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- Genre: Academic theses
- Genre: Masters Thesis
- Creators: Bakkaloglu, Bertan
- Creators: Yu, Hongbin
Description
Transportation plays a significant role in every human's life. Numerous factors, such as cost of living, available amenities, work style, to name a few, play a vital role in determining the amount of travel time. Such factors, among others, led in part to an increased need for private transportation and, consequently, leading to an increase in the purchase of private cars. Also, road safety was impacted by numerous factors such as Driving Under Influence (DUI), driver’s distraction due to the increase in the use of mobile devices while driving. These factors led to an increasing need for an Advanced Driver Assistance System (ADAS) to help the driver stay aware of the environment and to improve road safety.
EcoCAR3 is one of the Advanced Vehicle Technology Competitions, sponsored by the United States Department of Energy (DoE) and managed by Argonne National Laboratory in partnership with the North American automotive industry. Students are challenged beyond the traditional classroom environment in these competitions, where they redesign a donated production vehicle to improve energy efficiency and to meet emission standards while maintaining the features that are attractive to the customer, including but not limited to performance, consumer acceptability, safety, and cost.
This thesis presents a driver assistance system interface that was implemented as part of EcoCAR3, including the adopted sensors, hardware and software components, system implementation, validation, and testing. The implemented driver assistance system uses a combination of range measurement sensors to determine the distance, relative location, & the relative velocity of obstacles and surrounding objects together with a computer vision algorithm for obstacle detection and classification. The sensor system and vision system were tested individually and then combined within the overall system. Also, a visual and audio feedback system was designed and implemented to provide timely feedback for the driver as an attempt to enhance situational awareness and improve safety.
Since the driver assistance system was designed and developed as part of a DoE sponsored competition, the system needed to satisfy competition requirements and rules. This work attempted to optimize the system in terms of performance, robustness, and cost while satisfying these constraints.
EcoCAR3 is one of the Advanced Vehicle Technology Competitions, sponsored by the United States Department of Energy (DoE) and managed by Argonne National Laboratory in partnership with the North American automotive industry. Students are challenged beyond the traditional classroom environment in these competitions, where they redesign a donated production vehicle to improve energy efficiency and to meet emission standards while maintaining the features that are attractive to the customer, including but not limited to performance, consumer acceptability, safety, and cost.
This thesis presents a driver assistance system interface that was implemented as part of EcoCAR3, including the adopted sensors, hardware and software components, system implementation, validation, and testing. The implemented driver assistance system uses a combination of range measurement sensors to determine the distance, relative location, & the relative velocity of obstacles and surrounding objects together with a computer vision algorithm for obstacle detection and classification. The sensor system and vision system were tested individually and then combined within the overall system. Also, a visual and audio feedback system was designed and implemented to provide timely feedback for the driver as an attempt to enhance situational awareness and improve safety.
Since the driver assistance system was designed and developed as part of a DoE sponsored competition, the system needed to satisfy competition requirements and rules. This work attempted to optimize the system in terms of performance, robustness, and cost while satisfying these constraints.
ContributorsBalaji, Venkatesh (Author) / Karam, Lina J (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2019
Description
Flexible conducting materials have been in the forefront of a rapidly transforming electronics industry, focusing on wearable devices for a variety of applications in recent times. Over the past few decades, bulky, rigid devices have been replaced with a surging demand for thin, flexible, light weight, ultra-portable yet high performance electronics. The interconnects available in the market today only satisfy a few of the desirable characteristics, making it necessary to compromise one feature over another. In this thesis, a method to prepare a thin, flexible, and stretchable inter-connect is presented with improved conductivity compared to previous achievements. It satisfies most mechanical and electrical conditions desired in the wearable electronics industry. The conducting composite, prepared with the widely available, low cost silicon-based organic polymer - polydimethylsiloxane (PDMS) and silver (Ag), is sandwiched between two cured PDMS layers. These protective layers improve the mechanical stability of the inter-connect. The structure can be stretched up to 120% of its original length which can further be enhanced to over 250% by cutting it into a serpentine shape without compromising its electrical stability. The inter-connect, around 500 µm thick, can be integrated into thin electronic packaging. The synthesis process of the composite material, along with its electrical and mechanical and properties are presented in detail. Testing methods and results for mechanical and electrical stability are also illustrated over extensive flexing and stretching cycles. The materials put into test, along with conductive silver (Ag) - polydimethylsiloxane (PDMS) composite in a sandwich structure, are copper foils, copper coated polyimide (PI) and aluminum (Al) coated polyethylene terephthalate (PET).
