Digital Commons Network^™

Mechanisms Of Dendritic Shorting In Lithium Metal Batteries With Li7la3zr2o12 Solid Electrolytes, Lukas Karapin-Springorum

Pomona Senior Theses

Energy storage will play a crucial role in efforts to mitigate the effects of climate change caused by greenhouse gas emissions from human activity. Lithium metal batteries using solid electrolytes like Li₇La₃Zr₂O₁₂ have higher energy density than lithium-ion batteries, which may enable a more rapid and complete electrification of transportation. However, lithium metal batteries suffer from undesirable short-circuiting when metallic lithium deposits connect the two electrodes. It has been debated whether these lithium dendrites generally grow directionally from the anode or are generated by the reduction of lithium ions inside the solid electrolyte, …

Numerical Investigation And Statistical Analysis Of The Flow Patterns Behind Square Cylinders Arranged In A Staggered Configuration Utilizing The Lattice Boltzmann Method, M. Abid, N. Yasin, M. Saqlain, S. Ul-Islam, S. Ahmad

Mathematics & Statistics Faculty Publications

Flow past bluff bodies like square cylinders is important in engineering applications, but flow patterns behind staggered cylinder arrangements remain poorly understood. Existing studies have focused on tandem or side-by-side configurations, while offset orientations have received less attention. The aim of this paper is to numerically investigate flow dynamics and force characteristics behind two offset square cylinders using the single relaxation time lattice Boltzmann method. The effects of changing both the Reynolds number (Re = 1-150) and gap spacing ratio (g* = 0.5-5) between the cylinders are analyzed. Instantaneous vorticity contours, time histories of drag and lift coefficients, power spectra …

Numerical Solution Of Hybrid Nanofluid And Its Stability Over Permeable Wedge Sheet With Heat Transfer Analysis, Aisha M. Alqahtani, Zeeshan, Waris Khan, Florentin Smarandache, Nidhal Becheikh, Roobaea Alroobaea, Taseer Muhammad

Branch Mathematics and Statistics Faculty and Staff Publications

The inclusion of nanoparticles has the potential to improve the thermal efficiency of the base fluid. The field of nanofluid (NF) dynamics has attracted important attention due to its extensive range of practical uses like fuel cells, solar energy, medication administration, heat transfer, microfabrication, coolant applications, and other related domains. The aim of this study is to scrutinize the impact of Lorentz force, thermal energy, joule heating, heat source and injection parameters, and Brownian and thermoporetic diffusions on the hybrid nanofluid over the moving wedge. The stability inquiry is reported for the existing work in order to confirm the stable …

A Data-Driven Machine Learning Approach For Electron-Molecule Ionization Cross Sections, Allison Harris, Josh Nepomuceno

Faculty publications – Physics

Despite their importance in a wide variety of applications, the estimation of ionization cross sections for large molecules continues to present challenges for both experiment and theory. Machine learning (ML) algorithms have been shown to be an effective mechanism for estimating cross section data for atomic targets and a select number of molecular targets. We present an efficient ML model for predicting ionization cross sections for a broad array of molecular targets. Our model is a 3-layer neural network that is trained using published experimental datasets. There is minimal input to the network, making it widely applicable. We show that …

Tau Leptons In The Search For Charged Higgs Bosons, Juan Carlos Cardenas Jr

Physics Dissertations - Archive

The Standard Model (SM) of particle physics, a gracefully crafted collection of particle theories, has made an astounding number of accurate predictions about the properties of particles and the fundamental laws that govern our universe. Among its long list of remarkable successes are the unification of the electromagnetic and weak forces, the prediction of elementary particles such as the Higgs boson, and its ability to precisely predict a wide range of particle cross-sections and branching fractions which have been verified experimentally.

