Matching Items (38)
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- All Subjects: Materials Science
- All Subjects: Wireless communication systems
- Creators: Krause, Stephen
- Status: Published
Description
Rapid processing and reduced end-of-range diffusion effects demonstrate that susceptor-assisted microwave annealing is an efficient processing alternative for electrically activating dopants and removing ion-implantation damage in ion-implanted semiconductors. Sheet resistance and Hall measurements provide evidence of electrical activation. Raman spectroscopy and ion channeling analysis monitor the extent of ion implantation damage and recrystallization. The presence of damage and defects in ion implanted silicon, and the reduction of the defects as a result of annealing, is observed by Rutherford backscattering spectrometry, moreover, the boron implanted silicon is further investigated by cross-section transmission electron microscopy. When annealing B+ implanted silicon, the dissolution of small extended defects and growth of large extended defects result in reduced crystalline quality that hinders the electrical activation process. Compared to B+ implanted silicon, phosphorus implanted samples experience more effective activation and achieve better crystalline quality. Comparison of end-of-range dopants diffusion resulting from microwave annealing and rapid thermal annealing (RTA) is done using secondary ion mass spectroscopy. Results from microwave annealed P+ implanted samples show that almost no diffusion occurs during time periods required for complete dopant activation and silicon recrystallization. The relative contributions to heating of the sample, by a SiC susceptor, and by Si self-heating in the microwave anneal, were also investigated. At first 20s, the main contributor to the sample's temperature rise is Si self-heating by microwave absorption.
ContributorsZhao, Zhao (Author) / Alford, Terry Lynn (Thesis advisor) / Theodore, David (Committee member) / Krause, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Distributed inference has applications in a wide range of fields such as source localization, target detection, environment monitoring, and healthcare. In this dissertation, distributed inference schemes which use bounded transmit power are considered. The performance of the proposed schemes are studied for a variety of inference problems. In the first part of the dissertation, a distributed detection scheme where the sensors transmit with constant modulus signals over a Gaussian multiple access channel is considered. The deflection coefficient of the proposed scheme is shown to depend on the characteristic function of the sensing noise, and the error exponent for the system is derived using large deviation theory. Optimization of the deflection coefficient and error exponent are considered with respect to a transmission phase parameter for a variety of sensing noise distributions including impulsive ones. The proposed scheme is also favorably compared with existing amplify-and-forward (AF) and detect-and-forward (DF) schemes. The effect of fading is shown to be detrimental to the detection performance and simulations are provided to corroborate the analytical results. The second part of the dissertation studies a distributed inference scheme which uses bounded transmission functions over a Gaussian multiple access channel. The conditions on the transmission functions under which consistent estimation and reliable detection are possible is characterized. For the distributed estimation problem, an estimation scheme that uses bounded transmission functions is proved to be strongly consistent provided that the variance of the noise samples are bounded and that the transmission function is one-to-one. The proposed estimation scheme is compared with the amplify and forward technique and its robustness to impulsive sensing noise distributions is highlighted. It is also shown that bounded transmissions suffer from inconsistent estimates if the sensing noise variance goes to infinity. For the distributed detection problem, similar results are obtained by studying the deflection coefficient. Simulations corroborate our analytical results. In the third part of this dissertation, the problem of estimating the average of samples distributed at the nodes of a sensor network is considered. A distributed average consensus algorithm in which every sensor transmits with bounded peak power is proposed. In the presence of communication noise, it is shown that the nodes reach consensus asymptotically to a finite random variable whose expectation is the desired sample average of the initial observations with a variance that depends on the step size of the algorithm and the variance of the communication noise. The asymptotic performance is characterized by deriving the asymptotic covariance matrix using results from stochastic approximation theory. It is shown that using bounded transmissions results in slower convergence compared to the linear consensus algorithm based on the Laplacian heuristic. Simulations corroborate our analytical findings. Finally, a robust distributed average consensus algorithm in which every sensor performs a nonlinear processing at the receiver is proposed. It is shown that non-linearity at the receiver nodes makes the algorithm robust to a wide range of channel noise distributions including the impulsive ones. It is shown that the nodes reach consensus asymptotically and similar results are obtained as in the case of transmit non-linearity. Simulations corroborate our analytical findings and highlight the robustness of the proposed algorithm.