ContributorsNandy, Mayukh (Author) / Yu, Hongbin (Thesis advisor) / Chan, Candace (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2020
Description
Though a single mode of energy transfer, optical radiation meaningfully interacts with its surrounding environment at over a wide range of physical length scales. For this reason, its reconstruction and measurement are of great importance in remote sensing, as these multi-scale interactions encode a great deal of information about distant objects, surfaces, and physical phenomena. For some remote sensing applications, obtaining a desired quantity of interest does not necessitate the explicit mapping of each point in object space to an image space with lenses or mirrors. Instead, only edge rays or physical boundaries of the sensing instrument are considered, while the spatial intensity distribution of optical energy received from a distant object informs its position, optical characteristics, or physical/chemical state.
Admittedly specialized, the principals and consequences of non-imaging optics are nevertheless applicable to heterogeneous semiconductor integration and automotive light detection and ranging (LiDAR), two important emerging technologies. Indeed, a review of relevant engineering literature finds two under-addressed remote sensing challenges. The semiconductor industry lacks an optical strain metrology with displacement resolution smaller than 100 nanometers capable of measuring strain fields between high-density interconnect lines. Meanwhile, little attention is paid to the per-meter sensing characteristics of scene-illuminating flash LiDAR in the context of automotive applications, despite the technology’s much lower cost. It is here that non-imaging optics offers intriguing instrument design and explanations of observed sensor performance at vastly different length scales.
In this thesis, an effective non-contact technique for mapping nanoscale mechanical strain fields and out-of-plane surface warping via laser diffraction is demonstrated, with application as a novel metrology for next-generation semiconductor packages. Additionally, object detection distance of low-cost automotive flash LiDAR, on the order of tens of meters, is understood though principals of optical energy transfer from the surface of a remote object to an extended multi-segment detector. Such information is of consequence when designing an automotive perception system to recognize various roadway objects in low-light scenarios.
Admittedly specialized, the principals and consequences of non-imaging optics are nevertheless applicable to heterogeneous semiconductor integration and automotive light detection and ranging (LiDAR), two important emerging technologies. Indeed, a review of relevant engineering literature finds two under-addressed remote sensing challenges. The semiconductor industry lacks an optical strain metrology with displacement resolution smaller than 100 nanometers capable of measuring strain fields between high-density interconnect lines. Meanwhile, little attention is paid to the per-meter sensing characteristics of scene-illuminating flash LiDAR in the context of automotive applications, despite the technology’s much lower cost. It is here that non-imaging optics offers intriguing instrument design and explanations of observed sensor performance at vastly different length scales.
In this thesis, an effective non-contact technique for mapping nanoscale mechanical strain fields and out-of-plane surface warping via laser diffraction is demonstrated, with application as a novel metrology for next-generation semiconductor packages. Additionally, object detection distance of low-cost automotive flash LiDAR, on the order of tens of meters, is understood though principals of optical energy transfer from the surface of a remote object to an extended multi-segment detector. Such information is of consequence when designing an automotive perception system to recognize various roadway objects in low-light scenarios.