Yet despite its immense predictive power, some major problems with the standard model are its failure to accommodate dark …

Novel Time Projection Chamber Techniques With Applications Towards Neutrinoless Double Beta Decay Searches, Nicholas K. Byrnes

Physics Dissertations - Archive

One of the highest priority endeavors in nuclear and particle physics is the search for Neutrinoless Double Beta Decay (0νββ). The observation of 0νββ would prove that the neutrino is a Majorana particle i.e. its own antiparticle, offering a mechanism by which the matter-antimatter asymmetry observed in our universe could be explained. This theoretical decay mechanism is only energetically favored in certain neutron-rich isotopes and, if found, would be the rarest decay process ever observed. To compete with the exceedingly long half-life of 0νββ, all contemporary searches are focused on the following detector performance metrics: Increasing the instrumented isotopic mass …

Student Performance In Modern Physics In An Active, Partially-Flipped Classroom, Scott Yarbrough

Physics Dissertations - Archive

The effectiveness of the flipped classroom and hybrid-flipped (partially flipped, partially lecture-based) method of instruction has been extensively studied for high school and introductory undergraduate physics courses, and it has been shown to increase student understanding and performance. However, few studies have been done for upper-level undergraduate courses, and even fewer have been done for virtual courses. In Spring 2021 and Fall 2023, a fully virtual, hybrid-flipped Modern Physics course was taught, primarily to a class of primarily juniors and seniors, with some sophomores. All were STEM majors. The same course, with a similar enrolment and demographic of students, was …

Physics-Informed Neural Networks (Pinns) And Inverse Pinns For The Modeling And Parameter Estimation Of Electric Pumps In Liquid-Propellant Rocket Engines, Logan Mcfarland

Theses and Dissertations

This thesis presents a machine learning (ML) based approach to both model and estimate the parameters of an electric pump system that is used in liquid-propellent rocket engines. This is accomplished by utilizing Physics-Informed Neural Networks (PINNs) and inverse Physics-Informed Neural Networks (iPINNs). In an extreme system such as a liquidpropellent rocket engine, accurate control and efciency is imperative for successful performance. The electric pump system is inherently nonlinear and its dynamics are governed by ordinary diferential equations (ODEs). While entirely approachable, these nonlinear dynamics create a challenge in achieving precise control and accurate parameter estimations. Utilization of a PINN …

Analysis Of Macular Pigment Carotenoids In Human Blood Serum Of Glaucoma Patients As A Measure Of Ocular Health: A Raman Spectroscopic Study., Joy Udensi, Ekaterina Loskutova, James Loughman, Hugh J. Byrne

Datasets

Carotenoids are a major component of the human diet and have been widely studied for their antioxidant, and vision protection roles in the human body, and dietary supplementation is promoted in particular for ocular health. An initial trial (European Nutrition in Glaucoma Management (ENIGMA)), which assessed macular pigment optical density (MPOD) as well as ocular structural, functional and perceptual parameters before and after the 18-month supplementation of glaucoma patients with macular pigment (MP) carotenoids (lutein, zeaxanthin, meso-zeaxanthin), confirmed supplementation significantly improved the clinical ocular health of participants. Blood contains all major dietary carotenoids, presenting it as a suitable and efficient …

Applications Of Independent And Identically Distributed (Iid) Random Processes In Polarimetry And Climatology, Dan Kestner

Dissertations, Master's Theses and Master's Reports

The unifying theme of this thesis is the characterization of “perfect randomness,” i.e., independent and identically distributed (IID) stochastic processes as these are applied in physical science. Two specific and mathematically distinct applications are chosen: (i) Radar and optical polarimetry; (ii) Analysis of time series in meteorology. In (i), IID process of a special kind, namely, with a distribution defined by symmetry, is used to link its multivariate Gaussian density to uniformity on the Poincaré sphere. This “statistical ellipsometry” approach is then used to relate polarimetric mismatches or imbalances to ellipsometric variables and suitably chosen cross-correlation measures. In (ii), recently …

Dependence Of Energy Transfer On Curvature Similarity In Collisions Involving Curved Shock Fronts, Justin Cassell

Dissertations, Master's Theses and Master's Reports

In high-speed collisions of projectiles, pressure exerted by a resulting shock wave is so high that even solids begin to flow and hydrodynamics becomes relevant. Jetting results from hydrodynamic instability driving the evolution of an interface following shock loading. Our emphasis in this dissertation is mitigation of instabilities via several shocks and, specifically, the transfer of energy from a shock wave to another object. To that end, in 2022 and 2023 while on-site, we adapted Lawrence Livermore National Laboratory (LLNL) to explore the effects of shock front geometry on the transfer of energy during shock collisions via numerous computer simulations. …

Les-C Turbulence Models And Fluid Flow Modeling: Analysis And Application To Incompressible Turbulence And Fluid-Fluid Interaction, Kyle J. Schwiebert

