 : p. 219. 25.Poate, J.M. and J.S. Williams, in Ion Implantation and Beam Procesing J.S. Williams and J.M. Poate, Editors. 1984, Academic Press: New York, NY. p. 27. 26.Csepregi, L., L. Mayer, and T.W. Sigmon, Phys. Lett., 1975. 54A : p. 157. 27.Licoppe, C. and Y.I. Nissim, J. Appl. Phys., 1986. 59 (2): p. 432-438. 28.Olson, G.L., Mat. Res. Soc. Symp. Proc, 1985. 35 : p. 25. 29.Jones, K.S., Ph.D. Dissertation, Department of Materials Science and Minerals Engineering. 1987, University of California at Berkeley: Berkeley. p. 133. 30.Jones, K.S., S. Prussin, and E.R. Weber, Appl. Phys. A, 1988. 45 : p. 1-34. 31.Prussin, S. and K.S. Jones, J. of the Electro. Soc., 1990. 137 : p. 1912-1914. 32.Mauduit, B.D., Lanaab, L., Berguard, C., Faye, M., Martinez A., and Claverie, A., Nucl. Inst. and Meth. in Phys. Res. B, 1994. 84 : p. 190-194.

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89 33.Robertson, L.S., Jones, K. S., Rubin, L. M., and Jackson, J., J. Appl. Phys., 2000. 87 : p. 2910-2913. 34.Jones, K.S., "Annealing Kinetics of Ion Implanted Damage in Silicon," (Presentation, University of Florida, 2001). 35.Li, J. and K.S. Jones, J. Appl. Phys., 1998. 85 : p. 8137-8144. 36.Eaglesham, D.J., Stolk, P. A., Gossmann, H.-J., Haynes, T. E., and Poate, J. M.., Appl. Phys. Lett., 1994. 65 (18): p. 2305-2307. 37.Stolk, P.A., Gossmann, H.-J., Eaglesham, D. J., Jacobson, D. C., Rafferty, C. S., Gilmer, G. H., et al., J. Appl. Phys., 1997. 81 (9): p. 6031-6049. 38.Siedel, T.E., Lischer, C. S., Pai, R. V., Knoell, D. M., and Jacobson, D. C., Nucl. Inst. and Meth. in Phys. Res. B, 1985. 7/8 : p. 251. 39.Lampin, E., V. Senez, and A. Claverie, J. Appl. Phys., 1999. 85 : p. 8137-8144. 40.Liu, J., M.E. Law, and K.S. Jones, Solid-State Electr. 1995. 38 : p. 1305-1312. 41.Bonafos, C., D. Mathiot, and A. Claverie, J. Appl. Phys., 1998. 83 : p. 3008-3017. 42.Gutierrez, A.F., M.S. Thesis, Department of Materials Science and Engineerin g 2001, University of Florida: Gainesville. 43.Eaglesham, D.J., Agarwal, A., Haynes, T. E., Gossmann, H.-J., Jacobson, D. C., and Poate, J. M., Nucl. Inst. and Meth. in Phys. Res. B, 1996. 120 : p. 1-4. 44.Jain, S.C., Schoenmaker, W., Lindsay, R., Stolk, P. A., Decoutere, S., willander, M., and Mass, H. E., Appl. Phys. Rev., 2002. 91 (11): p. 8919-8941. 45.Jones, K.S., Zhang, L. H., Krishamoorthy, V., Law, M. E., Simmons, P., Chi, P., Rubin, L.,and Elliman, Appl. Phys. Lett., 1996. 68 : p. 2672-2674. 46.Robertson, L.S., Law, M. E., Jones, K. S., Rubin, L., Jackson, J., Chi, P., and simons, D. S., Appl. Phys. Lett., 1999. 75 : p. 3844-3846. 47.Meekinson, C.D., Institute of Physics Conference Series, 1991. 117 : p. 197. 48.Narayan, J. and K. Jagannadham, J. Appl. Phys., 1987. 62 : p. 1694. 49.Raman, R., Law, M. E., Krishnamoorthy, V., and Jones, K. S., Applied Physcis Letters, 1999. 74 (11): p. 1591-1593. 50.Omri, M., Bonofos, C., Claverie, A., Nejim, A., Cristano, F., Alquier, D., Martinez, A., and Cowern, N. E. B., Nulc. Instr. and Meth. in Phys. Res. B, 1996. 120 : p. 5-8.

PAGE 102

90 51.Ganin, E. and A. Marwick, Mat. Res. Soc., 1989. 147 : p. 13-18. 52.Williams, D.B. and C.B. Carter, Transmission Electron Microscopy 1st ed. Vol. 3. 1996, New York: Plenum Press. p. 8. 53.Law, M.E., Florida Object Oriented Process Simulator 1999, Gainesville, FL: Universtity of Florida. 54.Bharatan, S., Ph.D. Dissertation, Department of Materials Science and Engineering. 1999, University of Florida: Gainesville, FL. 55.Obradovic, B., Wang, G., Chen, Y. Li, D., Snell, C., and Tasch, A. F. UTMarlowe 5.0 1999, University of Texas, Austin; Los Alamos National Labratory. 56.Li, J.-H., Law, M. E., Jasper, C., and Jones, K. S., Mat. Sci. in Semi. Proc., 1998. 1 : p. 99-106. 57.Herner, S.B., Gila, B. P., Jones, K. S., Gossmann, H.-J., Poate, J. M., and Luftman, H. S., J. of Vac. Sci. and Tech. B, 1996. 14 : p. 3593. 58.Edington, J.W., The Operation and Calibration of the Electron Microscope 1974, Gloeilampenfabrieken: Philips. 59.Desmond, F.J., Kalbitzer S., Mannsperger H., and Damjantschitsch, H., Phys. Lett. 93A, 503 (1983). 60.Frank, W., Gosele, U., Mehrer H., and Seger A., Diffusion in Crystalline Solids. 1984, New York: Academic Press.

PAGE 103

91 BIOGRAPHICAL SKETCH I was born in 1978 on a U.S. Army base in Heidelberg, Germany. After graduating from Oviedo High School in Oviedo, FL, in 1997, I attended the University of Florida receiving my B.S. in materials science and engineering in May 2002. During my undergraduate coursework I played for the University of Florida lacrosse club team and interned with Texas Instruments in Dallas, TX, for seven months in 2000. In the fall of 2002 I began my graduate studies at the University of Florida in the SAWMP Group. After graduation I plan to obtain a rewarding engineering position.


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DISSOLUTION AND SURFACE PROXIMITY EFFECTS OF LOW ENERGY,
AMORPHIZING GERMANIUM IMPLANTS INTO SILICON




















By


ANDREW C. KING


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REOUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE


UNIVERSITY OF FLORIDA


2003




































Copyright 2003

by

Andrew C. King







































For Mom, Dad and Devin

















ACKNOWLEDGMENTS

I would first like to thank my advisor, Dr. Kevin Jones, for his guidance, patience,

commitment to science, and sense of humor. I would also like to thank Dr. Mark Law for

answering all of my questions and giving me excellent suggestions throughout my

research. Appreciation is also given to Dr. David Norton for support on my committee. I

am sincerely grateful to Mark Clark, Tony Saavedra, Andres Gutierrez, Russ Robison,

Ljubo Radic, and Carrie Ross for taking time to help me. Without their help I would not

have been able to complete this work. Finally, I would like to thank everybody in the

SWAMP Group for their friendship and support. The Semiconductor Research

Corporation supported this work.



















TABLE OF CONTENTS



ACKNOWLEDGMENTS .................. .................. ................ ...........

LIST OF TABLES ................. ................. ................ .........

LIST OF FIGURES ................ .............. ................ .........

ABSTRACT ................ ............... .............. ...........

CHAPTER

1 INTRODUCTION. ........._____ ........._____ ........._____ ..........


1.1 Background and Motivation ........................................ 1
1.2 IonImplantation ........................................ 4
1.3 Solid Phase Epitaxy .................. .................. .................. ......
1.4 End-of-Range Damage ........................................ 9
1.4. 1 Defect Evolution. .................. .................. .................. ......
1.4.2 Transient Enhanced Diffusion............................... 12
1.5 Effect of the Free Surface on End-of-Range Damage ............... ............... .. 14
1.6 Scope and Approach of this Study .............. .................. ............... ....


2 EXPERIMENTAL AND DATA EXTRACTION PROCEDURES .........____ ...... 18


2.1 Transmission Electron Microscopy.............................. 18
2.1.1 Plan-view Transmission Electron Microscopy Sample Preparation ......... 19
2.1.2 Cross-Section Transmission Electron Microscopy Sample Preparation... 20
2.1.3 Extraction of Defect Parameters from PTEM ................... ................... ....22
2.1.3.1 Extraction of defect densities from PTEM ................... .................. 22
2.1.3.2 Extraction of trapped interstitial concentrations from PTEM........ 23
2.2 Variable Angle Spectroscopic Ellipsometry ................... ................... ................ 24
2.3 UT Marlowe ................... ................... ................... ........
2.4 5 keV Ge' Defect Dissolution Study................................... 26
2.4.1 5 keV Defect Dissolution Activation Energy Experiment. ................... .... 27
2.4. 2 Surface Lapping Experiment. ................... ................... ................... .......
2.6 Surface Proximity Experiment.............................. 29
2.7 Ellipsometry Experiment ................... ................... ................... .........














3 5 keV Ge' DEFECT DISSOLUTION STUDY................................... 31

3.1 Overview................................ 31
3.2 Defect Dissolution Activation Energy.................................. 32
3.2.1 TEM Results................................. 32
3.2.2 Extraction of Defect Dissolution Activation Energy. ............... ............ 34
3.3 Surface Lapping Experiment ........................................ 35
3.3.1 Amorphous Layer Lapping Results ............... ............... ............... 35
3.3.2 Defect Evolution............................... 36
3.4 UT-Marlowe Simulations ........................................ 36
3.4. 1 Simulation Results ................... ................... ................... ......
3.4.2 NEI calculation............................. 37
3.5 Discussion ................... ................... ................... ........
3.6 Conclusion ........................................ 39



4 SURFACE PROXIMITY EXPERIMENT.............................. 60

4.1 Overview................................ 60
4. 2 Experimental Results ................... ................... ................... ........
4. 3 Discussion ................... ................... ................... .........
4.4 Conclusion ........................................ 63



5 LOW TEMPERATURE ANNEAL EFFECT ON ELLIPSOMETRY ACCURACY
FOR SHALLOW AMORPHOUS SILICON LAYERS ........................................ 75

5.1 Overview................................ 75
5.2 Experimental Results ................... ................... ................... .......
5.3 Conclusion ........................................ 76



6 CONCLUSIONS AND FUTURE WORK.................................... 83


6.1 5 keV Ge' Defect Dissolution Study................................... 83
6.2 Surface Proximity Experiment.............................. 84
6.3 Low Temperature Anneal Effect on Ellipsometry Accuracy for Shallow
Amorphous Silicon Layers ........................................ 85
6.4 Implications of Findings ................... ................... ................... ........



LIST OF REFERENCES ........................................ 87

BIOGRAPHICAL SKETCH .........____ .........____ .........____ ..........


















LIST OF TABLES


1.1 2002 ITRS doping technology requirements ................... ................... ................... .4

3.1 Time range where defect dissolution occurs at each annealing temperature as
observed by PTEM. ........................................ 33

3.2 Ellipsometry measurements of amorphous layer thickness for the 5, 10, and 10
keV lapped specimens. ........................................ 36
















LIST OF FIGURES


Fieure

1.1 Cross-sectional schematic of a MOSFET. ................... ................... ................... ......

1.2 EOR damage created from an amorphizing implant. ........................................ 10

1.3 Defect evolution of excess interstitials resulting from ion implantation into silicon
and subsequent annealing ........................................ 11

1.4 Defect evolution reported by Gutierrez for Ge' implanted at energies of 5, 10, and
30 keV at a constant dose of 10'5 cm~2 annealed at 750 "C. ................................... 13

3.2 PTEM micrographs of 5 keV Ge+, 1 x 10'5 cm~2 Ge+ annealed at 725 "C for (a)15
min, (b) 60 min, (c) 65 min, (d) 70 min, and (e) 80 min. ....................................... 40

3.2 PTEM micrographs of 5 keV Ge+, 1 x 10'5 cm~2 Ge+ annealed at 750 "C for (a) 5
min, (b) 15 min, (c) 45 min, (d) 60 min, and (e) 65 min. ....................................... 41

3.3 PTEM micrographs of 5 keV Ge+, 1 x 10'5 cm~2 Ge+ annealed at 775 "C for(a) 15
min, (b)35 min, (c) 40 min, and (d) 45 min. ........................................ 42

3.4 PTEM micrographs of 5 keV Ge+, 1 x 10'5 cm~2 Ge+ annealed at 825 "C for(a) 15
min, (b) 30 min, and (c)35 min. ........................................ 43

3.5 PTEM micrographs of 5 keV Ge+, 1 x 10'5 cm~2 Ge+ annealed at 875 "C for (a) 5
min, (b) 10 min, and (c) 15 min. ........................................ 44

3.6 PTEM micrograph of 5 keV Ge+, 1 x 10'5 cm~2 Ge+ annealed at 775 "C for 35 min
imaged at the g040 condition. ........................................ 45

3.7 Defect density trends for 5 keV, ix 10'5 Ge+ cm~2 implant over time annealed at
725, 750, 775, 825, and 875 "C. ................... ................... ................... .....

