Three-dimensional supercell simulation of novel semiconductor nanostructures

In this thesis we investigate atomic scale imperfections and fluctuations in the quantum transport properties of novel semiconductor nanostructures. For this purpose, we have developed a numerically efficient supercell model of quantum transport capable of representing potential variations in three dimensions. This flexibility allows us to examine new quantum device structures made possible through state-of-the-art semiconductor fabrication techniques such as molecular beam epitaxy and nanolithography. These structures, with characteristic dimensions on the order of a few nanometers, hold promise for much smaller, faster and more efficient devices than those in present operation, yet they are highly sensitive to structural and compositional variations such as defect impurities, interface roughness and alloy disorder. If these quantum structures are to serve as components of reliable, mass-produced devices, these issues must be addressed.

In Chapter 1 we discuss some of the important issues in resonant tunneling devices and mention some of thier applications. In Chapters 2 and 3, we describe our supercell model of quantum transport and an efficient numerical implementation. In the remaining chapters, we present applications.

In Chapter 4, we examine transport in single and double barrier tunneling structures with neutral impurities. We find that an isolated attractive impurity in a single barrier can produce a transmission resonance whose position and strength are sensitive to the location of the impurity within the barrier. Multiple impurities can lead to a complex resonance structure that fluctuates widely with impurity configuration. In addition, impurity resonances can give rise to negative differential resistance. In Chapter 5, we study interface roughness and alloy disorder in double barrier structures. We find that interface roughness and alloy disorder can shift and broaden the n = 1 transmission resonance and give rise to new resonance peaks, especially in the presence of clusters comparable in size to the electron deBroglie wavelength. In Chapter 6 we examine the effects of interface roughness and impurities on transmission in a quantum dot electron waveguide. We find that variation in the configuration and stoichiometry of the interface roughness leads to substantial fluctuations in the transmission properties. These fluctuations are reduced by an attractive impurity placed near the center of the dot.

Quantum simulation of enzyme catalysis

Separating the dynamics of variables that evolve on different timescales is a common assumption in exploring complex systems, and a great deal of progress has been made in understanding chemical systems by treating independently the fast processes of an activated chemical species from the slower processes that proceed activation. Protein motion underlies all biocatalytic reactions, and understanding the nature of this motion is central to understanding how enzymes catalyze reactions with such specificity and such rate enhancement. This understanding is challenged by evidence of breakdowns in the separability of timescales of dynamics in the active site form motions of the solvating protein. Quantum simulation methods that bridge these timescales by simultaneously evolving quantum and classical degrees of freedom provide an important method on which to explore this breakdown. In the following dissertation, three problems of enzyme catalysis are explored through quantum simulation.

Geometric elasticity for graphics, simulation, and computation

We develop new algorithms which combine the rigorous theory of mathematical elasticity with the geometric underpinnings and computational attractiveness of modern tools in geometry processing. We develop a simple elastic energy based on the Biot strain measure, which improves on state-of-the-art methods in geometry processing. We use this energy within a constrained optimization problem to, for the first time, provide surface parameterization tools which guarantee injectivity and bounded distortion, are user-directable, and which scale to large meshes. With the help of some new generalizations in the computation of matrix functions and their derivative, we extend our methods to a large class of hyperelastic stored energy functions quadratic in piecewise analytic strain measures, including the Hencky (logarithmic) strain, opening up a wide range of possibilities for robust and efficient nonlinear elastic simulation and geometry processing by elastic analogy.

On the solution of first excursion problems by simulation with applications to probabilistic seismic performance assessment

In a probabilistic assessment of the performance of structures subjected to uncertain environmental loads such as earthquakes, an important problem is to determine the probability that the structural response exceeds some specified limits within a given duration of interest. This problem is known as the first excursion problem, and it has been a challenging problem in the theory of stochastic dynamics and reliability analysis. In spite of the enormous amount of attention the problem has received, there is no procedure available for its general solution, especially for engineering problems of interest where the complexity of the system is large and the failure probability is small.

