Physics Commons^™

Design, Fabrication, And Characterization Of Advanced High-Power Single-Mode 9xxnm Semiconductor Lasers, Xiaolei Zhao

All Dissertations

This thesis presents the comprehensive design, fabrication, and demonstration of advanced high-power, high-efficiency single-mode semiconductor lasers operating at a wavelength of 9xxnm. We begin with the design of the laser epitaxial structure, serving as the cornerstone for achieving high-power high-efficiency lasers. Our methodology integrates a semi-analytical calculation model, which accounts for Longitudinal Spatial Hole Burning (LSHB) and Two-Photon Absorption (TPA) effects, facilitating a thorough exploration of how design parameters influence output power and conversion efficiency. This approach offers an effective and time-efficient epitaxial structure optimization strategy compared to conventional full 3D simulation models.

Subsequently, we demonstrate high-power, high-efficiency ridge waveguide …

6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We develop six-dimensional single-molecule orientation-localization microscopy (SMOLM) to measure the 3D positions and 3D orientations simultaneously of single fluorophores. We show how careful optimization of phase and polarization modulation components can encode phase, polarization, and angular spectrum information from each fluorescence photon into a microscope’s dipole-spread function. We used the transient binding and blinking of Nile red (NR) to characterize the helical structure of fibrils formed by designed amphipathic peptides, KFE8^L and KFE8^D, and the pathological amyloid-beta peptide Aβ42. We also deployed merocyanine 540 to uncover the interfacial architectures of biomolecular condensates.

Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Convolutional neural networks (CNNs) have become instrumental in advancing multi-frame image super-resolution (SR), a technique that merges multiple low-resolution images of the same scene into a high-resolution image. In this paper, a novel deep learning multi-frame SR algorithm is introduced. The proposed CNN model, named Exponential Fusion of Interpolated Frames Network (EFIF-Net), seamlessly integrates fusion and restoration within an end-to-end network. Key features of the new EFIF-Net include a custom exponentially weighted fusion (EWF) layer for image fusion and a modification of the Residual Channel Attention Network for restoration to deblur the fused image. Input frames are registered with subpixel …

Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor physical activity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a millimeter-wave (mmwave) radar sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can …

Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patniak

Faculty Publications

We examine the electromagnetic emission from two photo-illuminated linear arrays composed of inductively charged superconducting ring elements. The arrays are illuminated by an ultrafast infrared laser that triggers microwave broadband emission detected in the 1–26 GHz range. Based on constructive interference from the arrays a narrowing of the forward radiation lobe is observed with increasing element count and frequency demonstrating directed GHz emission. Results suggest that higher frequencies and a larger number of elements are achievable leading to a unique pulsed array emitter concept that can span frequencies from the microwave to the terahertz (THz) regime.

Boundary Integral Equation Methods For Superhydrophobic Flow And Integrated Photonics, Kosuke Sugita

Dissertations

This dissertation presents fast integral equation methods (FIEMs) for solving two important problems encountered in practical engineering applications.

The first problem involves the mixed boundary value problem in two-dimensional Stokes flow, which appears commonly in computational fluid mechanics. This problem is particularly relevant to the design of microfluidic devices, especially those involving superhydrophobic (SH) flows over surfaces made of composite solid materials with alternating solid portions, grooves, or air pockets, leading to enhanced slip.

The second problem addresses waveguide devices in two dimensions, governed by the Helmholtz equation with Dirichlet conditions imposed on the boundary. This problem serves as a …

Design And Fabrication Of A Trapped Ion Quantum Computing Testbed, Christopher A. Caron

Masters Theses

Here we present the design, assembly and successful ion trapping of a room-temperature ion trap system with a custom designed and fabricated surface electrode ion trap, which allows for rapid prototyping of novel trap designs such that new chips can be installed and reach UHV in under 2 days. The system has demonstrated success at trapping and maintaining both single ions and cold crystals of ions. We achieve this by fabricating our own custom surface Paul traps in the UMass Amherst cleanroom facilities, which are then argon ion milled, diced, mounted and wire bonded to an interposer which is placed …