ContributorsHoughton, Todd Kristopher (Author) / Yu, Hongbin (Thesis advisor) / Jiang, Hanqing (Committee member) / Jayasuriya, Suren (Committee member) / Zhang, Liang (Committee member) / Arizona State University (Publisher)
Created2020
Description
Respiratory behavior provides effective information to characterize lung functionality, including respiratory rate, respiratory profile, and respiratory volume. Current methods have limited capabilities of continuous characterization of respiratory behavior and are primarily targeting the measurement of respiratory rate, which has relatively less value in clinical application. In this dissertation, a wireless wearable sensor on a paper substrate is developed to continuously characterize respiratory behavior and deliver clinically relevant parameters, contributing to asthma control. Based on the anatomical analysis and experimental results, the optimum site for the wireless wearable sensor is on the midway of the xiphoid process and the costal margin, corresponding to the abdomen-apposed rib cage. At the wearing site, the linear strain change during respiration is measured and converted to lung volume by the wireless wearable sensor utilizing a distance-elapsed ultrasound. An on-board low-power Bluetooth module transmits the temporal lung volume change to a smartphone, where a custom-programmed app computes to show the clinically relevant parameters, such as forced vital capacity (FVC) and forced expiratory volume delivered in the first second (FEV1) and the FEV1/FVC ratio. Enhanced by a simple, yet effective machine-learning algorithm, a system consisting of two wireless wearable sensors accurately extracts respiratory features and classifies the respiratory behavior within four postures among different subjects, demonstrating that the respiratory behaviors are individual- and posture-dependent contributing to monitoring the posture-related respiratory diseases. The continuous and accurate monitoring of respiratory behaviors can track the respiratory disorders and diseases' progression for timely and objective approaches for control and management.
ContributorsChen, Ang (Author) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Allee, David (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2020
Description
This work analyzes and develops a point-of-load (PoL) synchronous buck converter using enhancement-mode Gallium Nitride (e-GaN), with emphasis on optimizing reverse conduction loss by using a well-known technique of placing an anti-parallel Schottky diode across the synchronous power device. This work develops an improved analytical switching model for the GaN-based converter with the Schottky diode using piecewise linear approximations.
To avoid a shoot-through between the power switches of the buck converter, a small dead-time is inserted between gate drive switching transitions. Despite optimum dead-time management for a power converter, optimum dead-times vary for different load conditions. These variations become considerably large for PoL applications, which demand high output current with low output voltages. At high switching frequencies, these variations translate into losses that contribute significantly to the total loss of the converter. To understand and quantify power loss in a hard-switching buck converter that uses a GaN power device in parallel with a Schottky diode, piecewise transitions are used to develop an analytical switching model that quantifies the contribution of reverse conduction loss of GaN during dead-time.
The effects of parasitic elements on the dynamics of the switching converter are investigated during one switching cycle of the converter. A designed prototype of a buck converter is correlated to the predicted model to determine the accuracy of the model. This comparison is presented using simulations and measurements at 400 kHz and 2 MHz converter switching speeds for load (1A) condition and fixed dead-time values. Furthermore, performance of the buck converter with and without the Schottky diode is also measured and compared to demonstrate and quantify the enhanced performance when using an anti-parallel diode. The developed power converter achieves peak efficiencies of 91.7% and 93.86% for 2 MHz and 400 KHz switching frequencies, respectively, and drives load currents up to 6A for a voltage conversion from 12V input to 3.3V output.
In addition, various industry Schottky diodes have been categorized based on their packaging and electrical characteristics and the developed analytical model provides analytical expressions relating the diode characteristics to power stage performance parameters. The performance of these diodes has been characterized for different buck converter voltage step-down ratios that are typically used in industry applications and different switching frequencies ranging from 400 KHz to 2 MHz.
To avoid a shoot-through between the power switches of the buck converter, a small dead-time is inserted between gate drive switching transitions. Despite optimum dead-time management for a power converter, optimum dead-times vary for different load conditions. These variations become considerably large for PoL applications, which demand high output current with low output voltages. At high switching frequencies, these variations translate into losses that contribute significantly to the total loss of the converter. To understand and quantify power loss in a hard-switching buck converter that uses a GaN power device in parallel with a Schottky diode, piecewise transitions are used to develop an analytical switching model that quantifies the contribution of reverse conduction loss of GaN during dead-time.
