Physical Sciences and Mathematics Commons^™

Interfacial Engineering And Photoelectrochemistry Of Patterned Metal/Semiconductor Heterostructures, Che Tan

McKelvey School of Engineering Theses & Dissertations

Photoelectrochemical (PEC) cells enable the conversion of solar energy into storable fuels, which is critical in overcoming the intermittent nature of this largest renewable source. However, the majority of semiconductors used as photoelectrodes in these cells have low conversion efficiencies and/or stabilities. Silicon (Si) is an attractive semiconductor material for photoelectrodes, but the development of efficient Si-based photoanodes is challenging due to their instability in alkaline solutions. Thus, one focus of this dissertation is the design and fabrication of highly stable nickel (Ni)-patterned Si photoanodes through interfacial engineering of the barrier heights. Recently, hot carriers in plasmonic metal nanostructures have …

Single-Molecule Localization Microscopy Of 3d Orientation And Anisotropic Wobble Using A Polarized Vortex Point Spread Function, Tianben Ding, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Within condensed matter, single fluorophores are sensitive probes of their chemical environments, but it is difficult to use their limited photon budget to image precisely their positions, 3D orientations, and rotational diffusion simultaneously. We demonstrate the polarized vortex point spread function (PSF) for measuring these parameters, including characterizing the anisotropy of a molecule’s wobble, simultaneously from a single image. Even when imaging dim emitters (∼500 photons detected), the polarized vortex PSF can obtain 12 nm localization precision, 4°–8° orientation precision, and 26° wobble precision. We use the vortex PSF to measure the emission anisotropy of fluorescent beads, the wobble dynamics …

The Challenges Of Applying Computational Legal Analysis To Mhealth Security And Privacy Regulations, Brian Tung

McKelvey School of Engineering Theses & Dissertations

As our world has grown in complexity, so have our laws. By one measure, the United States Code has grown over 30x as long since 1935, and the 186,000-page Code of Federal Regulations has grown almost 10x in length since 1938. Our growing legal system is too complicated; it’s impossible for people to know all the laws that apply to them. However, people are still subject to the law, even if they are unfamiliar with it. Therein lies the need for computational legal analysis. Tools of computation (e.g., data visualization, algorithms, and artificial intelligence) have the potential to transform civic …

Machine Learning For Analog/Mixed-Signal Integrated Circuit Design Automation, Weidong Cao

McKelvey School of Engineering Theses & Dissertations

Analog/mixed-signal (AMS) integrated circuits (ICs) play an essential role in electronic systems by processing analog signals and performing data conversion to bridge the analog physical world and our digital information world.Their ubiquitousness powers diverse applications ranging from smart devices and autonomous cars to crucial infrastructures. Despite such critical importance, conventional design strategies of AMS circuits still follow an expensive and time-consuming manual process and are unable to meet the exponentially-growing productivity demands from industry and satisfy the rapidly-changing design specifications from many emerging applications. Design automation of AMS IC is thus the key to tackling these challenges and has been …

Continuous-Time And Complex Growth Transforms For Analog Computing And Optimization, Oindrila Chatterjee

McKelvey School of Engineering Theses & Dissertations

Analog computing is a promising and practical candidate for solving complex computational problems involving algebraic and differential equations. At the fundamental level, an analog computing framework can be viewed as a dynamical system that evolves following fundamental physical principles, like energy minimization, to solve a computing task. Additionally, conservation laws, such as conservation of charge, energy, or mass, provide a natural way to couple and constrain spatially separated variables. Taking a cue from these observations, in this dissertation, I have explored a novel dynamical system-based computing framework that exploits naturally occurring analog conservation constraints to solve a variety of optimization …

A Neuromorphic Machine Learning Framework Based On The Growth Transform Dynamical System, Ahana Gangopadhyay

McKelvey School of Engineering Theses & Dissertations

As computation increasingly moves from the cloud to the source of data collection, there is a growing demand for specialized machine learning algorithms that can perform learning and inference at the edge in energy and resource-constrained environments. In this regard, we can take inspiration from small biological systems like insect brains that exhibit high energy-efficiency within a small form-factor, and show superior cognitive performance using fewer, coarser neural operations (action potentials or spikes) than the high-precision floating-point operations used in deep learning platforms. Attempts at bridging this gap using neuromorphic hardware has produced silicon brains that are orders of magnitude …

Photoacoustic Imaging, Feature Extraction, And Machine Learning Implementation For Ovarian And Colorectal Cancer Diagnosis, Eghbal Amidi

McKelvey School of Engineering Theses & Dissertations

Among all cancers related to women’s reproductive systems, ovarian cancer has the highest mortality rate. Pelvic examination, transvaginal ultrasound (TVUS), and blood testing for cancer antigen 125 (CA-125), are the conventional screening tools for ovarian cancer, but they offer very low specificity. Other tools, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), also have limitations in detecting small lesions. In the USA, considering men and women separately, colorectal cancer is the third most common cause of death related to cancer; for men and women combined, it is the second leading cause of cancer deaths. …