3.8 Trapped interstitial trends for 5 keV, ix 10'5 Ge+ cm~2 implant over time annealed
at 725, 750, 775, 825, and 875 "C. ........................................ 47

3.9 Average defect diameter over time for the 5 keV, 1 x 10'5 Ge+ cm~2 implant
annealed at 725, 750, 775, 825, and 875 "C. ........................................ 48









3.10 Defect dissolution rates versus inverse temperature, plotted in Arrhenius form. The
trend is show as a least square exponential curve fit. ................... ................... ....... 49

3.11 High-resolution cross section TEM micrographs of the amorphous layer thickness
for (a) 10 keV, (b) 10 keV-lapped, and (c) 5 keV samples................................. 50

3.12 PTEM micrographs of the 10 keV Ge+, 1 x 10'5 cm~2 Ge+ control implant annealed
at 750 "C for (a)5 min, (b) 15 min, (c) 30 min, (d) 45 min, (e) 60 min, and (f) 360
min. ........................................ 51

3.13 PTEM micrographs of the 10 keV Ge+, 1 x 10'5 cm~2 Ge+ implant whose amorphous
layer was polished to 80 ~i and annealed at 750 "C for (a) 5 min, (b) 15 min, (c) 30
min, (d) 45 min, (e) 60 min, and (f) 360 min. ................... ................... .................. 52

3.14 Defect evolution of the 5 keV, 10 keV, and 10 keV-lapped specimens annealed at
750 "C. ........................................ 53

3.15 UT-Marlowe.rbs output for the 5 keV, 1 x 10'5 Ge+ cm~2 implant......................... 54

3.16 UT-Marlowe simulated interstitial and vacancy profiles for the 5 keV, 1 x 10'5 Ge+
cm~2 implant. ........................................ 55

3.17 UT-Marlowe. rbs output for the 10 keV, 1 x 10'5 Ge+ cm~2 implant. ................... ... 56

3.18 UT-Marlowe simulated interstitial and vacancy profiles for the 5 keV, 1 x 10'5 Ge
cm~2 implant. ........................................ 57

3.19 NEI profile for the 5 and 10 keV, 1 x 10'5 Ge+ cm~2 implants................................ 58

3.20 Trapped interstitial concentrations from 5, 10 and 30 keV, 1 x 10'5 cm~2 Ge
implants annealed at 750 "C, as reported by Gutierrez. ........................................ 59

4.1 XTEM images of 10 keV 1 x 10'5 Ge+ cm~2 specimens whose amorphous layers
were lapped to (a) 155 ~i, (b) 125 ~i, and (c) 40 ~i. ........................................ 64

4.2 PTEM micrographs of the 155 ~i specimen at (a) 15 and (b) 45 min, the 125 ~i
specimen at (c) 15 and (d) 45 min, and the 40 ~i at (e) 15 min and (f) 45 min upon
annealing at 750 "C. ........................................ 65

4.3 Defect densities for the 180, 155, 125, 80, and 40 ~i specimens annealed at 750 "C.66

4.4 Trapped interstitial concentrations for the 180, 155, 125, 80, and 40 ~i specimens
annealed at 750 "C. ................... ................... ................... ........

4.5 Dislocation loop component of the overall defect density for the 180, 155, 125, 80,
and 40 ~i specimens annealed at 750 "C. ................... ................... ................... ....










4.6 C3 1 1) defect component of the overall defect density for the 180, 155, 125, 80, and
40 ~i specimens annealed at 750 "C. ........................................ 69

4.7 Dislocation loop component of the overall trapped interstitial concentration for the
180, 155, 125, 80, and 40 ~i specimens annealed at 750 "C. ................... ............... 70

4.8 C3 1 1) defect component of the overall trapped interstitial concentration for the 180,
155, 125, 80, and 40 ~i specimens annealed at 750 "C. ........................................ 71

4.9 Average dislocation loop diameter for the 180, 155, 125, 80, and 40 ~i specimens
annealed at 750 "C. ................... ................... ................... ........

4.10 Average C311) defect length for the 180, 155, 125, 80, and 40 ~i specimens
annealed at 750 "C. ................... ................... ................... ........

4.11 Trapped interstitial concentration with respect to amorphous layer depth for the 10
keV Ge' implant following a 750 "C anneal for 15 and 45 min. ............................ 74

5.1 Comparison of amorphous layer depth measurements between ellipsometry and
high resolution transmission electron microscopy following a 400 "C anneal over
time. ........................................ 78

5.2 Reduction in amorphous/crystalline interface roughness as measured by high-
resolution transmission electron microscopy following a 400 "C anneal. .............. 79

5.3 High-resolution transmission electron microscopy cross section images of 5 keV, 1
x 10'5 Ge+ cm~2 implant annealed at 400 OC for (a) 0 min, (b) 40 min, and (c) 80
min. ........................................ 80

5.4 High-resolution transmission electron microscopy cross section images of 10 keV, 1
x 10'5 Ge+ cm~2 implant annealed at 400 OC for (a) 0 min, (b) 40 min, and (c) 80
min. ........................................ 81

5.5 High-resolution transmission electron microscopy cross section images of 30 keV, 1
x 10'5 Ge+ cm~2 implant annealed at 400 OC for (a)O min and (b) 40 min.............. 82

















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

DISSOLUTION AND SURFACE PROXIMITY EFFECTS OF LOW ENERGY,
AMORPHIZING GERMANIUM IMPLANTS INTO SILICON

By

Andrew C. King

December 2003

Chair: Kevin S. Jones
Major Department: Materials Science and Engineering

As CMOS device dimensions are scaled laterally to increase the density of

transistors per die, they also must be scaled vertically. Thus, it becomes increasingly

important to understand the interactions of the silicon surface with point defects.

Preamorphization is a common method for preventing channeling of implanted ions deep

into the silicon crystal. Reducing the preamorphization implant energy effectively places

the end-of-range (EOR) damage closer to the surface. How the EOR damage evolves has

a critical effect on the amount of dopant diffusion that occurs. Speculation remains over

how the excess interstitial population in the EOR is affected by the surface as the

preamorphization energy is reduced.

The first experiment in this thesis characterizes the damage created by a 5 keV, 1 x

10'5 Ge+ cm~2 implant into silicon, which evolves much differently than higher energy

implants. Using plan-view transmission electron microscopy, it was found that small,

unstable dislocation loops formed in the EOR with a dissolution activation energy of 1.13










f 0.14 eV. The defects were shown not to coarsen significantly, but ratherjust decrease

in number before the rapid dissolution took place. A surface lapping experiment showed

that the defect dissolution energy is not attributed to the increased proximity of the

surface, but was in fact implant energy related. The amorphous layer of a 10 keV, 1 x

10'5 Ge+ cm~2 implant, which forms C311) defects and later stable dislocation loops, was

reduced to less than that of the 5 keV implant and annealed at 750 "C. The defect

evolutions were then quantified for the 5, 10, and 10 keV-lapped samples. It was found

that the defect evolution for the 10 keV-lapped specimen strongly resembles that of the

control, un-lapped 10 keV sample.

In the second experiment in this thesis, the effect of surface proximity for shallow

amorphous layers was further studied. The amorphous layer of a 10 keV, 1 x 10'5 Ge

cm~2 implant was reduced from 180 ~i to depths of 155, 125, 80, and 40 ~i. The samples

were then annealed at 750 "C for 15 and 45 min, and the defect populations were

analyzed using plan-view transmission electron microscopy. Results show that increased

surface proximity on amorphizing implants does not cause a significant reduction in the

trapped interstitial concentration even down to amorphous layer depths of 40 ~i.

The final experiment examines the effect of a low temperature anneal on the

accuracy of ellipsometry measurement of shallow amorphous silicon layers on the

surface of crystalline silicon substrates. It was shown that a 400 "C anneal significantly

improves the accuracy of the ellipsometry measurements and does not regrow the

amorphous layer. A reduction in the amorphous/crystalline interface roughness from the

anneal was correlated to the increase in accuracy.

















CHAPTER 1
INTRODUCTION



1.1 Background and Motivation

Modem day computing power is based on the integrated circuit (IC), which is a

large number oftransistors, resistors, capacitors, and other devices wired together on a

the same substrate to perform a designated circuit function. The invention of the IC is

attributed to Jack Kilby of Texas Instruments and Robert Noyce of Fairchild

Semiconductor in 1959 [1]. Since then, the number of components on a typical IC has

gone from the tens to the tens of millions.


In 1965 Gordon Moore [2], an executive at Intel, made the observation that in

order for the semiconductor industry to meet market demands, the number of transistors

on the IC would have to double every 1 to 2 years. This observation has since come to

be known as "Moore's Law," and has served as the industry trend and key indicator in

predicting cutting-edge semiconductor technology for the past 30 years.


In the late 1990's experts in the semiconductor industry from Europe, Japan,

Korea, Taiwan, and the USA developed the International Technology Roadmap for

Semiconductors (ITRS) [3], which presents a semiconductor industry-wide consensus on

the research and development needs for the industry over a 15 year time span. The

primary focus of the ITRS is to maintain the continued scaling trends of ICs that require

increasing the packing density, speed, and power efficiency of devices on the scale of










Moore's Law. These trends are ultimately responsible for decreasing the cost-per-

function of ICs, which has led to significant improvements in productivity and quality of

life through the proliferation of computers and other electronic devices.


The metal-oxide-semiconductor field-effect-transistor (MOSFET) is the basic

building block of the IC (Figure 1). The scaling trends established by the ITRS require

reducing the feature size of the MOSFET with every new generation of devices to meet

performance requirements. One of the most challenging problems of device scaling is

forming highly doped, ultra-shallow source/drain junctions and extensions with low sheet

resistance. With each successive technology node, the junction depths are required to

scale with the gate length to avoid short channel effects. These effects result when the

drain's electric field penetrates through the channel region and affects the potential

barrier between the source and the channel regions. These effects diminish the ability of

the gate to control the channel charge.


ITRS also requires increasingly higher doping concentrations of the junctions to

account for the inverse relationship between sheet resistance and junction depth.

Shallower junctions will ultimately have higher resistivity. In physical terms, a deeper

junction has a larger volume and therefore can incorporate a larger dose of electrically

active carriers than a shallow junction with the same concentration, thus achieving a

lower sheet resistance. Table 1 shows the 2002 ITRS junction-doping requirements

projected to the 2016 technology node.


Currently ion implantation is the preferred method of forming shallow junctions

due its precision in controlling dopant concentrations and profiles. Implanting arsenic

into the crystalline silicon forms shallow n+-p junctions with relative ease due to arsenic's









heavy atomic mass and small projected range. However, shallow p -n junctions are

difficult to form due to the p-type dopant's small atomic mass, boron. When boron is

implanted into silicon, channeling of the boron ion occurs. This results in a dopant

profile channeling tail and a much deeper junction [4].

PHYSICAL,
GATE LENGTH
SSIDE WALL.
SSPACER
GATE
GATE
OXIDE'

CHANNEL


DRAIN SOURCE/DR;AIN
EXTENSION EXTENSIONS
DEPTH

Figure 1.1 Cross-sectional schematic of a MOSFET.