ContributorsDasarathan, Sivaraman (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Reisslein, Martin (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
III-Nitride nanostructures have been an active area of research recently due to their ability to tune their optoelectronic properties. Thus far work has been done on InGaN quantum dots, nanowires, nanopillars, amongst other structures, but this research reports the creation of a new type of InGaN nanostructure, nanorings. Hexagonal InGaN nanorings were formed using Metal Organic Chemical Vapor Deposition through droplet epitaxy. The nanorings were thoroughly analyzed using x-ray diffraction, photoluminescence, electron microscopy, electron diffraction, and atomic force microscopy. Nanorings with high indium incorporation were achieved with indium content up to 50% that was then controlled using the growth time, temperature, In/Ga ratio and III/N ratio. The analysis showed that the nanoring shape is able to incorporate more indium than other nanostructures, due to the relaxing mechanism involved in the formation of the nanoring. The ideal conditions were determined to be growth of 30 second droplets with a growth time of 1 minute 30 seconds at 770 C to achieve the most well developed rings with the highest indium concentration.
ContributorsZaidi, Zohair (Author) / Mahajan, Subhash (Thesis advisor) / O'Connell, Michael J (Committee member) / Krause, Stephen (Committee member) / Arizona State University (Publisher)
Created2012
Description
Zinc oxide (ZnO) has attracted much interest during last decades as a functional material. Furthermore, ZnO is a potential material for transparent conducting oxide material competing with indium tin oxide (ITO), graphene, and carbon nanotube film. It has been known as a conductive material when doped with elements such as indium, gallium and aluminum. The solubility of those dopant elements in ZnO is still debatable; but, it is necessary to find alternative conducting materials when their form is film or nanostructure for display devices. This is a consequence of the ever increasing price of indium. In addition, a new generation solar cell (nanostructured or hybrid photovoltaics) requires compatible materials which are capable of free standing on substrates without seed or buffer layers and have the ability introduce electrons or holes pathway without blocking towards electrodes. The nanostructures for solar cells using inorganic materials such as silicon (Si), titanium oxide (TiO2), and ZnO have been an interesting topic for research in solar cell community in order to overcome the limitation of efficiency for organic solar cells. This dissertation is a study of the rational solution-based synthesis of 1-dimentional ZnO nanomaterial and its solar cell applications. These results have implications in cost effective and uniform nanomanufacturing for the next generation solar cells application by controlling growth condition and by doping transition metal element in solution.
ContributorsChoi, Hyung Woo (Author) / Alford, Terry L. (Thesis advisor) / Krause, Stephen (Committee member) / Theodore, N. David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Ball Grid Array (BGA) using lead-free or lead-rich solder materials are widely used as Second Level Interconnects (SLI) in mounting packaged components to the printed circuit board (PCB). The reliability of these solder joints is of significant importance to the performance of microelectronics components and systems. Product design/form-factor, solder material, manufacturing process, use condition, as well as, the inherent variabilities present in the system, greatly influence product reliability. Accurate reliability analysis requires an integrated approach to concurrently account for all these factors and their synergistic effects. Such an integrated and robust methodology can be used in design and development of new and advanced microelectronics systems and can provide significant improvement in cycle-time, cost, and reliability. IMPRPK approach is based on a probabilistic methodology, focusing on three major tasks of (1) Characterization of BGA solder joints to identify failure mechanisms and obtain statistical data, (2) Finite Element analysis (FEM) to predict system response needed for life prediction, and (3) development of a probabilistic methodology to predict the reliability, as well as, the sensitivity of the system to various parameters and the variabilities. These tasks and the predictive capabilities of IMPRPK in microelectronic reliability analysis are discussed.