Algebraic, Computational, And Data-Driven Methods For Control-Theoretic Analysis And Learning Of Ensemble Systems, Wei Miao

McKelvey School of Engineering Theses & Dissertations

In this thesis, we study a class of problems involving a population of dynamical systems under a common control signal, namely, ensemble systems, through both control-theoretic and data-driven perspectives. These problems are stemmed from the growing need to understand and manipulate large collections of dynamical systems in emerging scientific areas such as quantum control, neuroscience, and magnetic resonance imaging. We examine fundamental control-theoretic properties such as ensemble controllability of ensemble systems and ensemble reachability of ensemble states, and propose ensemble control design approaches to devise control signals that steer ensemble systems to desired profiles. We show that these control-theoretic properties …

Improving Additional Adversarial Robustness For Classification, Michael Guo

McKelvey School of Engineering Theses & Dissertations

Although neural networks have achieved remarkable success on classification, adversarial robustness is still a significant concern. There are now a series of approaches for designing adversarial examples and methods to defending against them. This paper consists of two projects. In our first work, we propose an approach by leveraging cognitive salience to enhance additional robustness on top of these methods. Specifically, for image classification, we split an image into the foreground (salient region) and background (the rest) and allow significantly larger adversarial perturbations in the background to produce stronger attacks. Furthermore, we show that adversarial training with dual-perturbation attacks yield …

Interaction Of Aqueous U(Vi) With Goethite, Montmorillonite, And Uo2(S), Anshuman Satpathy

McKelvey School of Engineering Theses & Dissertations

Uranium contamination in subsurface environments is a matter of great concern throughout the world. Fate and transport of uranium in the subsurface can be controlled by U(VI) adsorption and reduction onto common iron (oxy)hydroxides and clay minerals. Aqueous U(VI) can also exchange uranium atoms with solids comprised of uranium which can potentially lead to changes in the morphology of the uranium-containing solids and affect their stability. First, the performance of multiple surface complexation models (SCMs) on adsorption of U(VI) onto goethite was analyzed for a broad range of input conditions. Individual models could fit the data for which they were …

Assessment And Diagnosis Of Human Colorectal And Ovarian Cancer Using Optical Imaging And Computer-Aided Diagnosis, Yifeng Zeng

McKelvey School of Engineering Theses & Dissertations

Tissue optical scattering has recently emerged as an important diagnosis parameter associated with early tumor development and progression. To characterize the differences between benign and malignant colorectal tissues, we have created an automated optical scattering coefficient mapping algorithm using an optical coherence tomography (OCT) system. A novel feature called the angular spectrum index quantifies the scattering coefficient distribution. In addition to scattering, subsurface morphological changes are also associated with the development of colorectal cancer. We have observed a specific mucosa structure indicating normal human colorectal tissue, and have developed a real-time pattern recognition neural network to localize this specific structure …

A Collaborative Knowledge-Based Security Risk Assessments Solution Using Blockchains, Tara Thaer Salman

McKelvey School of Engineering Theses & Dissertations

Artificial intelligence and machine learning have recently gained wide adaptation in building intelligent yet simple and proactive security risk assessment solutions. Intrusion identification, malware detection, and threat intelligence are examples of security risk assessment applications that have been revolutionized with these breakthrough technologies. With the increased risk and severity of cyber-attacks and the distributed nature of modern threats and vulnerabilities, it becomes critical to pose a distributed intelligent assessment solution that evaluates security risks collaboratively. Blockchain, as a decade-old successful distributed ledger technology, has the potential to build such collaborative solutions. However, in order to be used for such solutions, …

Metal Salt Hydrolysis For Electrochemically Active Conducting Polymer Nanocomposites, Hongmin Wang

Arts & Sciences Electronic Theses and Dissertations

The diversity of nanostructures obtained from organic polymerization is limited when compared to the vast amount of inorganic nanostructures. This dissertation will focus on a synergistic mechanism between organic polymerization and in situ inorganic salt hydrolysis for developing electrochemically active organic-inorganic hybrid nanostructures. The degree of polymerization, crystallinity and doping level of the conjugated polymer backbone is controlled using oxidative radical vapor-phase polymerization resulting in organic semiconductors featuring high crystallinity and superior electrical conductivity. An aqueous metal salt solution of iron (III) chloride serves as an oxidant for initiating the polymerization and interestingly, this inorganic salt hydrolyzes in situ producing …

Aerosol Vapor Synthesis Of Organic Processable Pedot Particles And Measuring Electric Conductivity Using A 3d Printed Probe Station, Yang Lu

McKelvey School of Engineering Theses & Dissertations

Conducting polymers are organic semiconductors characterized by conjugated backbones (alternating single-double bonds) that enable mixed ionic-electronic conductivity. Their polymeric nature, tunable band structure and reversible redox capability have demonstrated fundamental advances in the fields ranging from electrochemical energy storage, sensing, to electro/photo catalysis and neuromorphic engineering. Conjugated backbones, the origin of all the unique physical and chemical properties associated with conducting polymers, prevent their solubility due to high lattice energy which hinders processing. Current solution utilizes a long-chain polymer (PSS) as dopants to render conducting polymer water dispersible (PEDOT:PSS). Nonetheless, PSS is highly acidic and hydrophilic limiting applicability with acid-incompatible …