Amorphizing the silicon substrate by implanting isoelectric species such as silicon

[5] or germanium [6] prior to dopant implantation (preamorphization) has been shown to

reduce the channeling tail of boron. In fact, the channeling tail can be completely

eliminated if the entire boron profile is within the amorphous region [7]. Subsequent

recrystallization of the amorphous layer by solid phase epitaxy (SPE) [8] has been found

to result in high dopant activation as well as reduced diffusion of dopant [9, 10].

The major drawback to the preamorphization technique is the formation of

extended defects below the original amorphous/crystalline (oc/c) interface following SPE.

These defects are referred to as end-of-range (EOR) damage since they reside at the end

of the projected range of the implanted species. EOR damage can have detrimental










affects on junction performance. If the EOR region is located within the depletion region

of the device, large leakage currents will result [11]. Also, the supersaturation of

interstitials in the EOR region can lead to transient enhanced diffusion (TED) [12] of the

dopant profile, resulting in a deeperjunction.


Table 1.12002 ITRS in uirements 3
Year of Production 2001 2004 2007 2010 2013 2016

Technology Node (nm) 130 90 65 45 32 22
MPU, Functions per chip (Gbits) 0. 54 1.07 4.29 8. 59 34.C 68.72
Physical Gate Length (nm) 65 37 25 18 13 9
Contact X, (nm) 48-95 27-45 18-37 13-26 10-1 7-13
Drain extension X, (nm) 27-45 15-25 10-17 7-12 5-9 4-6
Max Drain extension Rs (PMOS) 400 660 760 830 940 1210
(sq.)
Max Drain extension Rs (NMOS) 190 310 360 390 440 570
(sq.)
Extension lateral abruptness 7.2 4.1 2.8 2.0 1.4 1.0
(nm/decade)


Despite the difficulties presented by EOR damage, preamorphization is a

necessary process step in novel dopant activation techniques that are being developed to

meet future ITRS technology nodes, such as solid phase epitaxy regrowth (SPER) [13],

laser thermal processing (LTP) [14], and flash lamp annealing [15]. Therefore it

important to understand the parameters involved in EOR damage evolution in order

accurately model dopant diffusion in silicon, which is a key factor in the continued

scaling ofjunctions.


1.2 Ion Implantation

Ion implantation is the primary technology for introducing impurities into

semiconductors to form devices and IC circuits. The ion implantation process is highly

flexible in the selection of dopant species, in choosing the spatial location to implant the










species, and in its superior concentration profile control. The process consists of

accelerating a beam of ions with sufficient energy to penetrate the target material.

As the incident ions enter the substrate they under go two stopping processes,

nuclear and electronic stopping [16]. Nuclear Stopping (S,) occurs from collisions of the

incident ion and the core electrons of the substrate atoms. S, interactions usually involve

an energy transfer during the collision between the ions and the atoms large enough to

displace the substrate atoms from their lattice positions. This can lead to a damage

collision cascade where many nuclear events can be produced by one primary ion. The

large amount of damage produced by collision cascades from S, can form continuous

amorphous layers in silicon substrates. Electronic stopping (S,) arises from collisions

between the incident ions and the outer electron shells of the substrate atoms. S,

interactions are similar to a drag force exerted on the implanted ions, transfer much less

energy, and produce negligible damage to the substrate.

The depths that the ions reach, or travel before they come to rest, in the target

substrate follows an approximate Gaussian form, where the peak of the distribution

corresponds to the most probable projected ion range. This is referred to as the projected

range (Rp), and the standard deviation of the distribution is called the straggle (~Rp). Rp

depends mainly on the energy and mass of the implanted species, while ~Rp depends on

the ratio of the mass of the implanted ion to the mass of the substrate atom.

During the ion implantation process, combinations ofinterstitial and vacancy

pairs are created. These are called Frenkel pairs. A Frenkel pair is created during an

individual ion collision event when the implanted ion collides with a lattice atom and

knocks it out of position. The removed atom becomes an interstitial while a vacancy is










created in the lattice position where the atom was removed. Additionally, if the

interstitial produced by the initial collision has sufficient energy, it may knock off other

atoms from lattice position creating additional Frenkel pairs in a multiplying nature.

Mazzone [17] used Monte Carlo calculations to show that the vacancies and

interstitials in the Frenkel pairs reside at different regions of the ion-depth profile. The

calculations predict that the forward peaking nature of the momentum of an incoming ion

produces a vacancy-rich zone in the region extending from the surface down to about

0.8Rp while between Rp and 2Rp, there should be a interstitial-rich zone. Due to non-

conservative nature of ion implantation, meaning that substitution atoms are introduced

into the lattice in far excess of available unoccupied lattice sites, the interstitial

component dominates the point defect distribution for low to medium implant energies (<

a few hundred keV) [18].

During a post-implant anneal in non-amorphized silicon, excess interstitials in the

lattice have been observed due the damage created during implantation [19-21]. During

annealing, vacancies are recombined with interstitials, but the non-conservative nature of

implantation creates excess interstitials. Giles [19] proposed the "+1" model, which

suggests that one interstitial, is created for each implanted ion during annealing and their

diffusion is limited to either the surface or further into the substrate.

During the ion implantation process, the irradiation of silicon can produce a

crystalline-to-amorphous phase transition if a critical dose for amorphization is achieved.

As mentioned previously, amorphizing silicon eliminates channeling of boron, and the

SPE regrowth of the amorphous layer enhances electrical activation of the implanted

dopant. The amorphization phase transition begins when sufficient irradiation from the










ion beam produces a defected crystalline lattice with the same free energies as an

amorphous silicon network.

Holland et al. [22] proposed a model that considers the amorphization of silicon as

critical-point phenomenon where the onset of amorphization leads to a cooperative

behavior among various defects types that results in a greatly accelerated transition.

Through their experiment with silicon self implants, a dose dependence of damage

production was determined with two different regimes: an initial regime where growth is

constrained by the formation simple point defects, followed by a regime of unconstrained

growth which results in the complete amorphization of the lattice. In the latter regime,

the onset of amorphization is precipitated by the rapid growth of damage that results from

a cooperative mechanism where amorphous regions preferentially sink interstitial point

defects which promotes more damage and leads to further amorphization.

Another mechanism of amorphization from ion implantation proceeds by gradual

changes occurring to the lattice over a range of doses. The process starts by the

formation of small, isolated pockets of amorphous material. As the dose increases the

pockets increase in number and overlap until eventually all the pockets have overlapped

and a continuous amorphous layer is present.

Typically amorphization of silicon is done with 28Si+ or 73Ge+ [6] since they are

isoelectric and do not interfere with electrically active dopants. Clark [23] studied the

effect of increasing the preamorphizing species' mass on the formations of ultra-shallow

junctions. It was determined that ions with larger atomic mass units are more efficient in

amorphizing silicon, which results in less interstitial injection in the EOR region

following SPE and less TED.












1.3 Solid Phase Epitaxy

The recrystallization mechanism of implanted amorphized silicon is called solid

phase epitaxy (SPE). SPE proceeds epitaxially on an underlying crystalline silicon

substrate. It is layer-by-layer laminar growth with atomic step edges as growing sites.

Typical SPE regrowth begins to occur at temperatures as low as -400-450 OC [24, 25]

and on up to temperatures just below the melting point of amorphous silicon with

regrowth rates dramatically increasing for increasing temperature. This is due to the fact

that SPE recrystallization rates follow and Arrhenius expression determined by Csepregi

et al. [8, 26]


.=..i~i 1.1


where v is the regrowth velocity, v, is the pre-exponential factor, E, is the activation

energy, k is Boltzmann's constant, and T is temperature in degrees Kelvin. Their work

also showed that the orientation of the silicon also heavily determines recrystallization

rates, reporting that <100> silicon regrows at a rate about 3 times faster than <110>

silicon and about 25 times faster than <111> silicon. Experiments on determining the

activation energy and pre-exponential factor have produced varied results. Licoppe and

Nissim [27] report values of 3x108 cm/sec and 2.7 eV for v, and E, respectively, while

Olson [28] found values of 3.07x108 cm/sec and 2.68 eV for v, and E, respectively. In

general, amorphous silicon regrows at a rate of 10 ~i i s at 600 OC [13].

After the amorphous layer has regrown, the resulting recrystallized material is

largely defect free and better quality than irradiated silicon that was not amorphized. The

SPE process also produces high electrical activation of dopants because during regrowth










impurities may become trapped onto substitution lattice sites allowing metastable

conditions to be met. However, after regrowth the region just below the original

amorphous/crystalline interface will have a supersaturation ofinterstitials and will

probably form extended defects depending on the annealing conditions.




1.4 End-of-Range Damage

The regrowth of amorphized silicon leaves a supersaturation of interstitials in the

region just beyond the original amorphous/crystalline interface, which consolidates into

extended defects during annealing. There are two sources of the interstitials that lead to

the formation the extended defects. The first source is transmitted ions, which are the

ions that come to rest below the amorphous/crystalline interface. The second source is

the recoiling of excess interstitials deeper into the material due to the forward momentum

of the ion beam. Jones et al. [29, 30] classifies this form of ion implantation induced

damage as Type II or end-of-range (EOR) damage. The concentration of interstitials in

the EOR region is sufficient to form both dislocation loops and C311) defects, which are

described below. One interesting aspect of EOR damage is that the concentration of

defects is not strongly dependant on dose [29, 30], but does change with implant energy

[6, 31].

Dislocation loops in the EOR region are either C111) faulted Frank dislocation

loops, or C111) perfect prismatic dislocation loops [32]. These loops are metastable

defects consisting ofinterstitial silicon atoms. C311) defects, or rod-like defects, consist

of silicon interstitials condensed on the C31 1) habit plane and elongated in the [1 10]

direction.






































Figure 1 2 EOR damage created fr-om an amorphizng implant [30]


1.4.1 Defect Evolution


The excess mterstitals m the EOR created by the lon implantation process are

mobile at lugh temperatures, and undergo extensive diffusion durmg annealmg where

they can coalesce mto either dislocation loops or (311)'s m order to consenre free

energy Robertson et al [33] used transmission electron rmcroscopy (TEM) to observe

that EOR defects formed by a 20 keV 1 x 10'1/ cm2 Sri implant undergo an evolution

durmg annealmg at 750 oC over an extended penod of time (10-370 min) The study

showed that after 10 rmmute, both (311) defects and small dislocation loops are present,









and as annealing times progressed the {311} defects followed two evolutionary

pathways, faulting to form dislocation loops or dissolving releasing interstitials. Figure

1.3 shows a defect evolution tree from Jones [34].


Figure 1.3 Defect evolution of excess interstitials resulting from ion implantation into
silicon and subsequent annealing [34].

The {311} defect evolution shows that compared to dislocation loops, {311}'s are

metastable and become unstable at lower interstitial supersaturation. Therefore when the

supersaturation of interstitials fall below a critical point, dislocation loops become

energetically favorable and {311}'s undergo unfaulting to form dislocation loops [20,

35]. Also, the dissolution of {311} defects release interstitials that were trapped, which

can lead to TED [36].

Dislocation loops have a formation threshold higher than {311} defects making

loops less favorably during early annealing times. However, dislocation loops are more










thermodynamically stable than C311)'s, therefore they can exist at longer times and

higher temperatures. Stolk et al. [37] reported an activation energy for C311) dissolution

to 3.8 f 0.2 eV while previous studies of dislocation loop dissolution in silicon have

always shown an activation energy of 4 5 eV [38]. During the anneal the defect

evolution of dislocation loops undergoes four stages: nucleation, growth, coarsening, and

dissolution [39]. For short times during the nucleation stage, a large portion of

interstitials precipitate to form dislocation loops while a small percent diffuses down the

gradient. In the pure growth stage the supersaturation of interstitials is too low to form

new loops, so loops grow but the density of defects remains unchanged. For long

annealing times Ostwald ripening occurs, where the dislocation loops are in dynamic

equilibrium with the surrounding excess interstitials, resulting in the growth of large

dislocation loops at the expense of smaller ones [40, 41].

Gutierrez [42] examined the EOR defect evolution of 5-30 keV 1 x 10'5 Ge+ cm~2 at

750 "C using TEM and observed similar results as Robertson [33] for the 10 and 30 keV

implant energies, interstitials evolving from small clusters to C311) defects and then to

loops. However, for the lowest energy, 5 keV, the interstitials form small, unstable

dislocation loops that dissolve within a narrow time window, with no C311) formation.

