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Machine Learning-Based Regression For Magnetic Field Prediction From Odmr Spectral Data, Jesse B. Hernandez

Electronic Theses, Projects, and Dissertations

Optically Detected Magnetic Resonance (ODMR) using nitrogen-vacancy (NV) centers in diamond enables sensitive, room-temperature magnetic field sensing, but real ODMR spectra are often noisy and difficult to analyze with traditional peak-fitting methods. This thesis investigates whether machine learning can reliably predict magnetic field strength directly from ODMR spectra, and compares four model families under a single regression task: a random forest, an artificial neural network (ANN), a one-dimensional convolutional neural network (1D-CNN), and a Transformer.

Training data were generated from an NV-ensemble simulation calibrated to real measurements provided by the Ulsan National Institute of Science and Technology (UNIST), spanning 0 …

Pentagonal Pdte2 Monolayer For Sustainable Solar-Driven Hydrogen Production, Narender Kumar, Shambhu Bhandari, Dario Alfè, Ravindra Pandey, Nacir Tit

Michigan Tech Publications

This investigation demonstrates that the pentagonal PdTe2 (penta-PdTe2) monolayer is a highly tunable two-dimensional (2D) photocatalyst, characterized by the bandgap of 1.87 eV and high hole mobility. Using density functional theory calculations with the HSE06 functional, we show that tensile strain engineering (particularly at +2% and +3%) is essential for enabling spontaneous water splitting. At these strain values, the valence-band maximum and conduction-band maximum straddle the water redox potentials (H+/H2 and O2/H2O) under both acidic (pH = 0) and neutral (pH = 7) conditions. The monolayer's low hole effective mass facilitates rapid charge extraction, mitigating recombination and driving the oxygen …

Nonlinear Mode Crossing And Spontaneous Frequency Comb Generation In Driven Magnetic Nanodisks, Hasan Pi̇şki̇n

Turkish Journal of Physics

Nonlinear magnetization dynamics in confined nanostructures provide a rich platform for fundamental studies and advanced spintronic applications. Here, we investigate the driven dynamics of a perpendicularly magnetized permalloy nanodisk using high-resolution micromagnetic simulations. In the linear regime, geometric confinement quantizes the uniform precession into discrete radial standing spin-wave (SSW) modes. As the excitation amplitude increases, the fundamental Kittel mode exhibits a pronounced nonlinear frequency shift relative to the higher-order SSW modes, ultimately leading to a critical mode crossing associated with nonlinear resonance overlap and the breakdown of modal orthogonality. Time-domain analysis reveals that strong mode hybridization governs the ensuing dynamics, …

Stress–Strain Behavior Of The High-Entropy Cantor Alloy Crmnfeconi Using A Deep Neural Network Potential, Nguyen Le Hoai Phuong, Le Huu Nghia, Huynh Khanh Van, Vo Khuong Dien, Nguyen Thanh Tien

Turkish Journal of Physics

Machine learning interatomic potentials (MLIPs) provide an efficient approach to large-scale molecular dynamics simulations of high-entropy alloys. In this work, an MLIP trained on AIMD data was developed for the CrMnFeCoNi Cantor alloy and validated against DFT calculations. In addition, we compared MLIP results with those obtained using the classical modified embedded atom method (MEAM)-based interatomic potential for the CrMnFeCoNi Cantor alloy. The model achieved energy and force RMSEs of 7.39 x 10-6 meV/atom and 4.46 x 10-3 eV/A, respectively. Tensile simulations demonstrated that the MLIP accurately reproduced the stress–strain response, elastic constants, and deformation mechanisms observed in DFT calculations. …

Spacer-Mediated Gold Nanocube Arrays For Edge-Localized Excitonic Enhancement In Monolayer Mos2​, Abdullah Efe Yildiz, Emre Ozan Polat