The application of simulation methods to solving the first excursion problem is investigated in this dissertation, with the objective of assessing the probabilistic performance of structures subjected to uncertain earthquake excitations modeled by stochastic processes. From a simulation perspective, the major difficulty in the first excursion problem comes from the large number of uncertain parameters often encountered in the stochastic description of the excitation. Existing simulation tools are examined, with special regard to their applicability in problems with a large number of uncertain parameters. Two efficient simulation methods are developed to solve the first excursion problem. The first method is developed specifically for linear dynamical systems, and it is found to be extremely efficient compared to existing techniques. The second method is more robust to the type of problem, and it is applicable to general dynamical systems. It is efficient for estimating small failure probabilities because the computational effort grows at a much slower rate with decreasing failure probability than standard Monte Carlo simulation. The simulation methods are applied to assess the probabilistic performance of structures subjected to uncertain earthquake excitation. Failure analysis is also carried out using the samples generated during simulation, which provide insight into the probable scenarios that will occur given that a structure fails.

Dynamic rupture simulation integrated with earthquake observations

Dynamic rupture simulations are unique in their contributions to the study of earthquake physics. The current rapid development of dynamic rupture simulations poses several new questions: Do the simulations reflect the real world? Do the simulations have predictive power? Which one should we believe when the simulations disagree? This thesis illustrates how integration with observations can help address these questions and reduce the effects of non-uniqueness of both dynamic rupture simulations and kinematic inversion problems. Dynamic rupture simulations with observational constraints can effectively identify non-physical features inferred from observations. Moreover, the integrative technique can also provide more physical insights into the mechanisms of earthquakes. This thesis demonstrates two examples of such kinds of integration: dynamic rupture simulations of the M_w 9.0 2011 Tohoku-Oki earthquake and of earthquake ruptures in damaged fault zones:

(1) We develop simulations of the Tohoku-Oki earthquake based on a variety of observations and minimum assumptions of model parameters. The simulations provide realistic estimations of stress drop and fracture energy of the region and explain the physical mechanisms of high-frequency radiation in the deep region. We also find that the overridding subduction wedge contributes significantly to the up-dip rupture propagation and large final slip in the shallow region. Such findings are also applicable to other megathrust earthquakes.

(2) Damaged fault zones are usually found around natural faults, but their effects on earthquake ruptures have been largely unknown. We simulate earthquake ruptures in damaged fault zones with material properties constrained by seismic and geological observations. We show that reflected waves in fault zones are effective at generating pulse-like ruptures and head waves tend to accelerate and decelerate rupture speeds. These mechanisms are robust in natural fault zones with large attenuation and off-fault plasticity. Moreover, earthquakes in damaged fault zones can propagate at super-Rayleigh speeds that are unstable in homogeneous media. Supershear transitions in fault zones do not require large fault stresses. In the end, we present observations in the Big Bear region, where variability of rupture speeds of small earthquakes correlates with the laterally variable materials in a damaged fault zone.

Direct simulation of quantum dynamics in complex systems

Accurate simulation of quantum dynamics in complex systems poses a fundamental theoretical challenge with immediate application to problems in biological catalysis, charge transfer, and solar energy conversion. The varied length- and timescales that characterize these kinds of processes necessitate development of novel simulation methodology that can both accurately evolve the coupled quantum and classical degrees of freedom and also be easily applicable to large, complex systems. In the following dissertation, the problems of quantum dynamics in complex systems are explored through direct simulation using path-integral methods as well as application of state-of-the-art analytical rate theories.

Self-healing Techniques for RF and mm-Wave Transmitters and Receivers

With continuing advances in CMOS technology, feature sizes of modern Silicon chip-sets have gone down drastically over the past decade. In addition to desktops and laptop processors, a vast majority of these chips are also being deployed in mobile communication devices like smart-phones and tablets, where multiple radio-frequency integrated circuits (RFICs) must be integrated into one device to cater to a wide variety of applications such as Wi-Fi, Bluetooth, NFC, wireless charging, etc. While a small feature size enables higher integration levels leading to billions of transistors co-existing on a single chip, it also makes these Silicon ICs more susceptible to variations. A part of these variations can be attributed to the manufacturing process itself, particularly due to the stringent dimensional tolerances associated with the lithographic steps in modern processes. Additionally, RF or millimeter-wave communication chip-sets are subject to another type of variation caused by dynamic changes in the operating environment. Another bottleneck in the development of high performance RF/mm-wave Silicon ICs is the lack of accurate analog/high-frequency models in nanometer CMOS processes. This can be primarily attributed to the fact that most cutting edge processes are geared towards digital system implementation and as such there is little model-to-hardware correlation at RF frequencies.