This result suggests that for low energy amorphizing implants there may be a different

defect evolution.

1.4.2 Transient Enhanced Diffusion

In addition to forming extended defects, the excess interstitials created by ion

implantation causes an enhancement [40, 43] of the diffusion of the dopant profile which

is a major challenge in the formation of ultra-shallow junctions. An excellent review of










TED is provided by Jain et al. [44] The origin of TED is based on the results of

annealing a boron implanted silicon sample at 800 OC. During the anneal boron in the

tail of the implanted profile diffuses very fast, faster than the normal thermal diffusion by

a factor of 100 or more. After annealing for a while, the enhanced diffusion saturates.

The enhanced diffusion is temporary, on annealing the same sample again after the

saturation, enhanced diffusion does not occur again, hence transient enhanced diffusion.


~30 ke
10 ke
5 keV


Figure 1.4 Defect evolution reported by Gutierrez 142] for Ge' implanted at energies of 5,
10, and 30 keV at a constant dose of 10'5 cm~2 annealed at 750 "C.

For the case of amorphizing implants, the enhanced diffusion is limited to the

interactions between interstitials in the EOR region and the boron atoms [12, 20]. Both

(311) defects and dislocation loops can drive TED in amorphizing implants. Eaglesham


750 OC






r


100 1000

Time (sec.)










et al. [20] and Jones [45] found the dissolution of C311)'s in the EOR region correspond

to the same time interval as TED, which is consistent with assertion that C311) defects

are the source of the interstitials. Also, Lampi et al. [39] proposed that the evolution

process of dislocation loops not only affects the time interval of TED, but also implies

that loops are a source of interstitials as well. Robertson et al. [46] suggested that the

dissolution rate of C311) defects alone is not sufficient to drive TED and loop growth,

but is assisted by the dissolution of sub-microscopic interstitial clusters.

Therefore, the dissolution of interstitials from different defect morphologies affect

TED, but the degree of to which defect contributes is dependent on dissolution rate and

activation energy of a given interstitial precipitate. The dissolution rate of the defect will

determine the rate at which interstitials are released, while the activation energy of a

defect will determine the whether or not the interstitial precipitate will dissolve at a given

temperature.



1.5 Effect of the Free Surface on End-of-Range Damage

As mentioned above, the excess interstitials introduced from ion implantation are

believed to have two annealing sites, either the wafer surface or the bulk. It has widely

been proposed that the wafer surface is an infinite interstitial recombination sink;

therefore, as device scaling trends require shallower amorphous layers, the excess

interstitials in EOR damage will be in ever increasing proximity to the surface. Surface

effects on the formation and evolution of extended defects in the EOR and on TED are a

controversial topic and have produced studies with contradicting results.

Meekinson [47] using controlled etching reduced the thickness of a 3900 ~i

amorphous layer to 2000 ~i and 800 ~i and then annealed the samples in nitrogen ambient










at 1100 "C. TEM showed that the number of interstitials in EOR dislocation loops

decreased with a decrease in amorphous layer thickness. The study also reported

dislocation loops in the shallower amorphous layers lost interstitials from dislocation

loops at a faster rate than in the sample with the original amorphous layer thickness. A

similar study by Narayan et al. [48] reported a similar effect. They attributed this effect

to either the reduced distance between interstitials and the surface or glide of the loops to

surface due to an image force.

Roman et al. [49] created EOR dislocation loops 2600 ~i deep after annealing an

amorphizing dual implant of 120 keV and 30 keV 10'5 Si+l cm2 at 850 "C for 30 min. A

CMP procedure was used to remove various amounts silicon in order to reduce loop

depth in samples to 1800 and 1000 ~i. They found that the proximity to the surface

significantly affected dissolution kinetics of dislocation loops, and that loops dissolution

is diffusion limited to the surface. However, in this experiment the effect of amorphous

layer thickness was not a variable since the CMP procedure was performed after the

amorphous layer was recrystallized.

A model proposed by Omri et al. [50] considers the amorphous/crystalline interface

as a diffusion barrier for interstitials during the nucleation state of extended defects, when

the supersaturation is high. Then, according to their model, only after SPE regrowth

during the coalescence of loops when the supersaturation ofinterstitials is high the

surface can act as a recombination sink. In their experiment a 150 keV 2 x 10'5 Ge+ cm~2

implant was used to create a 175 nm thick amorphous layer. Anodic etching was used to

vary the thickness of the amorphous layer from 175- 30 nm that were annealed at 1000

and 1100 "C for 10s. Using TEM they observed that despite the varied amorphous layer










thickness, the population of loops were the same. It was concluded that only after the

amorphous layer has fully regrown interstitials can recombine at the surface. However,

when this occurs the defects are already involved in the coarsening process and the

supersaturation is small which tends to diminish the effect of the surface.

Ganin and Marwick [51] observed similar results to Omri. They compared the

EOR damage created by a 40 keV and 200 keV amorphizing In' implants and then

reduced the depth of the amorphous layer of the 200 keV implant to the sample thickness

of the 40 keV sample. This enabled them to study the effect of surface proximity on

EOR damage upon annealing. It was concluded that the damage created from the

implants was strongly energy dependent since the 200 keV sample with reduced

amorphous layer had the same EOR damage as a normal 200 keV implant.




1.6 Scope and Approach of this Study

The work in this thesis is divided into three experimental sets. In the first

experiment, the defect dissolution observed by Gutierrez for the 5 keV, 1 xlO'i Ge+ cm~2

implant condition will be further investigated. This investigation will entail determining

the defect dissolution activation using a time temperature study, qualifying the role of

increased surface proximity on the dissolution, and simulating implant conditions using

UT-Marlowe.

The second experiment in this thesis is a surface lapping experiment which will

help to enhance the understanding of increased surface proximity on interstitials in the

EOR region for low energy implants. In this experiments the amorphous layer of a 10

keV, 1 xlO'i Ge+ cm~2 implant will be lapped to various thicknesses and annealed.

Influence of surface proximity will then be quantified using plan-view TEM.










The final section of this thesis is a quick experiment that will measure the effect of

a low temperature pre-anneal on the accuracy of shallow amorphous layer thickness

measurements using ellipsometry. The results of all three of these experimental sections

as well their contributions to understanding of extended defect formation in ion implanted

silicon will be discussed. Finally, avenues of future experiments will be discussed.
















CHAPTER 2
EXPERIMENTAL AND DATA EXTRACTION PROCEDURES




In this chapter, and overview of the sample preparation, characterization

techniques, and data extraction procedures for the three experiments will be given.




2.1 Transmission Electron Microscopy

Transmission electron microscopy (TEM) is a very useful technique for imaging

extended defects created from the ion implantation process. Both diffraction and imaging

information can be obtained with TEM based on the interactions between the electron


beam and a thinned specimen as the beam transmits through that specimen. Specimens

can be viewed from both the top down orientation or in cross section to give a three-

dimensional perspective on the damage created.

Viewing specimens from the top down orientation is referred to as plan-view

transmission electron microscopy or PTEM. PTEM allows the imaging of extended

defects (dislocation loops and C311) defects and quantification of defect evolution.

Defects are visible in PTEM according to diffraction contrast if g b x u Z 0 where g is

the reciprocal lattice vector corresponding to the diffraction plane, b is the dislocations

Burgers vector, and u is the dislocation line direction. All PTEM specimens were viewed

on JEOL 200CX operating at 200 keV in the g 3g centered weak beam dark field

(WBDF) condition using a g220 two-beam imaging condition at a magnification of 50,000

X. The WBDF field condition is very useful in imaging defects since it only resolves the










region of the highest strain around an extended defect, which is the core of the dislocation

[52].

Viewing specimens in cross section is appropriately referred to as cross section

transmission electron microscopy (XTEM). A JOEL 2010 high-resolution TEM

operating at 200 keV as well as a JOEL 200CX operating at 200 keV were used to

measure amorphous layer thickness down the [110] zone axis.

2.1.1 Plan-view Transmission Electron Microscopy Sample Preparation

Plan-view transmission electron microscopy (PTEM) samples are prepared in order

to view the TEM specimen from the top-down orientation. The samples are made

according to the following procedure:

1. A 3 mm disc is cut out of experimental material with a Gatan ultrasonic disc

cutter using silicon carbide (SiC) powder abrasive and water. The sample is

mounted on a glass side with the top side (implanted side) down with

crystal bond. Crystal bond is a thermoplastic that softens with the

application of heat and hardens at room temperature. For all application

involving crystal bond a hot plate is used as the heat source (set to 200

"C) and acetone is used to remove the crystal bond from the specimen. The

glass side is then adhered to the disc cutters stage using double-sided tape.

2. The sample is then thinned to approximately 100 ~m using abrasive slurry

of 15 ~m aluminum oxide (AlzO~) powder and water on a glass plate. The

sample is mounted top-down on a metal stage using crystal bond. The stage

is attached to a handheld lapping fixture from South Bay Technology and










lapped in figure eight motions until the sample is deemed thin enough by

finger touch.

3. The sample is then further thinned using a wet drip etch of 25%

hydrofluoric acid (HF) and 75% nitric acid (HNO~). The sample is etched

by mounting it top side down on a Teflon stage with paraffin wax. The

wax is melted on a hot plate and is used coat the top side to prevent

etching of the implanted surface. The sample is then adhered to the stage

by coating the perimeter of the sample with wax leaving the center of the

sample uncovered to allow preferential etching of the sample center.

Etching is deemed complete when a hole is created and a red transmission

under a light source can be observed around the edges of the etch pit.

4. The sample is then removed from the Teflon mount and soaked in n-

heptane for 15 min 24 hr or until all wax has been removed. The sample

is now ready for PTEM.

2.1.2 Cross-Section Transmission Electron Microscopy Sample Preparation

Cross-section transmission electron microscopy (XTEM) samples are

prepared using either two techniques of the following techniques. The first technique is

performed according to the following procedure:

i. Two 20 milli-inch wide strips are cut with a high speed wafer dicing saw

~om the experimental material.

2. The two strips are glued together using a thermally activated two-

component epoxy with the surfaces of interest facing each other. Then two

dummy strips of the same width are glued to both sides of the experimental










strips making 6 strips total glued together. The epoxy is then cured on a hot

plate at -200 OC for 10 minutes to ensure proper cross-linking.

3. A 3 mm disc is cut from the glued strips using the same procedure outlined

in the above section.

4. The disc is then mechanically thinned on both sides using a progressive

sequence of gritted carbide lapping papers. The lapping is performed in an

up and down motion using a handheld lapping fixture.

5. The sample is further thinned using a VCR Dimpler. In this procedure the

disc is mounted on a thin sapphire disc with crystal bond and mounted on

the Dimpler stage. The sample is first flattened using the appropriate

flattening polishing wheel and 3 ~m slurry to 100 ~m. The center of the

sample, or the interface of the two center strips, is then dimpled using the

dimpling polishing wheel and 1 ~m slurry until a red transmission under

light can be observed on the interface. Then a fine polishing wheel is used

with a 0.1 and 0.05 ~m slurry to remove scratches on the dimpled surface

created during the thinning process.

6. The sample is then ion milled using Ar' in a dual-gun Gatan ion mill set at

12-14" tilt until a small hole created on the interface of the center strips is

created. The sample is now thin enough for XTEM.

The second technique uses a Strata Dual Beam 235 FIB (focused ion beam) from

FEI, Inc to cut out a XTEM specimen that is approximately 18 ~m long, 3 ~m deep, and

1500 ~i thick using a gallium ion source. The sample is first coated with carbon followed

by a layer of platinum that is approximately 1 ~m thick. Once the specimen is cut out, it










is mounted on a copper specimen ring with carbon mesh. The FIB XTEM is now ready

for TEM.

2.1.3 Extraction of Defect Parameters from PTEM

Determining defect parameters from PTEM images, such as defect density, trapped

interstitial concentration, and defect sizes, allows for the quantification of how

interstitials evolve over time at a specific annealing temperature. Understanding the

influence of implant energy, implanted species, annealing temperature, annealing time

and other factors on the damage created helps provide experimental results to assist

dopant diffusion models, such as FLOOPS [53], to correlate TED and the evolution of

EOR damage. There is an intrinsic 20 % error associated with the following methods for

extracting defect parameters [54].