ContributorsFallah-Adl, Ali (Author) / Tasooji, Amaneh (Thesis advisor) / Krause, Stephen (Committee member) / Alford, Terry (Committee member) / Jiang, Hanqing (Committee member) / Mahajan, Ravi (Committee member) / Arizona State University (Publisher)
Created2013
Description
Electromigration in metal interconnects is the most pernicious failure mechanism in semiconductor integrated circuits (ICs). Early electromigration investigations were primarily focused on aluminum interconnects for silicon-based ICs. An alternative metallization compatible with gallium arsenide (GaAs) was required in the development of high-powered radio frequency (RF) compound semiconductor devices operating at higher current densities and elevated temperatures. Gold-based metallization was implemented on GaAs devices because it uniquely forms a very low resistance ohmic contact and gold interconnects have superior electrical and thermal conductivity properties. Gold (Au) was also believed to have improved resistance to electromigration due to its higher melting temperature, yet electromigration reliability data on passivated Au interconnects is scarce and inadequate in the literature. Therefore, the objective of this research was to characterize the electromigration lifetimes of passivated Au interconnects under precisely controlled stress conditions with statistically relevant quantities to obtain accurate model parameters essential for extrapolation to normal operational conditions. This research objective was accomplished through measurement of electromigration lifetimes of large quantities of passivated electroplated Au interconnects utilizing high-resolution in-situ resistance monitoring equipment. Application of moderate accelerated stress conditions with a current density limited to 2 MA/cm2 and oven temperatures in the range of 300°C to 375°C avoided electrical overstress and severe Joule-heated temperature gradients. Temperature coefficients of resistance (TCRs) were measured to determine accurate Joule-heated Au interconnect film temperatures. A failure criterion of 50% resistance degradation was selected to prevent thermal runaway and catastrophic metal ruptures that are problematic of open circuit failure tests. Test structure design was optimized to reduce resistance variation and facilitate failure analysis. Characterization of the Au microstructure yielded a median grain size of 0.91 ìm. All Au lifetime distributions followed log-normal distributions and Black's model was found to be applicable. An activation energy of 0.80 ± 0.05 eV was measured from constant current electromigration tests at multiple temperatures. A current density exponent of 1.91 was extracted from multiple current densities at a constant temperature. Electromigration-induced void morphology along with these model parameters indicated grain boundary diffusion is dominant and the void nucleation mechanism controlled the failure time.
ContributorsKilgore, Stephen (Author) / Adams, James (Thesis advisor) / Schroder, Dieter (Thesis advisor) / Krause, Stephen (Committee member) / Gaw, Craig (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation introduces stochastic ordering of instantaneous channel powers of fading channels as a general method to compare the performance of a communication system over two different channels, even when a closed-form expression for the metric may not be available. Such a comparison is with respect to a variety of performance metrics such as error rates, outage probability and ergodic capacity, which share common mathematical properties such as monotonicity, convexity or complete monotonicity. Complete monotonicity of a metric, such as the symbol error rate, in conjunction with the stochastic Laplace transform order between two fading channels implies the ordering of the two channels with respect to the metric. While it has been established previously that certain modulation schemes have convex symbol error rates, there is no study of the complete monotonicity of the same, which helps in establishing stronger channel ordering results. Toward this goal, the current research proves for the first time, that all 1-dimensional and 2-dimensional modulations have completely monotone symbol error rates. Furthermore, it is shown that the frequently used parametric fading distributions for modeling line of sight exhibit a monotonicity in the line of sight parameter with respect to the Laplace transform order. While the Laplace transform order can also be used to order fading distributions based on the ergodic capacity, there exist several distributions which are not Laplace transform ordered, although they have ordered ergodic capacities. To address this gap, a new stochastic order called the ergodic capacity order has been proposed herein, which can be used to compare channels based on the ergodic capacity. Using stochastic orders, average performance of systems involving multiple random variables are compared over two different channels. These systems include diversity combining schemes, relay networks, and signal detection over fading channels with non-Gaussian additive noise. This research also addresses the problem of unifying fading distributions. This unification is based on infinite divisibility, which subsumes almost all known fading distributions, and provides simplified expressions for performance metrics, in addition to enabling stochastic ordering.
ContributorsRajan, Adithya (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Bliss, Daniel (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2014
Description
Damage detection in heterogeneous material systems is a complex problem and requires an in-depth understanding of the material characteristics and response under varying load and environmental conditions. A significant amount of research has been conducted in this field to enhance the fidelity of damage assessment methodologies, using a wide range of sensors and detection techniques, for both metallic materials and composites. However, detecting damage at the microscale is not possible with commercially available sensors. A probable way to approach this problem is through accurate and efficient multiscale modeling techniques, which are capable of tracking damage initiation at the microscale and propagation across the length scales. The output from these models will provide an improved understanding of damage initiation; the knowledge can be used in conjunction with information from physical sensors to improve the size of detectable damage. In this research, effort has been dedicated to develop multiscale modeling approaches and associated damage criteria for the estimation of damage evolution across the relevant length scales. Important issues such as length and time scales, anisotropy and variability in material properties at the microscale, and response under mechanical and thermal loading are addressed. Two different material systems have been studied: metallic material and a novel stress-sensitive epoxy polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
ContributorsZhang, Jinjun (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
The central theme of this dissertation is to understand the chemical processing science of advanced ceramic materials for biomedicine, including therapy and imaging. The secondary component focuses on the chemical processing of energy materials.