Computational Design Of Two-Dimensional Transition Metal Dichalcogenide Alloys And Their Applications, John Douglas Cavin

Arts & Sciences Electronic Theses and Dissertations

The discovery of bronze as an alloy of copper and tin is arguably the earliest form of material design, dating back thousands of years. In contrast, two-dimensional materials are new to the 21st century. The research presented in this dissertation is at the intersection of alloying and two-dimensional materials. I specifically study a class of two-dimensional materials known as transition metal dichalcogenides (TMDCs). Because of the large number of transition metals, there are many combinations of TMDCs that can be alloyed, making experimental exploration of the phase space of possible alloys unwieldly. Instead, I have applied first-principles methods to study …

Computational Modelling Enables Robust Multidimensional Nanoscopy, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

The following sections are included:

• Present State of Computational Modelling in Fluorescence Nanoscopy

• Recent Contributions to Computational Modelling in Fluorescence Nanoscopy

• Outlook on Computational Modelling in Fluorescence Nanoscopy

• Acknowledgments

• References

Deep Learning For Task-Based Image Quality Assessment In Medical Imaging, Weimin Zhou

McKelvey School of Engineering Theses & Dissertations

It has been advocated to use objective measures of image quality (IQ) for assessing and optimizing medical imaging systems. Objective measures of IQ quantify the performance of an observer at a specific diagnostic task. Binary signal detection tasks and joint signal detection and localization (detection-localization) tasks are commonly considered in medical imaging. When optimizing imaging systems for binary signal detection tasks, the performance of the Bayesian Ideal Observer (IO) has been advocated for use as a figure-of-merit (FOM). The IO maximizes the observer performance that is summarized by the receiver operating characteristic (ROC) curve. When signal detection-localization tasks are considered, …

Holistic Control For Cyber-Physical Systems, Yehan Ma

McKelvey School of Engineering Theses & Dissertations

The Industrial Internet of Things (IIoT) are transforming industries through emerging technologies such as wireless networks, edge computing, and machine learning. However, IIoT technologies are not ready for control systems for industrial automation that demands control performance of physical processes, resiliency to both cyber and physical disturbances, and energy efficiency. To meet the challenges of IIoT-driven control, we propose holistic control as a cyber-physical system (CPS) approach to next-generation industrial automation systems. In contrast to traditional industrial automation systems where computing, communication, and control are managed in isolation, holistic control orchestrates the management of cyber platforms (networks and computing platforms) …

Optical And Physicochemical Properties Of Atmospherically Processed Brown Carbon Using Novel First-Principle Instrumentation, Benjamin Sumlin

McKelvey School of Engineering Theses & Dissertations

Atmospheric processing of brown carbon (BrC) – a class of spherical, internally-mixed, light-absorbing organic aerosol – emitted from smoldering biomass combustion is an understudied phenomenon with implications for climate science, air quality models, and satellite retrieval algorithms. BrC aerosols have received significant attention as a strong contributor to atmospheric light absorption in the shorter visible wavelengths and a driver of UV photochemistry. Their complex refractive indices (m=n+ik), size distributions, and carbon oxidation states dictate their optical properties, atmospheric residence times, and chemical interactions, respectively. There is currently a gap in our understanding of these fundamental particle properties and their evolution …

Machine Learning Morphisms: A Framework For Designing And Analyzing Machine Learning Work Ows, Applied To Separability, Error Bounds, And 30-Day Hospital Readmissions, Eric Zenon Cawi

McKelvey School of Engineering Theses & Dissertations

A machine learning workflow is the sequence of tasks necessary to implement a machine learning application, including data collection, preprocessing, feature engineering, exploratory analysis, and model training/selection. In this dissertation we propose the Machine Learning Morphism (MLM) as a mathematical framework to describe the tasks in a workflow. The MLM is a tuple consisting of: Input Space, Output Space, Learning Morphism, Parameter Prior, Empirical Risk Function. This contains the information necessary to learn the parameters of the learning morphism, which represents a workflow task. In chapter 1, we give a short review of typical tasks present in a workflow, as …

Surface Modification Of Ii-Vi Semiconducting Nanocrystals, Calynn Morrison

Arts & Sciences Electronic Theses and Dissertations

This dissertation presents the compositional analysis of semiconductor materials by inductively coupled plasma optical emission spectroscopy (ICP-OES), a novel low-temperature shell growth precursor and installation pathway, and L-type for Z-type ligand exchange experiments conducted with four metal dithiocarbamate ligands. The techniques employed in the compositional analysis of semiconductor materials by inductively coupled plasma optical emission spectroscopy (ICP-OES) have a profound influence on the accuracy and reproducibility of the results. In Chapter 3, we describe methods for sample preparation, calibration, standard selection, and data collection. Specific protocols are suggested for the analysis of II-VI compounds and nanocrystals containing the elements Zn, …