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- All Subjects: Electrical Engineering
- Creators: Vasileska, Dragica
Description
This dissertation explores thermal effects and electrical characteristics in metal-oxide-semiconductor field effect transistor (MOSFET) devices and circuits using a multiscale dual-carrier approach. Simulating electron and hole transport with carrier-phonon interactions for thermal transport allows for the study of complementary logic circuits with device level accuracy in electrical characteristics and thermal effects. The electrical model is comprised of an ensemble Monte Carlo solution to the Boltzmann Transport Equation coupled with an iterative solution to two-dimensional (2D) Poisson’s equation. The thermal model solves the energy balance equations accounting for carrier-phonon and phonon-phonon interactions. Modeling of circuit behavior uses parametric iteration to ensure current and voltage continuity. This allows for modeling of device behavior, analyzing circuit performance, and understanding thermal effects.
The coupled electro-thermal approach, initially developed for individual n-channel MOSFET (NMOS) devices, now allows multiple devices in tandem providing a platform for better comparison with heater-sensor experiments. The latest electro-thermal solver allows simulation of multiple NMOS and p-channel MOSFET (PMOS) devices, providing a platform for the study of complementary MOSFET (CMOS) circuit behavior. Modeling PMOS devices necessitates the inclusion of hole transport and hole-phonon interactions. The analysis of CMOS circuits uses the electro-thermal device simulation methodology alongside parametric iteration to ensure current continuity. Simulating a CMOS inverter and analyzing the extracted voltage transfer characteristics verifies the efficacy of this methodology. This work demonstrates the effectiveness of the dual-carrier electro-thermal solver in simulating thermal effects in CMOS circuits.
The coupled electro-thermal approach, initially developed for individual n-channel MOSFET (NMOS) devices, now allows multiple devices in tandem providing a platform for better comparison with heater-sensor experiments. The latest electro-thermal solver allows simulation of multiple NMOS and p-channel MOSFET (PMOS) devices, providing a platform for the study of complementary MOSFET (CMOS) circuit behavior. Modeling PMOS devices necessitates the inclusion of hole transport and hole-phonon interactions. The analysis of CMOS circuits uses the electro-thermal device simulation methodology alongside parametric iteration to ensure current continuity. Simulating a CMOS inverter and analyzing the extracted voltage transfer characteristics verifies the efficacy of this methodology. This work demonstrates the effectiveness of the dual-carrier electro-thermal solver in simulating thermal effects in CMOS circuits.
ContributorsDaugherty, Robin (Author) / Vasileska, Dragica (Thesis advisor) / Aberle, James T., 1961- (Committee member) / Ferry, David (Committee member) / Goodnick, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
Description
Wurtzite (In, Ga, Al) N semiconductors, especially InGaN material systems, demonstrate immense promises for the high efficiency thin film photovoltaic (PV) applications for future generation. Their unique and intriguing merits include continuously tunable wide band gap from 0.70 eV to 3.4 eV, strong absorption coefficient on the order of ∼105 cm−1, superior radiation resistance under harsh environment, and high saturation velocities and high mobility. Calculation from the detailed balance model also revealed that in multi-junction (MJ) solar cell device, materials with band gaps higher than 2.4 eV are required to achieve PV efficiencies greater than 50%, which is practically and easily feasible for InGaN materials. Other state-of-art modeling on InGaN solar cells also demonstrate great potential for applications of III-nitride solar cells in four-junction solar cell devices as well as in the integration with a non-III-nitride junction in multi-junction devices.
This dissertation first theoretically analyzed loss mechanisms and studied the theoretical limit of PV performance of InGaN solar cells with a semi-analytical model. Then three device design strategies are proposed to study and improve PV performance: band polarization engineering, structural design and band engineering. Moreover, three physical mechanisms related to high temperature performance of InGaN solar cells have been thoroughly investigated: thermal reliability issue, enhanced external quantum efficiency (EQE) and conversion efficiency with rising temperatures and carrier dynamics and localization effects inside nonpolar m-plane InGaN quantum wells (QWs) at high temperatures. In the end several future work will also be proposed.
Although still in its infancy, past and projected future progress of device design will ultimately achieve this very goal that III-nitride based solar cells will be indispensable for today and future’s society, technologies and society.
This dissertation first theoretically analyzed loss mechanisms and studied the theoretical limit of PV performance of InGaN solar cells with a semi-analytical model. Then three device design strategies are proposed to study and improve PV performance: band polarization engineering, structural design and band engineering. Moreover, three physical mechanisms related to high temperature performance of InGaN solar cells have been thoroughly investigated: thermal reliability issue, enhanced external quantum efficiency (EQE) and conversion efficiency with rising temperatures and carrier dynamics and localization effects inside nonpolar m-plane InGaN quantum wells (QWs) at high temperatures. In the end several future work will also be proposed.