The effects of parasitic elements on the dynamics of the switching converter are investigated during one switching cycle of the converter. A designed prototype of a buck converter is correlated to the predicted model to determine the accuracy of the model. This comparison is presented using simulations and measurements at 400 kHz and 2 MHz converter switching speeds for load (1A) condition and fixed dead-time values. Furthermore, performance of the buck converter with and without the Schottky diode is also measured and compared to demonstrate and quantify the enhanced performance when using an anti-parallel diode. The developed power converter achieves peak efficiencies of 91.7% and 93.86% for 2 MHz and 400 KHz switching frequencies, respectively, and drives load currents up to 6A for a voltage conversion from 12V input to 3.3V output.
In addition, various industry Schottky diodes have been categorized based on their packaging and electrical characteristics and the developed analytical model provides analytical expressions relating the diode characteristics to power stage performance parameters. The performance of these diodes has been characterized for different buck converter voltage step-down ratios that are typically used in industry applications and different switching frequencies ranging from 400 KHz to 2 MHz.
ContributorsKoli, Gauri (Author) / Kitchen, Jennifer (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ozev, Sule (Committee member) / Arizona State University (Publisher)
Created2020
Description
This research focuses mainly on employing tunable materials to achieve dynamic radiative properties for spacecraft and building thermal management. A secondary objective is to investigate tunable materials for optical propulsion applications. The primary material investigated is vanadium dioxide (VO2), which is a thermochromic material with an insulator-to-metal phase transition. VO2 typically undergoes a dramatic shift in optical properties at T = 341 K, which can be reduced through a variety of techniques to a temperature more suitable for thermal control applications. A VO2-based Fabry-Perot variable emitter is designed, fabricated, characterized, and experimentally demonstrated. The designed emitter has high emissivity when the radiating surface temperature is above 345 K and low emissivity when the temperature is less than 341 K. A uniaxial transfer matrix method and Bruggeman effective medium theory are both introduced to model the anisotropic properties of the VO2 to facilitate the design of multilayer VO2-based devices. A new furnace oxidation process is developed for fabricating high quality VO2 and the resulting thin films undergo comprehensive material and optical characterizations. The corresponding measurement platform is developed to measure the temperature-dependent transmittance and reflectance of the fabricated Fabry-Perot samples. The variable heat rejection of the fabricated samples is demonstrated via bell jar and cryothermal vacuum calorimetry measurements. Thermal modeling of a spacecraft equipped with variable emittance radiators is also conducted to elucidate the requirements and the impact for thermochromic variable emittance technology.
The potential of VO2 to be used as an optical force modulating device is also investigated for spacecraft micropropulsion. The preliminary design considers a Fabry-Perot cavity with an anti-reflection coating which switches between an absorptive “off” state (for insulating VO2) and a reflective “on” state (for metallic VO2), thereby modulating the incident solar radiation pressure. The visible and near-infrared optical properties of the fabricated vanadium dioxide are examined to determine if there is a sufficient optical property shift in those regimes for a tunable device.
The potential of VO2 to be used as an optical force modulating device is also investigated for spacecraft micropropulsion. The preliminary design considers a Fabry-Perot cavity with an anti-reflection coating which switches between an absorptive “off” state (for insulating VO2) and a reflective “on” state (for metallic VO2), thereby modulating the incident solar radiation pressure. The visible and near-infrared optical properties of the fabricated vanadium dioxide are examined to determine if there is a sufficient optical property shift in those regimes for a tunable device.