2.1.3.1 Extraction of Defect Densities from PTEM

Defect density is simply the number of defects observed in PTEM in the area that

they were observed in. The defect densities in this study are determined by the following

procedure adapted for one set forth by Bharatan [54].

1. PTEM negatives are enlarged to 3X (making total magnification now 150

kX) and printed onto 8" x 10" photographic paper.

2. A transparent film with a grid of 4 cm x 4 cm squares printed on it is laid on

top of the print. All resolvable defects (defect clusters, dislocation loops,

(311)'s) within a given square are carefully traced onto the transparency

with a fine tip marker.

3. The defect density is then determined by dividing the total number of

defects counted by the area of the square, 16 cm2, and multiplying by the

magnification to the second power. This is done from at least three of the










squares on the transparency in random areas and the results are averaged

together.

This process is adapted to counting only specific defects as well. To determine the

(311) defect density, only C311) defects are traced and counted in the given area, and to

determine the dislocation loop density only dislocation loops are counted. The detection

limit of defects for PTEM is considered to be 107 defects / cm2

2.1.3.2 Extraction of Trapped Interstitial Concentrations from PTEM

The trapped interstitial concentration gives a quantity of the number of silicon

interstitial atoms present in the defects observed. The PTEM detection limit of trapped

interstitials is considered to be 6 x 109 interstitials / cm2. The first steps are the same as

in the procedure for determining defect density. Dislocation loops and C311) defects are

traced separately on transparencies. Then the following steps are taken:

1. The traced transparencies are scanned into .plct-formatted files using Adobe

Photoshop software.

2. The scanned file is imported into an image analysis program developed by

the National Institute of Health called NIH Image v.1.6.1. The software

measures the length sum of C311) and the total area of dislocation loops.

3. The C311) defect trapped interstitial concentrations are determined by

calculating a modified length sum by the linear density of interstitials (26

interstitials / nm) contained in the C311) defect and dividing by the scanned

area. The modified length sum is used for C3ll)type defects imaged at a

45" angle to the imaging plane because the length observed is a projected

length of the defect and not the actual length. In order to account for the

discrepancy, these defects' lengths are multiplied by a factor of 1.4.










4. Dislocation loop trapped interstitial concentrations are calculated by

dividing the total area of the loops by the area of the scanned image and

multiplying the result by the planar atomic density of the C 1 1 1) plane which

is 1.6 x 10'5 atoms / cm2.




At this point it is important to note that in his thesis, Gutierrez [42] assumed the

small defects created by the 5 keV energy to be dislocation loops and extracted trapped

interstitial concentrations using the above method. In this present work this assumption

is made also. Support for the assumption that the small defects observed in the TEM

from the 5 keV implant are dislocation loop like will be shown in Chapter 3.




2.2 Variable Angle Spectroscopic Ellipsometry

Ellipsometry is an optical technique that measures the change in polarized light as

it is reflected off a sample. Variable angle spectroscopic ellipsometry (VASE) is used in

this work as a fast, nondestructive technique for measuring amorphous silicon layer

thickness, in contrast to XTEM. In VASE a linearly polarized light is reflected off the

surface of the sample into a detector. As the polarized light reflects off the surface the

light changes from plane-polarized light into elliptically polarized light. The elliptically

polarized light is characterized as having two electric field components perpendicular to

one another and a phase difference, ~. It is yr,, which is the azimuth of the reflected

light, and ~ that are characteristic of the material under study and are measured for

sample analysis. Once the optical constants (yr, and ~) are measured, a computer

program constructs a model to solve for layer thickness based on a library of previously

measured constants.










All VASE measurements were performed using a J. A. Woolmam multi-

wavelength spectroscopic ellipsometer with a 75 W xenon light source at a fixed angle of

75". The system is first calibrated by measuring the silicon dioxide thickness on a

calibration wafer. The only sample preparation required in VASE is a careful cleaning of

the sample's surface with methanol. The sample area must be larger than 1 cm x 1 cm to

eliminate edge effects from the light source's beam, which is about 3 mm in diameter.

During measurements a fixed 20 ~i oxide layer was assumed for samples to account for

the native oxide of silicon. A minimum of three measurements is taken from different

areas on the sample for all measurements.

The VASE technique produces very precise measurements, but the accuracy may

some time be questionable. Scanning over a larger range of wavelengths of light also

increases accuracy of measurements. Overall the VASE system normally yields an

accuracy of 10-20% of actual thickness determined from TEM, however Lindfors[lO]

showed that very shallow amorphous layer the accuracy may be worse. In his work he

measured an amorphous layer thickness of a 2.5 keV 1 x 10'5 Si+ / cm2 to be 26 ~i with

high-resolution TEM compared to 13 ~i with VASE.



2.3 UT Marlowe

UT Marlowe [55] is a binary collision approximation simulator that considers

crystal structure, therefore it is used for the simulation of ion implantation into crystalline

and amorphous material. This modeling predicts both the impurity profiles as a function

of depth of implant parameters and also damage profiles, which can be used as input files

for TED simulators, such as FLOOPS (see section below).










During this work UT- Marlowe has been used to simulate the 5 and 10 keV 1 x 10'5

Ge+/cmz amorphizing implants in order to give a qualitative under standing of the initial

implant conditions and the difference of the net excess interstitials (NEI) in the EOR

region created between to the two energies. UT-Marlowe can simulate amorphous layer

depths by using the filename. rbs output file, which simulates a rutherford backscattering

spectrometry (RBS). The amorphous layer depth is determined by finding the depth at

which the percentage of amorphization decreases most rapidly on a linear linear plot.

The NEI is calculated by using two separate output files. The first output file used

is the filename. Ist output file. It is the concentration of silicon interstitials formed during

implantation at a given depth. When the concentration of interstitials reaches 5 x 102'

cm~~ or 10% of the lattice density at a given depth the lattice is considered amorphized.

The second output file used is the filename. vac file. It provides a concentration of

concentration profile of the number of silicon vacancies formed during implantation.

Subtracting the concentration profile of interstitials from the concentration profile of the

vacancies in the EOR region and taking the integral of the area underneath the difference

calculate the NEI. The NEI is the difference between two very large numbers therefore

the simulation was performed with 300,000 input ions.



2.4 5 keV Ge' Defect Dissolution Study

The goal of this study is to gain further understanding of the defect dissolution

observed by Gutierrez [42] for the 5 keV 1 x 10'5 Ge+ cm~2 implanted silicon wafers. The

first experiment in this study was performed to calculate the activation energy of the

observed defect dissolution. The second experiment was performed to determine if the










increased surface proximity for the 5 keV energy (amorphous layer thickness = 100 ~i)'

compared to the 10 keV energy (amorphous layer thickness = 220 ~i)2 has a role in the

dissolution process. For both experiments the source material used is Czochralski grown

(100) Si wafers implanted by Varian, Inc. at room temperature with a constant does of 1 x

10'5 Ge+ cm~2 at 5 and 10 keV energies with a 70 tilt. These wafers have only a native

oxide layer, approximately 20 ~i thick. Finally, UT Marlowe was used to obtain a

qualitative understanding of the difference in the NEI difference between the two

energies in the EOR region.

2.4.1 5 keV Defect Dissolution Activation Energy Experiment

To investigate the defect dissolution process observed for the 5 keV energy

implants, specimens were annealed at multiple temperatures to calculate the activation

energy of the dissolution. PTEM was used to identify times when the dissolution process

occurs at temperatures of 725, 750, 775, 825, and 875 "C. The times and corresponding

temperatures were plotted in an Arrhenius-type chart to calculate the activation energy.

The annealing was performed in a Lindberg tube furnace under nitrogen ambient with the

sample placed in a quartz boat. All annealing procedures were performed in this furnace.

Usually, samples are annealed first before they are thinned for TEM analysis, however

Li[56] et al. showed once samples are thinned they can be annealed as well without

producing a measurable effect on defect evolution. Based on this, many PTEM samples






Values obtained from Gut~errez's work The amorphous layer thickness for both energies are measured
agam m t~s work

Z Values obtained from Gut~errez's work The amorphous layer thickness for both energies are measured
agam m t~s work










in this work are annealed after they have been thinned to reduce the labor of sample

preparation for every annealing time.

2.4.2 Surface Lapping Experiment

In the second part of this experiment the effect of increased surface proximity

between the 5 and 10 keV implants was studied by using a mechanical lapping technique

to bring the EOR region in the 10 keV implant to the same proximity to the surface as the

5 keV implant. In this experiment the amorphous layer of a 2 cm x 2 cm 10 keV Ge+

sample was reduced to 80 ~i, which is less than that of the amorphous layer of the 5 keV

implant. The lapped sample was then annealed at 750 "C and the defect evolution was

characterized using PTEM and compared to control samples of the 5 keV and 10 keV

implants.

The mechanical lapping procedure used in the surface lapping experiment

removes measured amounts of amorphous silicon in order to increase the surface

proximity between the EOR region land excess interstitials) to surface. The procedure

used is based on the one developed by Herner et al [57]. The lapping procedure in this

experiment was performed according to the following steps:

1. A 2 cm x 2 cm sample is cut from experimental material using a high -

speed wafer dicing saw.

2. The square sample is then mounted on a lapping stage using crystal bond

and lapped using a hand lapping fixture from South Bay Technology and

polished on 12 in rayon polishing pads with Syton~ as the polishing agent.

Syton~ is colloidal silica with particle sizes from 0.2 0.6 ~m. The sample

is lapped in a figure eight motion. The lapping procedure removes about










10-12 ~i per lap once the native oxide has been removed by the lapping

procedure or by a buffered oxide etch (BOE).

3. Once the appropriate number of laps has been performed the sample is

removed from the stage and the crystal bond is removed with acetone.




2.6 Surface Proximity Experiment

This experiment is a continuation of the surface lapping experiment described in

the section above. The goal of this experiment is to determine what effect increased

surface proximity has on excess interstitials in the EOR region. Three 10 keV, ix 10'5

Ge+ cm~2 specimens with reduced amorphous layer depths of 155, 125, and 40 ~i will be

produced for this experiment in addition to the 80 ~i specimen from the section above.

The procedures of this experiment is described below:

i. 2 cm x 2 cm samples are cut from experimental material using a high speed

wafer dicing saw and their amorphous layers are lapped using the procedure

described in the above section.

2. Ellipsometry is then used to gain a quick measure of the lapped amorphous layer

depths.

3. A 3 mm core is taken from the center of each of the 2 cm x 2 cm square samples

and these cores are annealed at 750 "C for 15 min. The cored, annealed

specimens are then thinned for PTEM. XTEM specimens are made from each of

the square samples using a FIB to cut out a thin sample very close to area on the

sample where the core was taken. The amorphous layer depths are then measured

using XTEM.










4. PTEM is used to quantify the extended defects in the samples after the 15 min

anneal, and then the samples are annealed for another 30 min making the total

anneal time 45 min and examined with PTEM again.

The effect of increased surface proximity on interstitials in the EOR will be

determined by comparing the defect parameters obtained by PTEM versus amorphous

layer depths.



2.7 Ellipsometry Experiment

In this experiment, the effect of a low temperature anneal on the accuracy of

ellipsometry measurements for shallow amorphous layers will be determined. The

experimental material used in this experiment is 5, 10, and 30 keV, 1 x 10'5 Ge+ cm~2

implanted Si wafers from Varian, Inc. Samples from the wafers will be annealed at 400

"C for times ranging from 5 80 min in a conventional tube furnace with nitrogen

ambient. Amorphous layer depths will then be measured using ellipsometry for each

annealing time.

Ellipsometry measurements will be performed on a J. A. Woolmam multi-

wavelength spectroscopic ellipsometer described in section 2.2. Three measurements

will be performed on each sample. XTEM samples will be prepared for as-implanted

specimens for the three implant energies as well as samples that have been annealed for

40 and 80 min. The XTEM specimens will be images on a JEOL 2010 high resolution

TEM to image the amorphous layer depth as well as the amorphous/crystalline interface

roughness. The amorphous/crystalline roughness will be determined by averaging peak-

to-valley distance from five different positions along the interface from enlarged XTEM

images.
