Dissertations, Master's Theses and Master's Reports

In the first chapter of this dissertation, we give some background on the Navier-Stokes equations and turbulence modeling. The next two chapters in this dissertation focus on two important numerical difficulties arising in fluid flow modeling: poor mass-conservation and nonphysical oscillations. We investigate two different formulations of the Crank-Nicolson method for the Navier-Stokes equations. The most attractive implementation, second order accurate for both velocity and pressure, is shown to introduce non-physical oscillations. We then propose two options which are shown to avoid the poor behavior. Next, we show that grad-div stabilization, previously assumed to have no effect on the target …

Study Of Particle Accelerators In The Universe With The Hawc Observatory, Rishi Babu

Dissertations, Master's Theses and Master's Reports

HESS J1809-193 is an unidentified TeV source discovered in 2007 by the High Energy Stereoscopic System(H.E.S.S.) Collaboration. The emission originates in a region that is rich in cosmic-ray accelerators, including several supernova remnants and pulsars, including SNR G11.1+0.1, SNR G11.0-0.0, and the young radio pulsar PSR J1809-1917. Originally classified as a pulsar wind nebula candidate, recent studies show the peak of the TeV region overlapping with a system of molecular clouds and revising the original classification for other scenarios, including a pure hadronic scenario. This dissertation presents the morphological and spectral study of HESS J1809-193 using 2139 days of data …

Halide-Assisted Growth Of Transition Metal Dichalcogenides, Vinaayak Sivam Balasubramaniam

Dissertations, Master's Theses and Master's Reports

Monolayers of transition metal dichalcogenides (TMDCs) have attracted significant attention as the rare two-dimensional (2D) semiconducting materials with a direct energy band gap. Chemical vapour deposition (CVD) is one of the scalable techniques to grow atomically thin TMDC monolayers in high quality, but it requires high growth temperature. Herein we report the growth of MoS2, WS2 and MoSe2 by a one-step halide-assisted CVD method using NaCl and KCl as the catalysts. These halides could reduce the growth temperature of TMDCS by reacting with the precursors (TMDC powders) to form volatile intermediate compounds as the growth species. We use optical microscopy, …

2d Direct Numerical Simulation Of Low-Prandtl Number Rayleigh-Bénard Convection, Reed Downs

Dissertations, Master's Theses and Master's Reports

A two-dimensional (2D) direct numerical simulation (DNS) of Rayleigh-Benard convection (RBC) was performed at Rayleigh number (Ra) = 10^6 and Prandtl number (Pr) = 0.021. The simulation was run using the Boussinesq approximation on a square grid of 5184 spectral elements using Nek5000. The simulation was started from a conductive state, with non-permeable, isothermal horizontal walls and non-permeable, adiabatic vertical walls. After reaching a steady state, where the Nusselt number (Nu) converged to 6.2, the simulation was run for 60 freefall-averaged dimensionless time units. Time-averaged thermal boundary layers on the top and bottom plates were found to consist of ejection, …

Bayesian Inference In Reinforcement Learning Neural Networks During A Markov Decision Processes?, Katherine Graham

Scripps Senior Theses

The predictive mind theory proposes that brains work in a way that makes predictions about future stimuli to process information efficiently and accurately. Bayesian brain theory suggests that the brain utilizes Bayesian probability models to make predictions, while the free-energy minimization hypothesis proposes that these predictions are made to minimize energy or uncertainty, ensuring accurate perceptions. Vertechi et al. (2020) explored animal participants’ utilization of stimulus-bound strategy versus inference-based strategy to solve a Markov decision process with a 2-state environment, one of which is always active. These sites have a certain probability of switching to a different site and the …

Plant Root Hair Adhesion Mediated Through Variation In Sodium Ion Concentration, Natasha Mulenga

Honors Program Theses

This study investigates the effects of sodium ion (Na+) concentration on the adhesion of Brassica Rapa root hairs using atomic force microscopy (AFM). Plant root hair adhesion to soil particles plays a crucial role in anchoring plants and facilitating nutrient uptake. Previous research has shown that calcium ions (Ca2+) cross-link pectin molecules in the cell wall, increasing rigidity and reducing adhesion. As Na+ binds to pectin without cross-linking, we expected that root hairs exposed to sodium chloride (NaCl) solutions would exhibit longer adhesive interactions and similar binding forces compared to those exposed to calcium chloride (CaCl2) solutions of equal concentrations. …