ContributorsTaylor, Sydney June (Author) / Wang, Liping (Thesis advisor) / Wells, Valana (Committee member) / Yu, Hongbin (Committee member) / Wang, Robert (Committee member) / Thangavelautham, Jekanthan (Committee member) / Massina, Christopher J (Committee member) / Arizona State University (Publisher)
Created2020
Description
Power management circuits have been more and more widely used in various applications, while providing fully integrated voltage regulation remains a challenging topic. Switched-capacitor (SC) voltage converters have received attentions in integrated power conversion for fixed-ratio voltage conversions with good efficiency and feasibility of integration. During my PhD study, an on-chip current sensing technique is proposed to dynamically modulate both switching frequency and switch widths of SC voltage converters, enhancing fast transient response and higher efficiency across a wide range of load currents. In conjunction with SC converters, a low-dropout regulator (LDO) is implemented which is driven by a push-pull operational transconductance amplifier (OTA), whose current is mirrored and sensed with minimal power and efficiency overhead. The sensed load current directly controls the frequency and width of SC converters through a voltage-controlled oscillator (VCO) and a time-to-digital converter, respectively.
Theoretical analysis and optimization for SC DC-DC converters have been presented in prior works, however optimization of different capacitors, namely flying and input/output decoupling capacitors, in SC voltage regulators (SCVRs) under an area constraint has not been addressed. A methodology to optimize flying and decoupling capacitance for area-constrained on-chip SCVRs to achieve the highest system-level power efficiency. Considering both conversion efficiency and droop voltage against fast load transients, the proposed model determines the optimal ratio between flying and decoupling.
Based on the previous design, a fully integrated switched-capacitor voltage regulator with voltage comparison and on-chip lossless current sensing control is proposed. Based on the voltage comparison result and sensed current as the load current changes, the frequency of the SC converters are modulated for optimal efficiency. The voltage regulator targets 2.1V input voltage and 0.9V output voltage, which offers higher-voltage power transfer across chip package. A 17-phase interleaved structure is used to reduce output voltage ripple.
In 65nm CMOS, the regulator is implemented with MIM-capacitor, targeting 2.1V input voltage and 0.9V output voltage. According to the measurement results, the proposed SC voltage regulator achieves 69.6% peak efficiency at 60mA load current, which corresponds to a 4.2mW/mm2 power-area density and 12.5mW
F power-capacitance density. The efficiency across 20mA to 92mA regulator load current range is above 62%. The steady-state output voltage ripple across 22x load current range of 3.5mA-76mA is between 50mV to 60mV.
Theoretical analysis and optimization for SC DC-DC converters have been presented in prior works, however optimization of different capacitors, namely flying and input/output decoupling capacitors, in SC voltage regulators (SCVRs) under an area constraint has not been addressed. A methodology to optimize flying and decoupling capacitance for area-constrained on-chip SCVRs to achieve the highest system-level power efficiency. Considering both conversion efficiency and droop voltage against fast load transients, the proposed model determines the optimal ratio between flying and decoupling.
Based on the previous design, a fully integrated switched-capacitor voltage regulator with voltage comparison and on-chip lossless current sensing control is proposed. Based on the voltage comparison result and sensed current as the load current changes, the frequency of the SC converters are modulated for optimal efficiency. The voltage regulator targets 2.1V input voltage and 0.9V output voltage, which offers higher-voltage power transfer across chip package. A 17-phase interleaved structure is used to reduce output voltage ripple.
In 65nm CMOS, the regulator is implemented with MIM-capacitor, targeting 2.1V input voltage and 0.9V output voltage. According to the measurement results, the proposed SC voltage regulator achieves 69.6% peak efficiency at 60mA load current, which corresponds to a 4.2mW/mm2 power-area density and 12.5mW
F power-capacitance density. The efficiency across 20mA to 92mA regulator load current range is above 62%. The steady-state output voltage ripple across 22x load current range of 3.5mA-76mA is between 50mV to 60mV.
ContributorsMi, Xiaoyang (Author) / Seo, Jae-Sun (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ogras, Umit Y. (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2020
Description
Object detection is an interesting computer vision area that is concerned with the detection of object instances belonging to specific classes of interest as well as the localization of these instances in images and/or videos. Object detection serves as a vital module in many computer vision based applications. This work focuses on the development of object detection methods that exhibit increased robustness to varying illuminations and image quality. In this work, two methods for robust object detection are presented.