Although still in its infancy, past and projected future progress of device design will ultimately achieve this very goal that III-nitride based solar cells will be indispensable for today and future’s society, technologies and society.
ContributorsHuang, Xuanqi (Author) / Zhao, Yuji (Thesis advisor) / Goodnick, Stephen M. (Committee member) / King, Richard R. (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2020
Description
Advanced and mature computer simulation methods exist in fluid dynamics, elec-
tromagnetics, semiconductors, chemical transport, and even chemical and material
electronic structure. However, few general or accurate methods have been developed
for quantum photonic devices. Here, a novel approach utilizing phase-space quantum
mechanics is developed to model photon transport in ring resonators, a form of en-
tangled pair source. The key features the model needs to illustrate are the emergence
of non-classicality and entanglement between photons due to nonlinear effects in the
ring. The quantum trajectory method is subsequently demonstrated on a sequence
of elementary models and multiple aspects of the ring resonator itself.
tromagnetics, semiconductors, chemical transport, and even chemical and material
electronic structure. However, few general or accurate methods have been developed
for quantum photonic devices. Here, a novel approach utilizing phase-space quantum
mechanics is developed to model photon transport in ring resonators, a form of en-
tangled pair source. The key features the model needs to illustrate are the emergence
of non-classicality and entanglement between photons due to nonlinear effects in the
ring. The quantum trajectory method is subsequently demonstrated on a sequence
of elementary models and multiple aspects of the ring resonator itself.
ContributorsWelland, Ian Matthew (Author) / Ferry, David K. (Thesis advisor) / Goodnick, Stephen (Thesis advisor) / Zhao, Yuji (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2020
Description
The quest to find efficient algorithms to numerically solve differential equations isubiquitous in all branches of computational science. A natural approach to address
this problem is to try all possible algorithms to solve the differential equation and
choose the one that is satisfactory to one's needs. However, the vast variety of algorithms
in place makes this an extremely time consuming task. Additionally, even
after choosing the algorithm to be used, the style of programming is not guaranteed
to result in the most efficient algorithm. This thesis attempts to address the same
problem but pertinent to the field of computational nanoelectronics, by using PETSc
linear solver and SLEPc eigenvalue solver packages to efficiently solve Schrödinger
and Poisson equations self-consistently.
In this work, quasi 1D nanowire fabricated in the GaN material system is considered
as a prototypical example. Special attention is placed on the proper description
of the heterostructure device, the polarization charges and accurate treatment of the
free surfaces. Simulation results are presented for the conduction band profiles, the
electron density and the energy eigenvalues/eigenvectors of the occupied sub-bands
for this quasi 1D nanowire. The simulation results suggest that the solver is very
efficient and can be successfully used for the analysis of any device with two dimensional
confinement. The tool is ported on www.nanoHUB.org and as such is freely
available.
this problem is to try all possible algorithms to solve the differential equation and
choose the one that is satisfactory to one's needs. However, the vast variety of algorithms
in place makes this an extremely time consuming task. Additionally, even
after choosing the algorithm to be used, the style of programming is not guaranteed
to result in the most efficient algorithm. This thesis attempts to address the same
problem but pertinent to the field of computational nanoelectronics, by using PETSc
linear solver and SLEPc eigenvalue solver packages to efficiently solve Schrödinger
and Poisson equations self-consistently.
In this work, quasi 1D nanowire fabricated in the GaN material system is considered
as a prototypical example. Special attention is placed on the proper description
of the heterostructure device, the polarization charges and accurate treatment of the
free surfaces. Simulation results are presented for the conduction band profiles, the
electron density and the energy eigenvalues/eigenvectors of the occupied sub-bands
for this quasi 1D nanowire. The simulation results suggest that the solver is very
efficient and can be successfully used for the analysis of any device with two dimensional
confinement. The tool is ported on www.nanoHUB.org and as such is freely
available.
ContributorsBaikadi, Pranay Kumar Reddy (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Povolotskyi, Mykhailo (Committee member) / Arizona State University (Publisher)
Created2020
Description
Wurtzite (B, Ga, Al) N semiconductors, especially (Ga, Al) N material systems, demonstrate immense promises to boost the economic growth in the semiconductor industry that is approaching the end of Moore’s law. At the material level, their high electric field strength, high saturation velocity, and unique heterojunction polarization charge have enabled tremendous potentials for high power, high frequency, and photonic applications. With the availability of large-area bulk GaN substrates and high-quality epilayer on foreign substrates, the power conversion applications of GaN are now at the cusp of commercialization.Despite these encouraging advances, there remain two critical hurdles in GaN-based technology: selective area doping and hole-based p-channel devices. Current selective area doping methods are still immature and lead to low-quality lateral p-n junctions, which prevent the realization of advanced power transistors and rectifiers. The missing of hole-based p-channel devices hinders the development of GaN complementary integrated circuits.