CHAPTER 3
5 keV Ge' DEFECT DISSOLUTION STUDY



3.1 Overview

The work in this chapter was performed to gain a better understanding of the defect

dissolution observed by Gutierrez [42] for the 5 keV Ge' implant energy when compared

to higher energies shown previously in Figure 1.4. In his thesis, Gutierrez reported the

low energy implant created small unstable dislocation loops that dissolved rapidly after

60 min annealing time at 750 "C. Gutierrez concluded that the excess interstitials

resulting from the 5 keV implant condition have an alternate evolutionary pathway than

higher energy implants. The work in this chapter was performed to further characterize

the previously unreported small unstable dislocation loops created from the low energy,

amorphizing implant condition.

The first experiment in this chapter was performed to find the defect dissolution

activation energy of the small defects created from the 5 keV implant. Since these small

defects dissolve after shorter annealing times than ones created by the higher 10 and 30

keV implants, they must have a different dissolution energy threshold. The second

experiment in this chapter was performed to determine the effect of increased surface

proximity to the EOR region between the 5 and 10 keV implants. The 5 keV implant,

reported by Gutierrez, forms a 100 ~i amorphous layer compared to the 220 ~i amorphous

layer formed by the 10 keV energy. Therefore the diffusion distance to the surface for

the interstitials created in the 5 keV implant is roughly half as far as it is for the










interstitials in the 10 keV case. If the surface acts like an infinite interstitial

recombination sink then increased interstitial annihilation at the surface will lower the

supersaturation and may account for the dissolution observed in the 5 keV implant.

Finally in this chapter, initial implant conditions and the difference between the net

excess interstitials (NEI) in the EOR will be calculated using UT-Marlowe simulations

for the 5 and 10 keV energies.




3.2 Defect Dissolution Activation Energy

The defect dissolution activation energy for the 5 keV 1 x 10'5 Ge+ cm~2 implant

condition was calculated by obtaining the times when all defects dissolved at 725, 750,

775, 825, and 875 "C using PTEM.

3.2.1 TEM Results

Figures 3.1 3.5 show WBDF PTEM micrographs of the extended defects

created by the 5 keV 1 x 10'5 Ge+ cm~2 implant at each of their respective times and

temperatures until dissolution. As the micrographs show, the exact time when the defects

dissolve is not determined since they are not annealed in-sltu in the TEM, instead the

dissolution time is determined by finding the range in time when the last point defects are

present and next time where they are no longer present as observed by TEM. For

example, at 725 "C the final annealing time defects were observed was at 70 min. At the

next annealing time of 80 min, there are no observable defects and therefore they

assumed to be dissolved. The time of defect dissolution at 725 "C is then to occur at a


time between 70 and 80 min. Table 3.1 show the range of dissolution times determined

by PTEM at each respective temperature.










Table 3.1 Time range where defect dissolution occurs at each annealing temperature as
observed PTEM.
Temperature 725 "C 750 "C 775 "C 825 "C 875 "C

Range 70 80 min 60 65 min 40 45 min 30 35 min 10 15 min




Figure 3.6 shows a WBDF PTEM image of a 5 keV implant annealed at 775 "C for

35 min imaged at the go4o condition in contrast to the normal g220 condition. The defect is

faint, but shows two lobes with a line of no contrast through the middle that is parallel to

g. This is characteristic to dislocation loop contrast in TEM [58]. This observation

supports the assumption that the small defects created by the 5 keV energy implant are

dislocation loops like in nature.

Figures 3.7 and 3.8 show the defect density and trapped interstitial concentration

trends over time at the five annealing temperatures, respectively. As the figures show,

the defect densities and trapped interstitial concentrations decrease for increasing

temperatures, as expected. Another trend that is clearly shown by the three lowest

temperatures of 725, 750, and 775 "C is that the number of defects remains plateaued

relatively high, in the 10'0 defect/cm2 range until they approach their dissolution window

where the trend decreases rapidly. The trapped interstitial concentration also shows this

trend.

Figure 3.9 shows the average defect diameter over annealing at each of the five

respective temperatures. The error bars represent the standard deviation of the averages.

As annealing temperature increases, the average defect size increases. For the lowest

annealing temperature, 725 "C, the defects do not increase in diameter or ripen over time

significantly. At 15 min the average defect size is 5.89 nm and at the last point before










dissolution the average defect size has only increased to 8.92 nm. In general, the defects

for all annealing times do not increase in average diameter greater than 40% before

dissolution. The defects reduce in number more significantly than grow in size or

coarsen.

3.2.2 Extraction of Defect Dissolution Activation Energy

The activation energy for the 5 keV, 1 x 10'5 Ge+ cm~2 implant defect dissolution

was determined by applying an Arrhenius relationship to the time ranges and

temperatures where the dissolution was observed, shown in Figure 3.10. The mid-point

of the time ranges were plotted as a rate (s~') on the y-axis with error bars reflecting the

max and min of the time range. The inverse of temperature (K~') was plotted on the x-

axis multiplied by a factor of 104 for clarity.

Using a least square exponential curve fit to the data, the defect dissolution was

found to follow the trend;

z = 99.845 e^(-1.3091x) 3.1


The correlation coefficient, r, of the curve was determined to be 0.9709 1, which shows a

strong fit to the data. The activation energy is determined by multiplying the fitted

exponentialvalue, 1.3091, by Boltzmann's Constant (8.65 x 10~5 eV/K) and 104 to correct

for the x-axis factor of the same value. Performing these operations reveals the ultimate

trend of the defect dissolution, shown by the relationship;

~ = ~o e" -(Ea/kT) 3.2


where Ea is 1.13 eV and ~~ is 99.845 s~'. The error that is associated with the

experimentally determined Ea was determined to be f 0.14 eV. This was calculated by

fitting a line to plot in accordance with the maximum error represented by the error bars.










3.3 Surface Lapping Experiment

This experiment was performed to evaluate the effect of increased surface

proximity on the dissolution of the defects created by the 5 keV, 1 x 10'5 Ge+ cm

implant. If the surface is a source for interstitial recombination, than the increased

surface proximity in the 5 keV case may explain the rapid defect dissolution. In this

experiment the amorphous layer of a 10 keV, 1 x 10'5 Ge+ cm~2 was lapped to thickness

less than the thickness of 5 keV, 1 x 10'5 Ge+ cm~2 implant. Both the 5 and 10 keV

energy implants were annealed at 750 "C for times ranging from 5 360 min and the

defect evolution was characterized using PTEM.

3.3.1 Amorphous Layer Lapping Results

Ellipsometry was used to determine if the 10 keV-lapped specimen's amorphous

layer was polished to a thickness less than that of the 5 keV implant. Table 3.2 shows the

ellipsometry measurement results for the 5, 10, and 10 keV-lapped specimens. Based on

the ellipsometry results, the amorphous layer thickness for each specimen was verified

using high resolution transmission electron microscopy (HTREM). Figure 3.11 shows

the HRTEM results. The amorphous layer thickness for the 5, 10, and 10 keV lapped

specimens was determined to be 100, 180, and 80 ~i, respectively. The lapping procedure

reduced the 10 keV-lapped specimen's amorphous layer thickness by 100 ~i, 20 ~i less

than the 5 keV amorphous layer thickness.










Table 3.2 Ellipsometry measurements of amorphous layer thickness for the 5, 10, and 10
keV
Amorphous layer 5 keV 10 keV-lapped 10 keV
thickness
1 measurement 144.24 ~i 120.86 ~i 209. 54 ~i

measurement 144.64 ~i 118.20 ~i 220.39 ~i

3 measurement 144.04 ~i 110.72 ~i 226.25 ~i




3.3.2 Defect Evolution

Figures 3.12 and 3.13 show PTEM micrographs of the defect evolution for the 10

keV specimen and the 10 keV-lapped specimen annealed at 750 "C. For micrographs of

the 5 keV energy at 750 "C the reader is referred to Figure 3.2. It was found that the

defect evolution of the 10 keV-lapped specimen strongly resembled that of the control,

unlapped 10 keV specimen. Figure 3.14 shows the defect evolutions for the 5, 10, and 10

keV-lapped specimens. The 10 keV lapped specimen did not exhibit dissolution of

defects, stable dislocation loops were still present after the longest annealing time of 360

min. The defect evolution for the 10 keV control and 10 keV-lapped followed that of the

one reported by Gutierrez, small cluster defects evolved into C311) defects and

dislocation loops, then [311) defects dissolved leaving stable dislocation loops.




3.4 UT-Marlowe Simulations

UT-Marlowe simulations were performed to obtain pre-experimental conditions of

for the 5 and 10 keV, 1 x 10'5 Ge+ cm~2 implants. A 300,000-ion simulation was run for

the two energies at a 70 tilt to match the implant conditions. The predicted amorphous










layer depths, vacancy profiles, interstitial profiles, and the net excess interstitial (NEI)

profiles for the two energies were obtained.

3.4.1 Simulation Results

UT-Marlowe simulations for the 5 keV energy implant calculated a Rp of 70 ~i and

a ~Rp of 32 ~i. Figure 3.15 shows the .rbs output for the 5 keV implant. The profile

predicts the amorphous layer depth to be 108.3 ~i compared to that of 100 ~i measured by

HRTEM. Figure 3.16 shows the vacancy and interstitial profile of the 5 keV implant.

Note that the noise level in the data increases dramatically at concentrations below 1 x

10'9 cm~~. UT-Marlowe simulations for the 10 keV energy implant calculated a Rp of 114

~i and a ~Rp of 53 ~i. Figure 3.17 shows the .rbs output for the 10 keV implant. This

profile predicts the amorphous layer depth to be 195.48 ~i in contrast to 180 ~i measured

by HRTEM. Figure 3.18 shows the vacancy and interstitial profile of the 10 keV

implant. Again, note that the noise level in the data increases dramatically at

concentrations below 1 x 10'9 cm~~.

3.4.2 NEI calculation

The NEI profiles for the 5 and 10 keV implants were obtained by normalizing the

depth by eliminating the amorphous layer from the calculation and subtracting the

interstitials from the vacancies in the profiles. The area under the curves up to a

concentration of 1 x 10'9 cm~~ was then integrated to get the NEI concentration. Figure

3.19 shows the NEI profile for the two energies. The NEI concentration in the EOR

region for the 5 keV implant was calculated to be 3.47 x 10'4 cm~2. The NEI

concentration in the EOR region for the 10 keV implant was calculated to be 3.30 x 10'4

cm










3.5 Discussion

The 1.13 f 0.14 eV defect dissolution activation energy for the 5 keV implant is

an intriguing result, especially if these defects are considered to have a defect

morphology like dislocation loops. These defects clearly do not behave like any type of

dislocation loops previously reported in silicon, which have always have had dissolution

activation energies reported to be in the 4 5 eV range [59]. The explanation for this has

always been that the Si self-diffusion was involved, which has an activation energy of

-4.5 eV [59, 60]. The low 1.13 eV activation energy may indicate that instead of the

dislocations moving by a diffusion controlled climb process, the dissolve by a lower

energy glide process. Also, Figure 3.9 shows that the defects do not coarsen

significantly, which is a key characteristic of dislocation loops.

One may propose that these defects are in fact spherical, or volumetric clusters of

silicon interstitials, since that defect morphology would minimize the most energy.

Calculating the trapped interstitial concentration assuming a sphere instead of plate will

increase the value by a factor roughly of 10' interstitials/ cm2, which is an unreasonable

value given the experimental conditions and results. Also, the appearance of the defect

shown in Figure 3.6 is convincing evidence to the author that these defects are in fact

plate-like, dislocation loops.

The surface lapping experiment eliminated surface proximity as the main factor

responsible for the defect dissolution. The defects formed in the EOR are clearly implant

energy dependent in agreement with Omri [50] and Ganin and Marwick [51]. UT-

Marlowe simulations showed that there is no qualitative difference in the NEI in the EOR

between the 5 and 10 keV energy implants, but the accuracy of these results are

questionable. A simulation with a significantly larger amount of ions should be run to










further verify theses results. Gutierrez [42] showed in his thesis using quantitative PTEM

that there is almost an order of magnitude less trapped interstitials in the 5 keV case then

in the 10 keV energy. Figure 3.20 shows his experimental results. The small, unstable

defects may be a result from the implant condition that has a very small straggle, 32 ~i,

and a low supersaturation of excess interstitials.