Turkish Journal of Physics

Plasmonic nanostructures offer an effective route for enhancing light-matter interaction in atomically thin semiconductors, whose optical response is intrinsically limited by their subnanometer active thickness. Here, we numerically investigate excitonic enhancement in monolayer (ML) Molybdenum Disulfide (MoS2) coupled to size-tuned gold (Au) nanocube arrays separated by thin aluminum oxide (Al2O3) and hexagonal boron nitride (h-BN) spacer layers. By varying the nanocube side length, the localized surface plasmon resonance is tuned across the visible spectral range to modulate the A- and B-excitonic transitions of monolayer MoS2.We show that the nanocube-size-dependent spectral redshift can be further controlled through the spacer material and …

Theoretical Construction Of Light Hexaquarks And Their Substantiation By Seven-Dimensional Representation Of Su(2) Group, Mayank Joshi, Shuchi Bisht, Navjot Hothi, Manish Bisht

Turkish Journal of Physics

This manuscript presents a theoretical approach to constructing light hexaquarks using up and down quarks. These light exotic hexaquarks are shown to exhibit a seven-dimensional representation of the SU(2) isospin group. Additionally, the isospin septuplet is developed along with the quintet, triplet, and singlet representations for these light exotic hexaquarks. These particles are essentially mesonic in nature and also satisfy the requirements of the Kronecker product. Furthermore, the physical characteristics and weights of the respective states are intrinsically provided for these light hexaquarks.

Investigation Of The Production Technology Of Environmentally Safe Urethane Oligomers Based On Local Raw Materials, Bakhtiyor Kudratovich Shaykulov, Dilafruza Ruziboevna Akbarova Gulboeva, Fayzulla Nurmuminovich Nurqulov

Technical science and innovation

This paper investigates the step-by-step poly condensation pathway for synthesizing environmentally friendly, non-isocyanate urethane oligomers derived from local and safe raw materials: urea and ethylene glycol. The influence of thermodynamic parameters on the target product yield was systematically evaluated to determine the optimum technological matrix. Specifically, a 1:2 reactant mass ratio, a stable stationary temperature of 150-155 °C, and a reaction duration of 2 hours under an inert nitrogen atmosphere resulted in a sustainable and reproducible yield of 72%. Thermal degradation and competitive side-product condensations were activated above 160 °C, leading to a sharp drop in overall chemical efficiency. The …

Thermo-Entropic Analysis Of Unsteady Mhd Nanofluid Couette Flow: A Classical Spectral Approach With An Exploratory Quantum Linear-Solver Application, Serai Israel Mosala, Oluwole Daniel Makinde, Azwinndini Muronga

Mathematical Modelling and Numerical Simulation with Applications

This study presents a thermo-entropic analysis of unsteady MHD nanofluid Couette flow, combining a classical bivariate spectral quasilinearisation (BI-SQLM) and Crank--Nicolson solution with an exploratory application of quantum linear solvers. An incompressible, electrically conducting nanofluid flows between parallel plates under partial slip and convective heat exchange; the discretised linear systems are additionally solved via the Harrow--Hassidim--Lloyd (HHL) algorithm and the Variational Quantum Linear Solver (VQLS). Results are presented for Pure Water, Cu-Water, and Al₂O₃-Water across seven parameter variations. The Hartmann number dominates velocity suppression and entropy amplification, while velocity slip reduces upper-wall entropy generation more than …

Effects Of Co-Rotating Cylinders And Boundary Conditions On Heat And Mass Transfer In A Trapezoidal Enclosure, Olalekan Adebayo Olayemi, Olalekan Tajudeen Popoola, Leke Thaddeus Oladimeji, Isaac Kayode Adegun, Taofiq Omoniyi Amoloye, Oluwatayo Babatope Ojo, Benjamin Ohida Daniel, Michael Olabode Ibiwoye

Mathematical Modelling and Numerical Simulation with Applications

This study investigates the effects of rotational speed $(\Omega)$, Richardson number $\left(Ri\right)$, and Lewis number $\left(Le\right)$ on heat and mass transfer (HMT) around two co-rotating cylinders symmetrically situated in a trapezoidal enclosure. In the double-diffusive mechanism, the bottom wall of the trapezium is at a high temperature $\left(T_h\right)$ and concentration $\left(C_h\right)$, while the top wall is at a low temperature $\left(T_c\right)$ and concentration $\left(C_c\right)$. The side walls are perfectly insulated with zero mass flux, while the buoyancy ratio $\left(Br\right)$ is fixed at 1.0.  Two thermal-mass boundary scenarios are considered. Scenario 1: Cylinders are thermally insulated with zero mass flux, and …