Transient Diode Laser Absorption Spectroscopy For Measuring Collisional Quenching Rates Of Co And Its Potential For Studying H2o, Jordan M. Polvere

Master’s Theses

Motivated by the necessity of non-LTE models that account for species that are not in Local Thermodynamic Equilibrium (LTE) in Titan’s and Earth’s atmospheres, collisional quenching rates of CO and H2O_(g) have been studied. Providing more accurate and precise values of collisional quenching rate coefficients is crucial in the development of more advanced atmospheric models, which are important to fields of science such as meteorology and astronomy. Rates of collisional quenching of CO(v=1,2) by CO and CO(v=2) by N₂ at approximately 301-321 K were measured by transient diode laser absorption spectroscopy. The rate coefficients of CO(v=1)-CO, CO(v=2)-CO, and …

“Zero” Porosity High Loading Nmc622 Positive Electrodes For Li-Ion Batteries, Haidar Y. Alolaywi, Kubra Uzun, Yang-Tse Cheng

Chemical and Materials Engineering Faculty Publications

LiNi0.6 Mn0.2Co0.2 O 2 (NMC622) is a widely used positive electrode material for lithium-ion batteries, including electric vehicles. In this work, we investigated the effects of porosity, ranging from “zero” to the typical 35%, on the electrochemical behavior of high- loading NMC622 electrodes. Although it is well known that the energy density of the electrode increases with increasing areal capacity and decreasing porosity, NMC-positive electrodes with exceedingly low porosity (e.g., near zero) and high loading (e.g., 4 mAh cm−2 ) have not been investigated. Here, we report an intriguing observation that the “zero porosity” NMC electrode can have higher capacity …

Global Analysis Of The Neutron Magnetic Form Factor, Joseph P. Jayne

Honors Theses and Capstones

Protons and neutrons, the nucleons, are made up of smaller particles called quarks. Nucleons have three valence quarks, which are the dominant contributors to its properties, as well as sea quarks (quark-antiquark pairs) and gluons. The distribution of the charge and magnetization of these particles is described by the electric and magnetic form factors. These form factors can be measured with scattering experiments since they directly affect the particle’s cross section. Neutron form factors are challenging to measure because a pure neutron target will decay very fast and is not viable for experiments. Instead, targets like 2H and 3H are …

Accelerating Cavity Fault Prediction Using Deep Learning At Jefferson Laboratory, Md M. Rahman, A. Carpenter, K. Iftekharuddin, C. Tennant

Electrical & Computer Engineering Faculty Publications

Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive …

Passive Magnetic-Free Broadband Optical Isolator Based On Unidirectional Self-Induced Transparency, Haodong Wu, Jianshan Tang, Miangyuan Chen, Min Xiao, Yanqing Lu, Keyu Xia, Franco Nori

Physics Faculty Publications and Presentations

Achieving a broadband nonreciprocal device without gain and any external bias is very challenging and highly desirable for modern photonic technologies and quantum networks. Here we theoretically propose a passive and magnetic-free all-optical isolator for a femtosecond laser pulse by exploiting a new mechanism of unidirectional self-induced transparency, obtained with a nonlinear medium followed by a normal absorbing medium at one side. The transmission contrast between the forward and backward directions can reach 14.3 dB for a 2π − 5 fs laser pulse. The 20 dB bandwidth is about 56 nm, already comparable with a magneto-optical isolator. This work provides …

Tip-Induced Nanoscale Domain Engineering In X-Cut Lithium Niobate On Insulator, Jianan Ma, Ningchong Zheng, Pengcheng Chen, Xiaoyi Xu, Yunzhi Zhu, Yuefeng Nie, Shining Zhu, Min Xiao, Yong Zhang

Physics Faculty Publications and Presentations

Nanodomain engineering in lithium niobate on insulator (LNOI) is critical to realize advanced photonic circuits. Here, we investigate the tip-induced nanodomain formation in x-cut LNOI. The effective electric field exhibits a mirror symmetry, which can be divided into preceding and sequential halves according to the tip movement. Under our configuration, the preceding electric field plays a decisive role rather than the sequential one as in previous reports. The mechanism is attributed to the screening field formed by the preceding field counteracting the effect of the subsequent one. In experiment, we successfully fabricate nanodomain dots, lines, and periodic arrays. Our …