This thesis comprehensively studied these challenges. The first part (chapter 2) researched the selective area doping by etch-then-regrow. A GaN-based vertical-channel junction field-effect transistors (VC-JFETs) was experimentally demonstrated by blanket regrowth and self-planarization. The devices’ electrical performances were characterized to understand the regrowth quality. The non-ideal factors during p-GaN regrowth were also discussed. The second part (chapter 3-5) systematically studied the application of the hydrogen plasma treatment process to change the p-GaN properties selectively. A novel GaN-based metal-insulator-semiconductor junction was demonstrated. Then a novel edge termination design with avalanche breakdown capability achieved in GaN power rectifiers is proposed. The last part (Chapter 6) demonstrated a GaN-based p-channel heterojunction field-effect transistor, with record low leakage, subthreshold swing, and a record high on/off ratio. In the end, some outlook and future work have also been proposed.
Although in infancy, the demonstrated etch-then-regrow and the hydrogen plasma treatment methods have the potential to ultimately solve the challenges in GaN and benefit the development of the wide-ultra-wide bandgap industry, technology, and society.
ContributorsYang, Chen (Author) / Zhao, Yuji (Thesis advisor) / Goodnick, Stephen (Committee member) / Yu, Hongbin (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2021
Forward and Backward Machine Learning for Modeling Copper Diffusion in Cadmium Telluride Solar Cells
Description
To optimize solar cell performance, it is necessary to properly design the doping profile in the absorber layer of the solar cell. For CdTe solar cells, Cu is used for providing p-type doping. Hence, having an estimator that, given the diffusion parameter set (time and Temperature) and the doping concentration at the junction, gives the junction depth of the absorber layer, is essential in the design process of CdTe solar cells (and other cell technologies). In this work it is called a forward (direct) estimation process. The backward (inverse) problem then is the one in which, given the junction depth and the desired concentration of Cu doping at the CdTe/CdS heterointerface, the estimator gives the time and/or the Temperature needed to achieve the desired doping profiles. This is called a backward (inverse) estimation process. Such estimators, both forward and backward, do not exist in the literature for solar cell technology. To train the Machine Learning (ML) estimator, it is necessary to first generate a large set of data that are obtained by using the PVRD-FASP Solver, which has been validated via comparison with experimental values. Note that this big dataset needs to be generated only once. Next, one uses Machine Learning (ML), Deep Learning (DL) and Artificial Intelligence (AI) to extract the actual Cu doping profiles that result from the process of diffusion, annealing, and cool-down in the fabrication sequence of CdTe solar cells. Two deep learning neural network models are used: (1) Multilayer Perceptron Artificial Neural Network (MLPANN) model using a Keras Application Programmable Interface (API) with TensorFlow backend, and (2) Radial Basis Function Network (RBFN) model to predict the Cu doping profiles for different Temperatures and durations of the annealing process. Excellent agreement between the simulated results obtained with the PVRD-FASP Solver and the predicted values is obtained. It is important to mention here that it takes a significant amount of time to generate the Cu doping profiles given the initial conditions using the PVRD-FASP Solver, because solving the drift-diffusion-reaction model is mathematically a stiff problem and leads to numerical instabilities if the time steps are not small enough, which, in turn, affects the time needed for completion of one simulation run. The generation of the same with Machine Learning (ML) is almost instantaneous and can serve as an excellent simulation tool to guide future fabrication of optimal doping profiles in CdTe solar cells.
ContributorsSalman, Ghaith (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen M. (Thesis advisor) / Ringhofer, Christian (Committee member) / Banerjee, Ayan (Committee member) / Arizona State University (Publisher)
Created2021
Description
Wide bandgap semiconductors, also known as WBG semiconductors are materials which have larger bandgaps than conventional semiconductors such as Si or GaAs. They permit devices to operate at much higher voltages, frequencies and temperatures. They are the key material used to make LEDs, lasers, radio frequency applications, military applications, and power electronics. Their intrinsic qualities make them promising for next-generation devices for general semiconductor use. Their ability to handle higher power density is particularly attractive for attempts to sustain Moore's law, as conventional technologies appear to be reaching a bottleneck. Apart from WBG materials, ultra-wide bandgap (UWBG) materials, such as Ga2O3, AlN, diamond, or BN, are also attractive since they have even more extreme properties. Although this field is relatively new, which still remains a lot of effort to study and investigate, people can still expect that these materials could be the main characters for more advanced applications in the near future.