Adaptive Plasmonic Metasurfaces For Radiative Cooling And Passive Thermoregulation, Azadeh Didari-Bader, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri

Engineering Faculty Articles and Research

In this work, we investigate a class of planar photonic structures operating as passive thermoregulators. The radiative cooling process is adjusted through the incorporation of a phase change material (Vanadium Dioxide, VO₂) in conjunction with a layer of transparent conductive oxide (Aluminum-doped Zinc Oxide, AZO). VO₂ is known to undergo a phase transition from the “dielectric” phase to the “plasmonic” or “metallic” phase at a critical temperature close to 68°C. In addition, AZO shows plasmonic properties at the long-wave infrared spectrum, which, combined with VO₂, provides a rich platform to achieve low reflections across the …

Cellulose Nanocrystal Dielectric Elastomers, David Frailey

Theses and Dissertations

Optical devices, such as filters and sensors, have numerous advantages including compactness in size and immunity from electromagnetic interference. The fabrication of optical devices often requires precision and complicated processing, resulting in expensive and delicate components. Cellulose nanocrystals (CNCs) are biomaterials that can self-assemble into liquid crystals, similar to those used in electronic displays. This material can function as an optical grating by reflecting/transmitting circularly polarized light at certain wavelengths and viewing angles. Since gratings are building blocks of optical systems, like lasers and lidars, their fabrication at low costs will enable the further proliferation of optical technologies. Furthermore, if …

Analysis And Application Of Finite Element And High-Order Finite Difference Methods For Maxwell’S Equations In Complex Media, Li Zhu

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Perfectly Matched Layer (PML) technique is an effective tool introduced by B´erenger [13] to reduce the unbounded wave propagation problem to a bounded domain problem. This dissertation focuses on two different PML models and their applications to wave propagation problems with Maxwell’s equation in complex media. We investigate these models using two popular numerical methods: the Finite Difference Method (FDM) in Chapters 2 and 3, and the Finite Element Method (FEM) in Chapters 4 and 5.In Chapter 2, we focus on analyzing the stability of a PML developed by B’ecache et al. [10] for simulating wave propagation in the …

Effect On Focusing Fields By Ferromagnetic Cell Cores In Linear Induction Accelerators, Cooper Guillaume

Senior Honors Theses

In the Los Alamos National Laboratories DARHT facility, there are two perpendicular linear induction accelerators, LIAs. The LIAs’ solenoids produce magnetic fields which focus the electron beam. Simultaneously, the accelerating pulse creates a magnetic field. These two field intensities act upon a ferromagnetic material in the cells to enhance magnetic flux density. Due to the nonlinearity of the material, this flux density will reach a saturation point. In turn, the magnetic field intensity of the axial solenoidal magnetic field will be affected and slightly altered. The width of the electron beam will increase, causing a decrease in effectiveness. Through simulation, …

Measurements Of Magnetic Field Penetration Of Materials For Superconducting Radiofrequency Cavities, Iresha Harshani Senevirathne

Physics Theses & Dissertations

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently high purity niobium is the material of choice for SRF cavities which have been optimized to operate near their theoretical field limits. This brings about the need for significant R&D efforts to develop next generation superconducting materials which could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under high RF magnetic field without penetration of quantized …

Computational Design Of Fiber-Optic Probes For Biosensing, Suwarna Karna

Electrical Engineering Theses

This thesis presents a study on the optical characteristics of hollow-core photonic crystal fibers (HC-PCFs) with a band gap cladding structure and their applications in optical fiber sensing. This 800B HC-PCF exhibited excellent optical properties and has a flexible structure, which makes them suitable for a wide range of industrial applications. Finite element simulations and structural optimization designs were conducted using the surface plasmon resonance (SPR) technique to determine the optimal performance parameters of the 800B HC-PCF. The fiber was further modified using the SPR technique to improve its practical detection capabilities. The performance of the modified fiber was observed …