In the context of varying illumination, this work focuses on robust generic obstacle detection and collision warning in Advanced Driver Assistance Systems (ADAS) under varying illumination conditions. The highlight of the first method is the ability to detect all obstacles without prior knowledge and detect partially occluded obstacles including the obstacles that have not completely appeared in the frame (truncated obstacles). It is first shown that the angular distortion in the Inverse Perspective Mapping (IPM) domain belonging to obstacle edges varies as a function of their corresponding 2D location in the camera plane. This information is used to generate object proposals. A novel proposal assessment method based on fusing statistical properties from both the IPM image and the camera image to perform robust outlier elimination and false positive reduction is also proposed.
In the context of image quality, this work focuses on robust multiple-class object detection using deep neural networks for images with varying quality. The use of Generative Adversarial Networks (GANs) is proposed in a novel generative framework to generate features that provide robustness for object detection on reduced quality images. The proposed GAN-based Detection of Objects (GAN-DO) framework is not restricted to any particular architecture and can be generalized to several deep neural network (DNN) based architectures. The resulting deep neural network maintains the exact architecture as the selected baseline model without adding to the model parameter complexity or inference speed. Performance results provided using GAN-DO on object detection datasets establish an improved robustness to varying image quality and a higher object detection and classification accuracy compared to the existing approaches.
In the context of varying illumination, this work focuses on robust generic obstacle detection and collision warning in Advanced Driver Assistance Systems (ADAS) under varying illumination conditions. The highlight of the first method is the ability to detect all obstacles without prior knowledge and detect partially occluded obstacles including the obstacles that have not completely appeared in the frame (truncated obstacles). It is first shown that the angular distortion in the Inverse Perspective Mapping (IPM) domain belonging to obstacle edges varies as a function of their corresponding 2D location in the camera plane. This information is used to generate object proposals. A novel proposal assessment method based on fusing statistical properties from both the IPM image and the camera image to perform robust outlier elimination and false positive reduction is also proposed.
In the context of image quality, this work focuses on robust multiple-class object detection using deep neural networks for images with varying quality. The use of Generative Adversarial Networks (GANs) is proposed in a novel generative framework to generate features that provide robustness for object detection on reduced quality images. The proposed GAN-based Detection of Objects (GAN-DO) framework is not restricted to any particular architecture and can be generalized to several deep neural network (DNN) based architectures. The resulting deep neural network maintains the exact architecture as the selected baseline model without adding to the model parameter complexity or inference speed. Performance results provided using GAN-DO on object detection datasets establish an improved robustness to varying image quality and a higher object detection and classification accuracy compared to the existing approaches.
ContributorsPrakash, Charan Dudda (Author) / Karam, Lina (Thesis advisor) / Abousleman, Glen (Committee member) / Jayasuriya, Suren (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2020
Description
Nearly all solar photovoltaic (PV) systems are designed with maximum power point tracking (MPPT) functionality to maximize the utilization of available power from the PV array throughout the day. In conventional PV systems, the MPPT function is handled by a power electronic device, like a DC-AC inverter. However, given that most PV systems are designed to be grid-connected, there are several challenges for designing PV systems for DC-powered applications and off-grid applications. The first challenge is that all power electronic devices introduce some degree of power loss. Beyond the cost of the lost power, the upfront cost of power electronics also increases with the required power rating. Second, there are very few commercially available options for DC-DC converters that include MPPT functionality, and nearly all PV inverters are designed as “grid-following” devices, as opposed to “grid-forming” devices, meaning they cannot be used in off-grid applications.
To address the challenges of designing PV systems for high-power DC and off-grid applications, a load-managing photovoltaic (LMPV) system topology has been proposed. Instead of using power electronics, the LMPV system performs maximum power point tracking through load management. By implementing a load-management approach, the upfront costs and the power losses associated with the power electronics are avoided, both of which improve the economic viability of the PV system. This work introduces the concept of an LMPV system, provides in-depth analyses through both simulation and experimental validation, and explores several potential applications of the system, such as solar-powered commercial-scale electrolyzers for the production of hydrogen fuel or the production and purification of raw materials like caustic soda, copper, and zinc.