3.6 Conclusion

The small, unstable defects created by the 5 keV, 1 x 10'5 Ge+ cm~2 implantation

into silicon reported by Gutierrez [42] were found to have a dissolution activation energy

of 1.13 f 0.14 eV. PTEM showed that these defects do not significantly coarsen, but

ratherjust decrease in number. A lapping experiment which reduced the amorphous

layer of a 10 keV implant with the same dose to less than that of the 5 keV implant

showed that increased surface proximity is not responsible for the defect dissolution. It

was found that the defects in the 5 keV energy case were strongly implant energy

dependent. The author proposes that these small defects are dislocation loop-like and are

result of the implant's small straggle and low interstitial supersaturation.

















1000 A


(b) (c)


Figure 3 2 PTEM micrographs of 5 keV Ge ,
(a)15 rmm, (b) 60 rmm, (c) 65 mm,


1 x 10'1 cm2 Gei anmealed at 725 oC for
(d) 70 mm, and (e) 80 mmn
















1000 A









(a) (b) (c)









(d) (e)

Figure 3 2 PTEM rmcrographs of 5 keV Ge 1 x 10' cm2 Gei annealed at 750 oC for (a)
5 mmS (b 15 mmS (c) 45 rmm, (d) 60 rmm, and (e) 65 rmm
















1000 A










(a) (b) (c)










(d)

Figure 3 3 PTEM rmcrographs of 5 keV Ge 1 x 10' cm2 Gei annealed at 775 oC for (a)
15 rmm, (b) 35 rmm, (c) 40 mmn, and (d) 45 rmm
















1000 A










(a) (b) (c)

Figure 3 4 PTEM nucrographs of 5 keV Ge 1 x 10 lcm2 Gei annealed at 825 oC for (a)
15 nun, (b) 30 nun, and (c) 35 rnn
















1000 A










(a) (b) (c)

Figure 3 5 PTEM rmcrographs of 5 keV Ge 1 x 10' cm2 Gei annealed at 875 oC for (a)
5 mm, (b 10 mm, and (c) 15 mmn


















5














1x1012


1x1011


1x1010


1x109


1x108


1x107


1x106


1000 2000 3000

Time (s)


4000 5000


Figure 3.7 Defect density trends for 5 keV, ix 10'5 Ge+ cm~2 implant over time annealed
at 725, 750, 775, 825, and 875 "C.
















^1x1014


1x10


1x1012


1x1011


1x1010


1x109


1000 2000 3000 4000 5000

Time (s)


Figure 3.8 Trapped interstitial trends for 5 keV, ix 10'5 Ge+ cm~2 implant over time
annealed at 725, 750, 775, 825, and 875 "C.














40

E 35
r P ~ 750 OC
30 ~ 1~ 775 OC
~825 OC
E1~ 25 ~ ~I \ A ~ 875 OC

20 P

15

10

5
Q

0 1000 20~0 13000 4~000 5"000

Time (s)

Figure 3.9 Average defect diameter over time for the 5 keV, 1 x 10'5 Ge+ cm~2 implant
annealed at 725, 750, 775, 825, and 875 "C.












1x10~2



y = 99.845 e"(-1.3091x) R= 0.97091




u, 1x10~3








1x10~4
8.5 9 9.5 10

104!T(K~~)

Figure 3.10 Defect dissolution rates versus inverse temperature, plotted in Arrhenius
form. The trend is show as a least square exponential curve fit.

























Figure 311 Hlgl igh-tnlo: ealuti~moncpkonshe cta nTomlorahsftea orhosl
thicknessila foreVa) 10 h-ap4ndleV, (b)~ 1 V-appd ndc eVsmle nw
punt henio te sufc


















.::::~iii~i~~j~:ii...: ::::'::.:1:..
.:::-:.:::::
::.
::.

""'''


....:r::.....

=:f~
:,:..:::



.k...."


(a)


(e) (f)


Figure 3.12 PTEM micrographs of the 10 keV Ge 1 x 1015 cm-2 Ge+ control implant
annealed at 750 OC for (a) 5 min, (b) 15 min, (c) 30 min, (d) 45 min, (e) 60

min, and (f) 360 min.



































i ~~~t~; r.:;
::"~-~

-


Iji:I:l:l:


Figure 3 13 FTEM micrographs of the 10 keV Ge 1 x 10'1 cm2 Gei implant whose
amorphous layer was pohished to 80 A and annealed at 750 oC for (a) 5 mm,
(b 15 mm, (c) 30 rmm, (d) 45 rmm, (e) 60 mm, and (f) 360 mm














t10 keV- 180 PI
~10 keV 80 a
~5 keV 100 a












TEM detection limit
L


Time (s)

Figure 3.14 Defect evolution of the 5 keV, 10 keV, and 10 keV-lapped specimens
annealed at 750 "C.






54






100


80


u,
60
c 3
m
O O
E 40
Q or

Pi 20

a

0 100 200 300 400 500

De pth (A)


Figure 3.15 UT-Marlowe .rbs output for the 5 keV, 1 x 10'5 Ge+ cm~2 implant.

















1x1d2

~ Interstitials
-- Va ca n ci es
"E ixldl



elxldO



~1x1019
O

1x10'8 r I I R T
0 100 200 300 400 500

De pth (A)


Figure 3.16 UT-Marlowe simulated interstitial and vacancy profiles for the 5 keV, 1 x
10'5 Ge+ cm~2 implant.
























100



80

~ ~I u, I\
I\
60 o
c
I ~r
L LI L V)
O O
E 40 E
Q


Pi 20

a

0 100 200 300 400 500

De pth (A)


Figure 3.17 UT-Marlowe .rbs output for the 10 keV, 1 x 10'5 Ge+ cm~2 implant.













1x1d2
~ Interstitials
--e Va ca n ci e s
"E ,,,dl



e 1,1d0



~1x1019

O

1x1018
0 100 200 300 400 500

De pth (A)
Figure 3.18 UT-Marlowe simulated interstitial and vacancy profiles for the 5 keV, 1 x
10'5 Ge+ cm~2 implant.












1x1022

~10 keV NEI
---- 5 keV NEI
mg~ 1x1021



e



1x1019


1x1018
0 50 100 150 200

Normalized Depth (A)
Figure 3.19 NEI profile for the 5 and 10 keV, 1 x 10'5 Ge+ cm~2 implants.






























. e n a ni I i

1 P to 100 100oo


"R-Dkt
*-SheV


Figure 320 Tr~lisb appedintersht, Iand0elOcnc entaosfo 5 0ad0kV 0 e 2G
implniantaneald 1 O aleyddat75cCuarepnidbyutnez42
















CHAPTER 4
SURFACE PROXIMITY EXPERIMENT



4.1 Overview

In Chapter 3 an amorphous layer lapping experiment showed that increased

surface proximity was not the key factor responsible for the defect dissolution observed

in the 5 keV case. This finding again raises the argument of the role of the surface on

excess interstitials. Does increasing the surface proximity to excess interstitials in the

EOR region cause increased annihilation of these interstitials as proposed by Meekinson

[47], Narayan [48], and Raman [49]? To approach this question from a low energy

standpoint a 10 keV, 1 x 10'5 Ge+ cm~2 implant was used in a continuation of the

amorphous layer lapping experiment from Chapter 3.

In this present experiment, the amorphous layer of a 10 keV implant was reduced

to various depths and annealed at 750 "C for 15 and 45 min and the subsequent extended

defects and trapped interstitial concentrations are studied using PTEM. By reducing the

amorphous layer thickness, the EOR region and the excess interstitials that reside there

are brought in closer proximity to the surface.




4.2 Experimental Results

The 10 keV implant forms a continuous amorphous layer 180 ~i deep, as shown in

Figure 3.11. The lapping procedure produced specimens with 155, 125, 80, and 40 ~i.

Figure 4.1 shows the XTEM images of the amorphous layer depths for the 155, 125, and










40 ~i specimens. The 80 ~i specimen is the same one from Chapter 3, and its XTEM

image is also shown in Figure 3.1 1. Figure 4.2 shows PTEM micrographs of the 1 55,

125, and 40 ~i specimens annealed at 750 "C for 15 and 45 min. The reader is referred to

Figure 3.12 and 3.13 for the PTEM micrographs for the 180 ~i and 80 ~i specimens. The

micrographs show that the defect population for the 155, 125, and 80 ~i specimens are

very similar to the control, 180 ~i specimen. On the other hand, the 40 ~i specimen's

PTEM micrographs look a little different. There is a smaller population of small clusters

or dislocation loops and no clear C311) defects are visible.

The defect densities and trapped interstitial concentrations for the five specimens

are shown in Figure 4.3 and 4.4, respectively. The defect densities show no clear trend

that can be correlated to increased surface proximity. The 155 and 125 ~i specimens have

higher defect density values than the 180 ~i specimen after 15 min. However, after 45

min the 80 ~i specimen is the only specimen with a higher defect density than the control.

With the shallowest amorphous layer depth of 40 ~i the smallest the smallest

concentration of trapped interstitials exists at 15 min, but this trend is does not hold at 45

min. After 45 min, the 180 ~i control specimen maintains the largest concentration of

trapped interstitials, which may support that at longer annealing times increased surface

proximity may be responsible for increased interstitial annihilation, but overall the defect

densities and trapped interstitial concentrations are within the intrinsic 20 % error

associated with this method of counting for all specimens and no clear effect of the

surface can be determined.

Figures 4.5 and 4.6 show the defect densities separated by the defect type,

dislocation loops and C311) defects, respectively. An important note here is that no clear










(311) morphology was observed in the 40 ~i specimen PTEM micrographs, showing that

at the shallowest amorphous layer depths C311) defects may not form. Figures 4.7 and

4.8 show the trapped interstitial concentrations separated by the defect type, dislocation

loops and C311) defects, respectively. The average dislocation loops diameter is shown

in Figure 4.9. It shows that there is a slight increase in defect diameter for 40 ~i

specimen, but it is with in the error. The error bars reflect the standard deviation

associated with the averaging of the diameters. Figure 4.10 shows the average defect

length for the specimens, showing no clear trend.



4.3 Discussion

The overall trapped interstitial concentration with respect to amorphous layer

depth is shown in Figure 4.11. It is clear in Figure 4.11 that there is no trend related to

surface proximity on trapped interstitial concentration after 15 min of annealing time,

untilthe shallowest depth of 40 ~i when the amorphous layer depth approaches that of the

average dislocation loop diameter. At the longer annealing time of 45 min, the trend does

not hold further showing that the trapped interstitial population is independent of

amorphous layer depth and therefore surface proximity.

The lapping experiment in Chapter 3, which only considered the 180 and 80 ~i

specimens quantified the defect evolution over 360 min of annealing time. At the longer

annealing times, there was no evidence that the increased surface proximity, roughly half

of the interstitials diffusion distance between the two specimens in this case, had any

effect on the interstitial concentration. Figure 3.13 shows that after 360 min, large, stable

dislocation loops are present in both specimens and Figure 3.14 shows that their defect

densities are comparable throughout the annealing times. The totality of these findings










show that the model proposed by Omri [50] is still valid with amorphous layers very

close to the surface, in that the surface does not have an effect on defect evolution of

EOR damage

These results also shed doubt on the concept of an image force exerted by the free

surface onto dislocation loops as suggested by Narayan and Jagannagham [48]. In this

theory the image force is proportional to the ratio of defect size divided by its distance to

the surface (F ~d/L). Narayan and Jagannagham theorized that dislocation loops with

diameters greater than 2L will move to the surface and there will be a band of defect free

crystal in that region. The results in this thesis show that dislocation loops exist very

close to the surface and are not drawn to the surface by an image force.



4.4 Conclusion

In this chapter the amorphous layer of a 10 keV, 1 x 10'5 Ge+ cm~2 implant was

tapped to thicknesses reduced from 180 ~i to 165, 125, 80, and 40 ~i. The specimens

were then annealed at 750 "C for 15 and 45 min. The defect populations for the control-

180 ~i, 165, 125, and 80 ~i specimens were all very similar to each other at both

annealing times. However, the 40 ~i specimen formed slightly larger dislocation loops

and had a smaller interstitial population than the other specimens but was within the error

of TEM analysis. After 45 min the control specimen had the highest concentration of

trapped interstitials, which may be evident that the surface does have some effect after

longer annealing times, but is not clear from the error.









































't;








1000 A


.* v* .*.