A High-Precision Electron Emission Model: Computational Methods For Nanoscale Structures, Alister J. Tencate

Graduate Research Theses & Dissertations

The high-intensity, high-brightness and precision frontiers for charged particle beams are an increasingly important focus for study. Electron microscopy has demonstrated high quality beams from a single nanotip emitter, and cathodes of structured nanoscale arrays show promise as ultracold electron sources. Optimization of the cathode design for precision applications necessitates a detailed treatment of the interplay between the structure geometry, quantum mechanical emission mechanism, and electromagnetic interactions between the emitted electrons and the boundary interface. This dissertation details the numerical tools developed to simulate these processes efficiently with enough fidelity to be accurate even in the ultracold regime.

Conventional simulation …

The Effect Of The Width Of The Incident Pulse To The Dielectric Transition Layer In The Scattering Of An Electromagnetic Pulse — A Qubit Lattice Algorithm Simulation, George Vahala, Linda Vahala, Abhay K. Ram, Min Soe

Electrical & Computer Engineering Faculty Publications

The effect of the thickness of the dielectric boundary layer that connects a material of refractive index n₁ to another of index n₂is considered for the propagation of an electromagnetic pulse. A qubit lattice algorithm (QLA), which consists of a specially chosen non-commuting sequence of collision and streaming operators acting on a basis set of qubits, is theoretically determined that recovers the Maxwell equations to second-order in a small parameter ϵ. For very thin boundary layer the scattering properties of the pulse mimics that found from the Fresnel jump conditions for a plane wave - except that …

Carrier Transport Engineering In Wide Bandgap Semiconductors For Photonic And Memory Device Applications, Ravi Teja Velpula

Dissertations

Wide bandgap (WBG) semiconductors play a crucial role in the current solid-state lighting technology. The AlGaN compound semiconductor is widely used for ultraviolet (UV) light-emitting diodes (LEDs), however, the efficiency of these LEDs is largely in a single-digit percentage range due to several factors. Until recently, AlInN alloy has been relatively unexplored, though it holds potential for light-emitters operating in the visible and UV regions. In this dissertation, the first axial AlInN core-shell nanowire UV LEDs operating in the UV-A and UV-B regions with an internal quantum efficiency (IQE) of 52% are demonstrated. Moreover, the light extraction efficiency of this …

Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Imaging of both the positions and orientations of single fluorophores, termed single-molecule orientation-localization microscopy, is a powerful tool for the study of biochemical processes. However, the limited photon budget associated with single-molecule fluorescence makes high-dimensional imaging with isotropic, nanoscale spatial resolution a formidable challenge. Here we realize a radially and azimuthally polarized multi-view reflector (raMVR) microscope for the imaging of the three-dimensional (3D) positions and 3D orientations of single molecules, with precisions of 10.9 nm and 2.0° over a 1.5-μm depth range. The raMVR microscope achieves 6D super-resolution imaging of Nile red molecules transiently bound to lipid-coated spheres, accurately resolving …

Oam-Based Wavelets In A High Speed Optical Probing System For Measuring The Angular Decomposition Of The Environment, Justin Free

All Theses

This thesis presents the theoretical development of orbital angular momentum (OAM) based wavelets for the analysis of localized OAM information in space. An optical probing system for generating and detecting these wavelets is demonstrated; individual wavelets can scan the environment in 10µs or less. The probing system was applied to a three-dimensional atmospheric turbulence distribution to obtain a continuous wavelet transform of the angular information of the turbulent propagation path about a fixed radius. An entire continuous wavelet transform was measured in 3.8ms; the measurements are much faster than the turbulence and give insight into the short time scale of …

A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Lung segmentation plays an important role in computer-aided detection and diagnosis using chest radiographs (CRs). Currently, the U-Net and DeepLabv3+ convolutional neural network architectures are widely used to perform CR lung segmentation. To boost performance, ensemble methods are often used, whereby probability map outputs from several networks operating on the same input image are averaged. However, not all networks perform adequately for any specific patient image, even if the average network performance is good. To address this, we present a novel multi-network ensemble method that employs a selector network. The selector network evaluates the segmentation outputs from several networks; on …