To address the challenges of designing PV systems for high-power DC and off-grid applications, a load-managing photovoltaic (LMPV) system topology has been proposed. Instead of using power electronics, the LMPV system performs maximum power point tracking through load management. By implementing a load-management approach, the upfront costs and the power losses associated with the power electronics are avoided, both of which improve the economic viability of the PV system. This work introduces the concept of an LMPV system, provides in-depth analyses through both simulation and experimental validation, and explores several potential applications of the system, such as solar-powered commercial-scale electrolyzers for the production of hydrogen fuel or the production and purification of raw materials like caustic soda, copper, and zinc.
ContributorsAzzolini, Joseph Anthony (Author) / Tao, Meng (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Qin, Jiangchao (Committee member) / Reno, Matthew J. (Committee member) / Arizona State University (Publisher)
Created2020
Description
The realization of Silicon based photonic devices will enable much faster data transmission than is possible today using the current electronics based devices. Group IV alloys germanium tin (GeSn) and silicon germanium tin (SiGeSn) have the potential to form an direct bandgap material and thus, they are promising candidates to develop a Si compatible light source and advance the field of silicon photonics. However, the growth of the alloys is challenging as it requires low temperature growth and proper strain management in the films during growth to prevent tin segregation. In order to satisfy these criteria, various research groups have developed novel chemical vapor deposition (CVD) reactors to deposit the films. While these reactors have been highly successful in depositing high crystal quality high Sn concentration films, they are generally expensive set-ups which utilize several turbomolecular/cryogenic pumps and/or load-lock systems. An more economical process than the state-of-the art to grow group IV materials will be highly valuable. Thus, the work presented in this dissertation was focused on deposition of group IV semiconductor thin films using simplified plasma enhanced CVD (PECVD) reactors.
Two different in-house assembled PECVD reactor systems, namely Reactor No. 1 and 2, were utilized to deposit Ge, GeSn and SiGeSn thin films. PECVD technique was used as plasma assistance allows for potentially depositing the films at growth temperatures lower than those of conventional CVD. Germane (GeH4) and Digermane (Ge2H6) were used as the Ge precursor while Disilane (Si2H6) and tin chloride (SnCl4) were used as the precursors for Si and Sn respectively. The growth conditions such as growth temperature, precursor flow rates, precursor partial pressures, and chamber pressure were varied in a wide range to optimize the growth conditions for the films. Polycrystalline Ge films and SiGeSn films with an Sn content upto 8% were deposited using Reactor No. 1 and 2. Development of epitaxial Ge buffers and GeSn films was accomplished using a modified Reactor No. 2 at temperatures <400oC without the aid of ultra-high vacuum conditions or a high temperature substrate pre-deposition bake thereby leading to a low economic and thermal budget for the deposition process.
Two different in-house assembled PECVD reactor systems, namely Reactor No. 1 and 2, were utilized to deposit Ge, GeSn and SiGeSn thin films. PECVD technique was used as plasma assistance allows for potentially depositing the films at growth temperatures lower than those of conventional CVD. Germane (GeH4) and Digermane (Ge2H6) were used as the Ge precursor while Disilane (Si2H6) and tin chloride (SnCl4) were used as the precursors for Si and Sn respectively. The growth conditions such as growth temperature, precursor flow rates, precursor partial pressures, and chamber pressure were varied in a wide range to optimize the growth conditions for the films. Polycrystalline Ge films and SiGeSn films with an Sn content upto 8% were deposited using Reactor No. 1 and 2. Development of epitaxial Ge buffers and GeSn films was accomplished using a modified Reactor No. 2 at temperatures <400oC without the aid of ultra-high vacuum conditions or a high temperature substrate pre-deposition bake thereby leading to a low economic and thermal budget for the deposition process.
ContributorsVanjaria, Jignesh (Author) / Yu, Hongbin (Thesis advisor) / Arjunan, Arul C (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2020