All these issues have significantly degraded yield of high performance mm-wave and RF CMOS systems which often require multiple trial-and-error based Silicon validations, thereby incurring additional production costs. This dissertation proposes a low overhead technique which attempts to counter the detrimental effects of these variations, thereby improving both performance and yield of chips post fabrication in a systematic way. The key idea behind this approach is to dynamically sense the performance of the system, identify when a problem has occurred, and then actuate it back to its desired performance level through an intelligent on-chip optimization algorithm. We term this technique as self-healing drawing inspiration from nature's own way of healing the body against adverse environmental effects. To effectively demonstrate the efficacy of self-healing in CMOS systems, several representative examples are designed, fabricated, and measured against a variety of operating conditions.

We demonstrate a high-power mm-wave segmented power mixer array based transmitter architecture that is capable of generating high-speed and non-constant envelope modulations at higher efficiencies compared to existing conventional designs. We then incorporate several sensors and actuators into the design and demonstrate closed-loop healing against a wide variety of non-ideal operating conditions. We also demonstrate fully-integrated self-healing in the context of another mm-wave power amplifier, where measurements were performed across several chips, showing significant improvements in performance as well as reduced variability in the presence of process variations and load impedance mismatch, as well as catastrophic transistor failure. Finally, on the receiver side, a closed-loop self-healing phase synthesis scheme is demonstrated in conjunction with a wide-band voltage controlled oscillator to generate phase shifter local oscillator (LO) signals for a phased array receiver. The system is shown to heal against non-idealities in the LO signal generation and distribution, significantly reducing phase errors across a wide range of frequencies.

Direct simulation of proton-coupled electron transfer reaction dynamics and mechanisms

Proton-coupled electron transfer (PCET) reactions are ubiquitous throughout chemistry and biology. However, challenges arise in both the the experimental and theoretical investigation of PCET reactions; the rare-event nature of the reactions and the coupling between quantum mechanical electron- and proton-transfer with the slower classical dynamics of the surrounding environment necessitates the development of robust simulation methodology. In the following dissertation, novel path-integral based methods are developed and employed for the direct simulation of the reaction dynamics and mechanisms of condensed-phase PCET.

Simulation of shock-induced bubble collapse with application to vascular injury in shockwave lithotripsy

Shockwave lithotripsy is a noninvasive medical procedure wherein shockwaves are repeatedly focused at the location of kidney stones in order to pulverize them. Stone comminution is thought to be the product of two mechanisms: the propagation of stress waves within the stone and cavitation erosion. However, the latter mechanism has also been implicated in vascular injury. In the present work, shock-induced bubble collapse is studied in order to understand the role that it might play in inducing vascular injury. A high-order accurate, shock- and interface-capturing numerical scheme is developed to simulate the three-dimensional collapse of the bubble in both the free-field and inside a vessel phantom. The primary contributions of the numerical study are the characterization of the shock-bubble and shock-bubble-vessel interactions across a large parameter space that includes clinical shockwave lithotripsy pressure amplitudes, problem geometry and tissue viscoelasticity, and the subsequent correlation of these interactions to vascular injury. Specifically, measurements of the vessel wall pressures and displacements, as well as the finite strains in the fluid surrounding the bubble, are utilized with available experiments in tissue to evaluate damage potential. Estimates are made of the smallest injurious bubbles in the microvasculature during both the collapse and jetting phases of the bubble's life cycle. The present results suggest that bubbles larger than 1 μm in diameter could rupture blood vessels under clinical SWL conditions.