Electro-Optical Sensors For Atmospheric Turbulence Strength Characterization With Embedded Edge Ai Processing Of Scintillation Patterns, Ernst Polnau, Don L. N. Hettiarachchi, Mikhail A. Vorontsov

Electro-Optics and Photonics Faculty Publications

This study introduces electro-optical (EO) sensors (TurbNet sensors) that utilize a remote laser beacon (either coherent or incoherent) and an optical receiver with CCD camera and embedded edge AI computer (Jetson Xavier Nx) for in situ evaluation of the path-averaged atmospheric turbulence refractive index structure parameter C-n(2) at a high temporal rate. Evaluation of C-n(2) values was performed using deep neural network (DNN)-based real-time processing of short-exposure laser-beacon light intensity scintillation patterns (images) captured by a TurbNet sensor optical receiver. Several pre-trained DNN models were loaded onto the AI computer and used for TurbNet sensor performance evaluation in a set …

Materials Design For Energy Applications Using Ab- Initio Calculations, Hind Hemaidee Alqurashi

Graduate Theses and Dissertations

The structural, dynamical, electronic, and thermoelectric properties of rock-salt and wurtzite Cd1-xZnxO alloys, VTiRhZ (Al, Ga, In, Si, Ge, Sn) and ZrTiRhZ (Ge, Sn) quaternary Heusler alloys (QHAs) were investigated using density functional theory (DFT) and semi-classical Boltzmann transport theory. From these calculations, the alloys were identified as potential materials for future thermoelectric applications. Furthermore, the magnetic and spin-polarization properties of these QHAs were investigated. The total magnetic moments were found to be integer values for all QHAs. In addition, all studied QHAs except VTiRhAl possess a half-metallic behavior with a 100% spin-polarization. The half-metallic ferromagnetic behavior makes them promising …

Arrayed Waveguide Lens For Beam Steering, Mostafa Honari-Latifpour, Ali Binaie, Mohammad Amin Eftekhar, Nicholas Madamopoulos, Mohammad-Ali Miri

Publications and Research

Integrated planar lenses are critical components for analog optical information processing that enable a wide range of applications including beam steering. Conventional planar lenses require gradient index control which makes their on-chip realization challenging. Here, we introduce a new approach for beam steering by designing an array of coupled waveguides with segmented tails that allow for simultaneously achieving planar lensing and off-chip radiation. The proposed arrayed waveguide lens is built on engineering the evanescent coupling between adjacent channels to realize a photonic lattice with an equi-distant ladder of propagation constants that emulates the continuous parabolic index profile. Through coupled-mode analysis …

Subwavelength Engineering Of Silicon Photonic Waveguides, Farhan Bin Tarik

All Dissertations

The dissertation demonstrates subwavelength engineering of silicon photonic waveguides in the form of two different structures or avenues: (i) a novel ultra-low mode area v-groove waveguide to enhance light-matter interaction; and (ii) a nanoscale sidewall crystalline grating performed as physical unclonable function to achieve hardware and information security. With the advancement of modern technology and modern supply chain throughout the globe, silicon photonics is set to lead the global semiconductor foundries, thanks to its abundance in nature and a mature and well-established industry. Since, the silicon waveguide is the heart of silicon photonics, it can be considered as the core …

Study Of Single-Photon Wave-Packets With Atomically Thin Nonlinear Mirrors, Christopher Klenke

Graduate Theses and Dissertations

A novel controlled phase gate for photonic quantum computing is proposed by exploiting the powerful nonlinear optical responses of atomically thin transition metal dichalcogenides (TMDs) and it is shown that such a gate could elicit a π-rad phase shift in the outgoing electric field only in the case of two incident photons and no other cases. Firstly, the motivation for such a gate is developed and then the implementation of monolayer TMDs is presented as a solution to previous realization challenges. The single-mode case of incident photons upon a TMD is derived and is then used to constrain the more …

Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras

Electrical and Computer Engineering Faculty Publications

In recent decades, climate change has significantly affected glacier dynamics, resulting in mass loss and an increased risk of glacier-related hazards including supraglacial and proglacial lake development, as well as catastrophic outburst flooding. Rapidly changing conditions dictate the need for continuous and detailed ob-servations and analysis of climate-glacier dynamics. Thematic and quantitative information regarding glacier geometry is fundamental for understanding climate forcing and the sensitivity of glaciers to climate change, however, accurately mapping debris-cover glaciers (DCGs) is notoriously difficult based upon the use of spectral information and conventional machine-learning techniques. The objective of this research is to improve upon an …

Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Human Activity Recognition (HAR) that includes gait analysis may be useful for various rehabilitation and telemonitoring applications. Current gait analysis methods, such as wearables or cameras, have privacy and operational constraints, especially when used with older adults. Millimeter-Wave (MMW) radar is a promising solution for gait applications because of its low-cost, better privacy, and resilience to ambient light and climate conditions. This paper presents a novel human gait analysis method that combines the micro-Doppler spectrogram and skeletal pose estimation using MMW radar for HAR. In our approach, we used the Texas Instruments IWR6843ISK-ODS MMW radar to obtain the micro-Doppler spectrogram …

Maximum Trapping Focal Length In Photophoretic Trap For 3d Imaging Systems, Jason M. Childers

Electrical Engineering

This product is a photophoretic trapping system which allows varying focal lengths to test which focal lengths are possible for trapping toner particles. This system establishes that there exists a maximum trapping distance limitation and is the first time the effect of focal length is studied in a photophoretic trapping system. Increasing photophoretic trapping focal length is necessary for improving this technology as a 3D display. The 3D imaging technology is realized by dragging a microscopic (micrometer-scale) particles with a laser beam to trace an image. This technology can display fully colored and high-resolution 3D images visible from almost any …

Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay

Electrical and Computer Engineering Faculty Publications

Deep learning approaches play a crucial role in computer-aided diagnosis systems to support clinical decision-making. However, developing such automated solutions is challenging due to the limited availability of annotated medical data. In this study, we proposed a novel and computationally efficient deep learning approach to leverage small data for learning generalizable and domain invariant representations in different medical imaging applications such as malaria, diabetic retinopathy, and tuberculosis. We refer to our approach as Incremental Modular Network Synthesis (IMNS), and the resulting CNNs as Incremental Modular Networks (IMNets). Our IMNS approach is to use small network modules that we call SubNets …

Porous Silicon Photonics For Label-Free Interferometric Biosensing And Flat Optics, Tahmid Hassan Talukdar

All Dissertations

This dissertation uses porous silicon as a material platform to explore novel optical effects in three domains: (i) It studies dispersion engineering in integrated waveguides to achieve high performance group index sensing. With proper design parameters, the sensor waveguides can theoretically achieve 6 times larger group index shift compared to the actual bulk effective refractive index shift. We demonstrate the guided mode confinement factor to be a key parameter in design and implementation of these waveguides. (ii) It explores multicolor laser illumination to experimentally demonstrate perceptually enhanced colorimetric sensing, overcoming the limitations faced by many contemporary colorimetric sensors. Our technique …

Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha

Electrical and Computer Engineering Faculty Publications

Background Nuclei classification, segmentation, and detection from pathological images are challenging tasks due to cellular heterogeneity in the Whole Slide Images (WSI). Methods In this work, we propose advanced DCNN models for nuclei classification, segmentation, and detection tasks. The Densely Connected Neural Network (DCNN) and Densely Connected Recurrent Convolutional Network (DCRN) models are applied for the nuclei classification tasks. The Recurrent Residual U-Net (R2U-Net) and the R2UNet-based regression model named the University of Dayton Net (UD-Net) are applied for nuclei segmentation and detection tasks respectively. The experiments are conducted on publicly available datasets, including Routine Colon Cancer (RCC) classification and …