Recently, layered double hydroxide (LDH) nanoparticles (NPs) with various intercalated compounds (e.g. fluorescent molecules, radio-labeled ATP, vitamins, DNA, and drugs) have exhibited versatility and promise as a combined therapeutic and diagnostic (i.e. theranostic) vector. However, its eventual acceptance in biomedicine will be contingent on understanding the processing science, reproducibly synthesizing monodispersed NPs with controlled mean particle size (MPS), and ascertaining the efficacy of the NPs for drug delivery and imaging. First, statistical design of experiments were used to optimize the wet chemistry synthesis of (Zn, Al)-LDH NPs. A synthesis model, which allows the synthesis of nearly monodispersed NPs with controlled MPS, was developed and experimentally verified. Also, the evolution of the nanostructure was characterized, from coprecipitation to hydrothermal treatment, to identify the formation mechanisms. Next, the biocompatibility, cellular uptake and drug delivery capability of LDH NPs were studied. In an in vitro study, using cultured pancreatic adenocarcinoma BXPC3 cells, valproate-intercalated LDH NPs showed an improved efficacy (~50 fold) over the sodium valproate alone. Finally, Gd(DTPA)-intercalated LDH NPs were synthesized and characterized by proton (1H) nuclear magnetic resonance. The longitudinal relaxivity (r1) of 28.38 s-1 mM-1, which is over 6 times higher than the clinically approved contrast agent, Gd(DTPA), demonstrated the potential of this vector for use in magnetic resonance imaging.
Visible light-transparent single metal-semiconductor junction devices, which convert ultraviolet photon energy into high open circuit voltage (Voc>1.5-2 V), are highly desirable for transparent photovoltaics that can potentially power an electrochromic stack for smart windows. A Schottky junction solar cell, comprised of sputtered ZnO/ZnS heterojunction with Cr/Au contacts, was fabricated and an Voc of fî1.35 V was measured. Also, a low-cost route to form ZnO/ZnS heterojunctions by partial sulfurization of solution-grown ZnO thin films (350 nm-5 fÝm thick; conductivity comparable to phosphorus-doped Si) was demonstrated. A final study was on a cathode material for Li-ion batteries. Phase-pure LiFePO4 powders were synthesized by microwave-assisted sol-gel method and characterized.
Recently, layered double hydroxide (LDH) nanoparticles (NPs) with various intercalated compounds (e.g. fluorescent molecules, radio-labeled ATP, vitamins, DNA, and drugs) have exhibited versatility and promise as a combined therapeutic and diagnostic (i.e. theranostic) vector. However, its eventual acceptance in biomedicine will be contingent on understanding the processing science, reproducibly synthesizing monodispersed NPs with controlled mean particle size (MPS), and ascertaining the efficacy of the NPs for drug delivery and imaging. First, statistical design of experiments were used to optimize the wet chemistry synthesis of (Zn, Al)-LDH NPs. A synthesis model, which allows the synthesis of nearly monodispersed NPs with controlled MPS, was developed and experimentally verified. Also, the evolution of the nanostructure was characterized, from coprecipitation to hydrothermal treatment, to identify the formation mechanisms. Next, the biocompatibility, cellular uptake and drug delivery capability of LDH NPs were studied. In an in vitro study, using cultured pancreatic adenocarcinoma BXPC3 cells, valproate-intercalated LDH NPs showed an improved efficacy (~50 fold) over the sodium valproate alone. Finally, Gd(DTPA)-intercalated LDH NPs were synthesized and characterized by proton (1H) nuclear magnetic resonance. The longitudinal relaxivity (r1) of 28.38 s-1 mM-1, which is over 6 times higher than the clinically approved contrast agent, Gd(DTPA), demonstrated the potential of this vector for use in magnetic resonance imaging.