Effective Size Of A Parity-Time-Symmetric Dimer, Li Ge

Publications and Research

Parity-time (PT)-symmetric dimers were introduced to highlight the unusual properties of non-Hermitian systems that are invariant after a combined parity and time reversal operation. They are also the building blocks of a variety of symmetry and topologically protected structures, especially on integrated photonic platforms. As the name suggests, it consists of two coupled oscillators, which can be optical, mechanical, electronic, and so on in nature. In this article, we show that its effective size, defined by the number of lattice sites inversely proportional to the lattice momentum, is surprisingly three instead of two from the perspective of energy quantization. More …

Computationally Modeling The Human-Structure Interaction Response Of An Occupied Cantilevered Structure, Brennan Smith

Honors Theses

There is a limited understanding of the impact that passive human occupants have on a dynamic structural system, referred to as Human-Structure Interaction (HSI). Cantilevers are naturally prone to excessive vibrations due to their long unsupported spans, and cantilevered structures such as those commonly found in the seating area of a stadium facility or concert hall are designed to support a high density of occupancy.

This study determined that HSI in cantilevered structures can be modeled using a simple two-degree-of-freedom system. The results of the model were validated by data that was collected on a small-scale laboratory structure intentionally designed …

Performance Optimization For A Scintillating Glass Electromagnetic Calorimeter At The Eic, J. Crafts, Renee H. Fatemi, T. Horn, D. Kalinkin

Physics and Astronomy Faculty Publications

The successful realization of the EIC scientific program requires the design and construction of high-performance particle detectors. Recent developments in the field of scientific computing and increased availability of high performance computing resources have made it possible to perform optimization of multi-parameter designs, even when the latter require longer computational times (for example simulations of particle interactions with matter). Procedures involving machine-assisted techniques used to inform the design decision have seen a considerable growth in popularity among the EIC detector community. Having already been realized for tracking and RICH PID detectors, it has a potential application in calorimetry designs. A …

General Physics Ii - Lab Manual, David Goldberg, Peter Glass

Open Educational Resources

No abstract provided.

Ltspice Modeling For Gan-Git Hemt Including Cryogenic Temperature, Md Maksudul Hossain, Yuqi Wei, H. Alan Mantooth

Electrical Engineering Faculty Publications and Presentations

Highly efficient electrically driven avionics have led to a renewed interest in cryogenic propulsion systems with the goal of reducing carbon emission footprint. Although cryogenic converters promise better efficiency and improved power density, the successful design is incumbent upon the appropriate switching device selection and simulation-based analyses prior to initial prototyping. In this work, a datasheet-driven compact model for a gallium nitride (GaN) Gate Injection Transistor (GIT) has been proposed and implemented in LTspice, a versatile, high performance, and free circuit simulator in order to investigate the merit of the chosen device in a power electronic system.

Investigating Microphysical Variability And Entrainment In Clouds Using Airborne Digital Holography, Machine Learning, And Large Eddy Simulations, Nithin Allwayin

Dissertations, Master's Theses and Master's Reports

Advancing our understanding of cloud microphysics—the processes governing cloud particles' formation, growth, and interactions—is essential for accurate weather and climate modeling. In this work, we investigate how droplet size distributions vary in a cloud and explore how microphysical properties such as droplet size and number concentration respond to entrainment and mixing.

In the first part of the work, a novel algorithm is developed combining hypothesis testing with density-based clustering to identify characteristic cloud droplet size distribution types in marine stratocumulus clouds. Applied to data from the airborne Holographic Detector for Clouds (HOLODEC), the algorithm successfully identifies a relatively small set …

Interpreting Neural Operators: How Nonlinear Waves Propagate In Non-Reciprocal Solids, Jonathan Colen, Alexis Poncet, Denis Bartolo, Vincenzo Vitelli

Data Science Faculty Publications

We present a data-driven pipeline for model building that combines interpretable machine learning, hydrodynamic theories, and microscopic models. The goal is to uncover the underlying processes governing nonlinear dynamics experiments. We exemplify our method with data from microfluidic experiments where crystals of streaming droplets support the propagation of nonlinear waves absent in passive crystals. By combining physics-inspired neural networks, known as neural operators, with symbolic regression tools, we generate the solution, as well as the mathematical form, of a nonlinear dynamical system that accurately models the experimental data. Finally, we interpret this continuum model from fundamental physics principles. Informed by …