In the dissertation, three topics with power devices made by WBG or UWBG semiconductors were introduced. In chapter 1, a generally background knowledge introduction is given. This helps the reader to learn current research focuses. In chapter 2, a comprehensive study of temperature-dependent characteristics of Ga2O3 SBDs with highly-doped substrate is demonstrated. A modified thermionic emission model over an inhomogeneous barrier with a voltage-dependent barrier height is investigated. Besides, the mechanism of surface leakage current is also discussed. These results are beneficial for future developments of low-loss β-Ga2O3 electronics and optoelectronics. In chapter 3, vertical GaN Schottky barrier diodes (SBDs) with floating metal rings (FMRs) as edge termination structures on bulk GaN substrates was introduced. This work represents a useful reference for the FMR termination design for GaN power devices. In chapter 4, AlGaN/GaN metal-insulator-semiconductor high electron mobility transistors (MISHEMTs) fabricated on Si substrates with a 10 nm boron nitride (BN) layer as gate dielectric was demonstrated. The material characterization was investigated by X-ray photoelectric spectroscopy (XPS) and UV photoelectron spectroscopy (UPS). And the gate leakage current mechanisms were also investigated by temperature-dependent current-voltage measurements.
Although still in its infancy, past and projected future progress of electronic designs will ultimately achieve this very goal that WBG and UWBG semiconductors will be indispensable for today and future’s science, technologies and society.
ContributorsYang, Tsung-Han (Author) / Zhao, Yuji (Thesis advisor) / Vasileska, Dragica (Committee member) / Yu, Hongbin (Committee member) / Nemanich, Robert (Committee member) / Arizona State University (Publisher)
Created2021
Description
Self-heating degrades the performance of devices in advanced technology nodes. Understanding of self-heating effects is necessary to improve device performance. Heat generation in these devices occurs at nanometer scales but heat transfer is a microscopic phenomena. Hence a multi-scale modeling approach is required to study the self-heating effects. A state of the art Monte Carlo device simulator and the commercially available Giga 3D tool from Silvaco are used in our study to understand the self heating effects. The Monte Carlo device simulator solves the electrical transport and heat generation for nanometer length scales accurately while the Giga 3D tool solves for thermal transport over micrometer length scales. The approach used is to understand the self-heating effects in a test device structure, composed of a heater and a sensor, fabricated and characterized by IMEC. The heater is the Device Under Test(DUT) and the sensor is used as a probe. Therefore, the heater is biased in the saturation region and the sensor is biased in the sub-threshold regime. Both are planar MOSFETs of gate length equal to 22 nm. The simulated I-V characteristics of the sensor match with the experimental behavior at lower applied drain voltages but differ at higher applied biases.
The self-heating model assumes that the heat transport within the device follows Energy Balance model which may not be accurate. To properly study heat transport within the device, a state of the art Monte Carlo device simulator is necessary. In this regard, the Phonon Monte Carlo(PMC) simulator is developed. Phonons are treated as quasi particles that carry heat energy. Like electrons, phonons obey a corresponding Boltzmann Transport Equation(BTE) which can be used to study their transport. The direct solution of the BTE for phonons is possible, but it is difficult to incorporate all scattering mechanisms. In the Monte Carlo based solution method, it is easier to incorporate different relevant scattering mechanisms. Although the Monte Carlo method is computationally intensive, it provides good insight into the physical nature of the transport problem. Hence Monte Carlo based techniques are used in the present work for studying phonon transport. Monte Carlo simulations require calculating the scattering rates for different scattering processes. In the present work, scattering rates for three phonon interactions are calculated from different approaches presented in the literature. Optical phonons are also included in the transport problem. Finally, the temperature dependence of thermal conductivity for silicon is calculated in the range from 100K to 900K and is compared to available experimental data.
The self-heating model assumes that the heat transport within the device follows Energy Balance model which may not be accurate. To properly study heat transport within the device, a state of the art Monte Carlo device simulator is necessary. In this regard, the Phonon Monte Carlo(PMC) simulator is developed. Phonons are treated as quasi particles that carry heat energy. Like electrons, phonons obey a corresponding Boltzmann Transport Equation(BTE) which can be used to study their transport. The direct solution of the BTE for phonons is possible, but it is difficult to incorporate all scattering mechanisms. In the Monte Carlo based solution method, it is easier to incorporate different relevant scattering mechanisms. Although the Monte Carlo method is computationally intensive, it provides good insight into the physical nature of the transport problem. Hence Monte Carlo based techniques are used in the present work for studying phonon transport. Monte Carlo simulations require calculating the scattering rates for different scattering processes. In the present work, scattering rates for three phonon interactions are calculated from different approaches presented in the literature. Optical phonons are also included in the transport problem. Finally, the temperature dependence of thermal conductivity for silicon is calculated in the range from 100K to 900K and is compared to available experimental data.
ContributorsShaik, Abdul Rawoof (Author) / Vasileska, Dragica (Thesis advisor) / Ferry, David (Committee member) / Goodnick, Stephan (Committee member) / Arizona State University (Publisher)
Created2016