Visible light-transparent single metal-semiconductor junction devices, which convert ultraviolet photon energy into high open circuit voltage (Voc>1.5-2 V), are highly desirable for transparent photovoltaics that can potentially power an electrochromic stack for smart windows. A Schottky junction solar cell, comprised of sputtered ZnO/ZnS heterojunction with Cr/Au contacts, was fabricated and an Voc of fî1.35 V was measured. Also, a low-cost route to form ZnO/ZnS heterojunctions by partial sulfurization of solution-grown ZnO thin films (350 nm-5 fÝm thick; conductivity comparable to phosphorus-doped Si) was demonstrated. A final study was on a cathode material for Li-ion batteries. Phase-pure LiFePO4 powders were synthesized by microwave-assisted sol-gel method and characterized.
ContributorsSun Zhou, Xiao Di (Author) / Dey, Sandwip K (Thesis advisor) / Krause, Stephen (Committee member) / Nagaraj, Vinay J (Committee member) / Marzke, Robert (Committee member) / Arizona State University (Publisher)
Created2014
Description
Transparent conductive oxides (TCO) comprise a class of materials that exhibit unique combination of high transparency in the visible region along with high electrical conductivity. TCOs play an important role as transparent electrodes for optoelectronic devices such as solar cell panels, liquid crystal displays, transparent heat mirrors and organic light emitting devices (OLED). The most commonly used transparent electrodes in optoelectronic applications is indium tin oxide (ITO) due to its low resistivity (~ 10−4 Ω-cm) and high transmittance (~ 80 %). However, the limited supply of indium and the growing demand for ITO make the resulting fabrication costs prohibitive for future industry. Thus, cost factors have promoted the search for inexpensive materials with good electric-optical properties.
The object of this work is to study the structure-property-processing relationship and optimize a suitable transparent electrode with the intent to optimize them for flexible optoelectronics applications. The work focuses on improved processing of the mixed oxide (indium gallium zinc oxide, IGZO) thin films for superior optical and electrical properties. The study focuses on two different methods of post-deposition annealing-microwave and conventional. The microwave annealing was seen to have the dual advantage of reduced time and lower temperature, as compared to conventional annealing. Another work focuses on an indium free transparent composite electrode (TCE) where a very thin metal layer is inserted between the two TCO layers. A novel Nb2O5/Ag/Nb2O5 multilayered structure can exhibit better electrical and optical properties than a single layered TCO thin film. The focus for low cost alternative leads to a TiO2/metal/TiO2 based TCE. A systematic study was done to understand the effect of metal thickness and substituting different metals (Ag, Cu or Au) on the opto-electrical properties of the TCEs. The TiO2/Ag/TiO2 with mid Ag thickness 9.5 nm has been optimized to have a sheet resistance of 5.7 Ohm/sq. average optical transmittance of 90 % at 550 nm and figure of merit with 61.4 ×10-3 Ω-1. The TCEs showed improved optical and electrical properties when annealed in forming gas and vacuum. These dielectric/metal/dielectric multilayer TCEs have lower total thickness and are more efficient than a single-layer ITO film.
The object of this work is to study the structure-property-processing relationship and optimize a suitable transparent electrode with the intent to optimize them for flexible optoelectronics applications. The work focuses on improved processing of the mixed oxide (indium gallium zinc oxide, IGZO) thin films for superior optical and electrical properties. The study focuses on two different methods of post-deposition annealing-microwave and conventional. The microwave annealing was seen to have the dual advantage of reduced time and lower temperature, as compared to conventional annealing. Another work focuses on an indium free transparent composite electrode (TCE) where a very thin metal layer is inserted between the two TCO layers. A novel Nb2O5/Ag/Nb2O5 multilayered structure can exhibit better electrical and optical properties than a single layered TCO thin film. The focus for low cost alternative leads to a TiO2/metal/TiO2 based TCE. A systematic study was done to understand the effect of metal thickness and substituting different metals (Ag, Cu or Au) on the opto-electrical properties of the TCEs. The TiO2/Ag/TiO2 with mid Ag thickness 9.5 nm has been optimized to have a sheet resistance of 5.7 Ohm/sq. average optical transmittance of 90 % at 550 nm and figure of merit with 61.4 ×10-3 Ω-1. The TCEs showed improved optical and electrical properties when annealed in forming gas and vacuum. These dielectric/metal/dielectric multilayer TCEs have lower total thickness and are more efficient than a single-layer ITO film.
ContributorsDhar, Aritra (Author) / Alford, Terry L. (Thesis advisor) / Petuskey, William (Thesis advisor) / Krause, Stephen (Committee member) / Chizmeshya, Andrew (Committee member) / Arizona State University (Publisher)
Created2015