~.;

.ii


: t


Figure 4 2 PTEM rmcrographs of the 155 A specimen at (a) 15 and (b 45 mm, the 125 A
specimen at (c) 15 and (d) 45 rmm, and the 40 A at (e) 15 mm and (f) 45 mm
upon annealmg at 750 og


















1x1012 i 155 a
-' 125 a
--~- so a



01x1011
A
\ =-
E
v, I ~---
r ---. ;~--~r-----a
Q)
O ~o
t; 1x1010 'h~

o



1x109
1800 2000 2200 2400

Time (s)


Figure 4.3 Defect densities for the 180, 155, 125, 80, and 40 ~i specimens annealed at
750 "C.














1x1015 I -e
-~ 125 a
--~- so a
--.- 40 a


1x1014
bt


t ~-- -
a
cI 1x1013 I





1x1012
1800 2000 2200 2400

Time (s)

Figure 4.4 Trapped interstitial concentrations for the 180, 155, 125, 80, and 40 ~i
specimens annealed at 750 "C.














~lso ~-DL
1012 155 a-DL
-' 125 a-DL
"E --.- so 8-DL
--.- 40 8-DL

E
v, 1011
A,
o
..

o

F 10101 ---5
`



O
109
1800 2000 2200 2400

Time (s)


Figure 4.5 Dislocation loop component of the overall defect density for the 180, 155, 125,
80, and 40 ~i specimens annealed at 750 "C.





















(V
E


1x1011
E
v,

o

o

~ 1x1010
O

r
r


22
I
I
Z
z
z


1x109


1800


2000


2200


2400


Time (s)


Figure 4.6 C3 1 1) defect component of the overall defect density for the 180, 155, 125,
80, and 40 ~i specimens annealed at 750 "C.


~180 A -(311)
-e 155 a -(311)
-e 125 a -(311>
so a -(311)


1x1012
















~lso a-DL
155 a-DL
-~ 125 a-DL
so ~-DL
--.- 40 ~-DL









-a


1800


2000


2200


2400


Figure 4.7 Dislocation loop component of the overall trapped interstitial concentration for
the 180, 155, 125, 80, and 40 ~i specimens annealed at 750 "C.


Time (s)














~lso a-(311)
-e 155 8-(311)
-e 125 a-(311)
--- so a-(311)


a---


1800


2000


2200


2400


Time (s)

Figure 4.8 C3 1 1) defect component of the overall trapped interstitial concentration for the
180, 155, 125, 80, and 40 ~i specimens annealed at 750 "C.













IVV A
f 30 1 -. 155~
c 125 a
~- so a
25 C 1--.- 40 a


O
20


15


10

o
5


5 o
Q 1800 2000 2200 2400

Time (s)


Figure 4.9 Average dislocation loop diameter for the 180, 155, 125, 80, and 40 ~i
specimens annealed at 750 "C.















~lso a
155 a
-~ 125 a
so a


-I


2000


2200


2400


1800


Time (s)


Figure 4.10 Average C311) defect length for the 180, 155, 125, 80, and 40 ~i specimens
annealed at 750 "C.












~C--18OO4
~ 2400


Amorphous Layer Depth (a)

Figure 4.11 Trapped interstitial concentration with respect to amorphous layer depth for
the 10 keV Ge' implant following a 750 "C anneal for 15 and 45 min.
















CHAPTER 5
LOW TEMPERATURE ANNEAL EFFECT ON ELLIPSOMETRY ACCURACY FOR
SHALLOW AMORPHOUS SILICON LAYERS




5.1 Overview

As results show in the previous chapters of this thesis, ellipsometry measurements

of shallow amorphous silicon layers are not very accurate when compared to high-

resolution transmission electron microscopy (HRTEM) results. The roughness of the

amorphous crystalline interface may be a factor which introduces error in the

ellipsometry measurements. To test this hypothesis, silicon wafers with shallow

amorphous layers were annealed at 400 OC for times ranging from 5 80 min in an

attempt to smooth out the phase transition between the amorphous layer and the

crystalline substrate. The efficacy of the low temperature anneal will be determined by

comparing ellipsometry results at each annealing time to HRTEM results. The roughness

of the amorphous/crystalline interface is then measured using HRTEM to correlate to the

improved accuracy of the ellipsometry measurements.




5.2 Experimental Results

Figure 5.1 shows the ellipsometry results compared to HRTEM measurements for

the range of annealing times at 400 OC. Ellipsometry measurements were performed at O,

5, 10, 20, 40, 60, and 80 min, while HRTEM specimens were only imaged at 0, 40, and

80 min of annealing time. In the Figure 5.1 the average of three ellipsometry










measurements are plotted with error bars representing the standard deviation of the

averages. However, the ellipsometry measurements are very precise with typical

standard deviations in the measurements < 1.0 ~i making the error bars indistinguishable

in the figure.

The influence of the anneal is clearly shown to improve the accuracy of the

ellipsometry measurements for the 5 and 10 keV case. For the 5 keV implant before the

anneal, ellipsometry measured the amorphous layer depth to 144 ~i. After a 20 min

anneal, the measured value changed to 105 ~i, an improvement of accuracy when

compared to HRTEM of- 40%. The same trend is shown with the 10 keV case. For the

30 keV case, the accuracy associated with the ellipsometry measurements was already

good and did not improve over time. At 400 "C, HRTEM showed no regrowth of the

amorphous layer up to the longest anneal time of 80 min for any of the implant energy

conditions.

The roughness of the amorphous/crystalline interface over the annealing time as

measured by HRTEM is shown in Figure 5.2. The figure shows that roughness did

decrease from the anneal, the mean peak-to-valley distance decreased. Figures 5.3 5.5

show HRTEM images of the amorphous layers for each implant energy. The images

show that 400 "C was too low to regrow the amorphous layer.



5.3 Conclusion

This experiment showed that the accuracy of ellipsometry measurements of

shallow amorphous silicon layers on silicon substrates can be improved by decreasing the

roughness of the amorphous/crystalline interface. At 400 "C, the amorphous layer was

shown not to regrow measurably at times ranging from 5 80 min. The implications of







77


this work may help researchers obtain more accurate amorphous silicon layer

measurements using the quick, nondestructive technique of VASE.





















8_ ____~g~~~~~~~g~------9














`m.
~.......................81,.............

--EI


--
-


5 ke~-ellipsometry
-n--10 keV-ellipsometry
-8--30 keV-ellipsometry
~5 keV-XTEM
~10 keV-XTEM
~30 keV-XTEM


40 60


Time (min)

Figure 5.1 Comparison of amorphous layer depth measurements between ellipsometry
and high resolution transmission electron microscopy following a 400 "C
anneal over time.





0 20 40 60 80 100


Time (mins)

Figure 5.2 Reduction in amorphous/crystalline interface roughness as measured by high-
resolution transmission electron microscopy following a 400 "C anneal.


5 keV Roughness
10 keV Roughness
30 keV roughness









100 A,


surface



t ~a/c mnterface


(a)

100 A,


surfacee


..,,5..' ** .*.-.***-**..r...*,*. '. 8/ 11terfa C O



(b)

100 A,


surface


a/c mterface


Figure 5 3 High-resolution transmission electron microscopy cross section images of 5
keV, 1 x 10 Gei cm2 implant annealed at 400 oC for (a) 0 mm, (b) 40 mmn,
and (c) 80 mmn


~"~~~ i'4?:gR E-:$ :: --'
... .*;*., .. .: .** .. .F*- "
.. *. i .: 4 .. .*. .
c.- ** **;-,*-.., .* 1 :. : ..-: :-: *











~i '




Ci& surface
ale interface


loo a


t surface


a/c interface






surface







a/c interface


e


loo a
,c1;;5~j


e


Figure 5 4


High-resolution transmission electron mlcroscopy cross section images of 10
keV, 1 x 10'5 Gei cm~2 implant annealed at 400 "C for (a)O min, (b) 40 mm,
and (c) 80 mm












100 A


Ssurface


surface










ae mterface


Figure 5 5 High-resolution transmission electron microscopy cross section un ages of 30
keV, 1 x 10" Gei cm. implant annealed at 400 oC for (a) 0 min and (b) 40















CHAPTER 6
CONCLUSIONS AND FUTURE WORK




6.1 5 keV Ge+ Defect Dissolution Study

The small, unstable defects formed as a result of a 5 keV, 1 x 10'5 Ge+ cm~2

implant into silicon were shown to have a dissolution activation energy of 1.13 f 0.14

eV, which a value much less than the energies reported for dislocation loops (4.0 5.0

ev) [38] and C311) defects (3.8 f.02 eV) [37]. The low activation energy may suggest

that the defects dissolve by a glide process rather than a diffusion-controlled climb

process. In the PTEM, the small defects show contrast consistent with dislocation loop

morphology. However, these defects do not coarsen significantly like dislocation loops

and dissolve very rapidly at high temperatures, as evident from the 1.13 eV activation

energy.

It was shown that the 5 keV defect dissolution is strongly implant energy

dependent. A lapping experiment reduced the amorphous layer of 10 keV implant, which

forms C311) defects and later stable dislocation loops, to less than that of the 5 keV

implant's amorphous layer and then the defect evolutions were compared. The 10 keV-

lapped specimen's defect evolution strongly resembled that of the un-lapped 10 keV

specimen, eliminating increased surface proximity as possible explanation for the defect

dissolution observed for the 5 keV energy. It is proposed that the 5 keV implant energy's

small straggle and the low supersaturation ofinterstitials are responsible for forming this

new defect morphology.










The results from this experiment have created as many if not more questions than

they have answered. Possible future work in this area is needed to determine at what

specific implant energy does the unstable dislocation loops form. This can be determined

by obtaining implant of the same dose at energies between 5 and 10 keV and study the

defect evolution. Another potential experiment is needed to determine the effect of

germanium in the silicon on forming the defects, whether there is a strain or chemical

influence.

In addition, the results may indicate that there is a lower supersaturation of

interstitials in the EOR for the 5 keV case. An experiment that solves for the

supersaturation of excess interstitials by measuring the diffusion enhancement of a buried

boron marker would help determine if this was true. Another experiment that may

warranted is to determine to defect dissolution activation energy for the dislocation loops

observed in for the 10 keV case to see if they dissolve with the 4-5 eV activation energy,

or if there is a step function decrease in the stability of defects as the implant energy is

reduced. A final experiment that may be warranted is to see what effect the presence of

boron may have on the defect evolution and what extent the dissolution, if any would

have on TED and boron diffusion in general.




6.2 Surface Proximity Experiment

This experiment lapped the amorphous layer of a 10 keV, 1 x 10'5 Ge+ cm~2

implant into silicon from 180 ~i to depths of 165, 125, 80 and 40 ~i for four different

specimens. The defect population was analyzed following anneals at 750 "C for 15 and

45 min to determine if there is a measurable effect from increased proximity to the

wafer's surface on excess interstitials in the EOR. It was determined that there is no clear










influence of the surface in the annihilation of interstitials for amorphous layers 80 ~i or

thicker. The specimen with a 40 ~i thick amorphous layer showed showed a slight

smaller defect and interstitial population than the thicker amorphous layer specimens at

15 min, but the trend did not hold after 45 min. This may suggests that there is somewhat

of a surface effect at distances roughly equal to the radius of a dislocation loop.




6.3 Low Temperature Anneal Effect on Ellipsometry Accuracy for Shallow
Amorphous Silicon Layers

A low temperature anneal, at 400 "C, was shown to improve the accuracy of

ellipsometry depth measurements for amorphous silicon layers on silicon substrates.

Measurements were performed on 5, 10, and 30 keV Ge' implants all at a dose of 1 x

10'5 cm~2 with no anneal and then compared to samples that had been annealed for times

~om 5 80 min. The error in amorphous layer depths was reduced from about 40 % to

practically O% after 20 min of annealing time. High resolution cross sectional

transmission electron microscopy measured a reduction in the amorphous/crystalline

interface roughness over time in the anneal, which was correlated to the improved

accuracy ofthe ellipsometry measurements.




6.4 Implications of Findings


The defects created by the 5 keV implant show that there is different regime of

damage associated with low energy, amorphizing implants that is not understood very

well at this point. The simple assumption that the surface acts to reduce the excess

interstitial supersaturation was shown to be invalid, or at least not significant. It is clear

that more investigations are necessary to construct an accurate model of extended defect










evolution associated within this regime. This will assist the semiconductors industry in its

drive to meet scaling requirements by more accurately predicting dopant diffusion

profiles as the implant energy is also scaled.

















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