Characterization Of Combined Adsorption Using Fermi Levels, Molecular Dynamics, And Monte Carlo Simulations To Prevent Cu–Zn (111) Alloy Corrosion, Mushtaq Jerri Meften, Ammar Abdul Jabbar Kadhim, Mohammed Shafeeq Abed

Makara Journal of Science

Experimentally developing corrosion inhibitors requires a significant amount of money and time. In silico advancement empowers selecting inhibitor molecules based on their properties derived from theoretical studies, thereby reducing costs. Our main approaches include theoretical studies such as Fermi levels, electrostatic potential surface (EPS), Fukui indices, molecular dynamics stimulations, and Monte Carlo as indispensable tools to investigate the adsorption mechanisms of molecules 6-((5-(((3S,5R)-2-oxo-5-((2-(pyrazin-2-yloxy) thiazol-5-yl) thio) tetrahydro-2H-thiopyran-3-yl) oxy)isothia-zol-3-yl)thio) nicotinic acid (PTT), and (S)-2-((5-((6-((3-(2-thioxoethoxy)-1,2,4-thiadiazol-5-yl)thio)-1,6-dihydropyra-zin-2-yl)oxy)-1,3,4-thiadiazol-2-yl) thio) acetaldehyde (TTD) on the Cu/Zn (111) alloy. We electronically characterized PTT and TTD, which were proven effective inhibitors. Notably, all results suggested that the two exhibited high …

Increasing The Density Value Of Composite Propellant Ap/Htpb/Al For Rocket Performance Using The Sphere Packing Model, Muhammad Iqbal Alfikri, Bayu Prianto, Ariadne Lakshmidevi Juwono

Makara Journal of Science

This research employs the sphere packing volume (SPV) model to optimize the density of composite propellants thereby enhancing rocket performance. We systematically varied the diameters of spherical ammonium perchlorate (AP) particles (50 and 400 µm) and aluminum powder (Al) particles (10 and 30 µm). These particles were incorporated at an ideal AP:Al ratio of 4:1 into a matrix of hydroxyl-terminated polybutadiene and toluene diisocyanate. By adjusting the AP ratio for each Al particle size and considering theoretical and tap densities, we precisely calculated the SPV value for each composition. The composition with the highest SPV value yielded remarkable results. This …

Complementary Thermodynamic Mechanisms Of Boron And Carbon Segregation At Grain Boundaries In Nickel Alloys, Tyler D. Dolezal, Rodrigo Freitas, Ju Li

Faculty Publications

Grain boundary stabilization by light interstitials is central to the performance of Ni-based superalloys, yet the thermodynamic mechanisms governing their interactions with substitutional chemistry remain poorly resolved. Here, we use hybrid Monte Carlo molecular dynamics simulations to quantify how boron and carbon modify the thermodynamic, structural, and chemical ordering of grain boundaries in Ni-Cr alloys. By analyzing interfacial state variables, site-resolved segregation spectra, local chemical ordering, and structural evolution, we show that boron and carbon stabilize grain boundaries through complementary pathways. Carbon drives saturation-controlled stabilization by recruiting Cr and conditioning boundary chemistry, while suppressing temperature-driven structural transformations of the boundary. …

A Systematic Approach For Controlling Tem Sample Thicknesses, Monte Kozell

Physics Faculty Publications and Presentations

Historically, TEM prep has been an artisan craft without a systematic workflow that ensures quantified control over TEM sample thickness. Over- and under-thinning is a significant problem in the TEM prep process. A direct measurement process was demonstrated to control the final thickness of the TEM lamella. Final lamella thickness was controlled by directly measuring lamella thickness in real time using a 10–15 kV SEM while performing secondary electron imaging at the mill position, allowing for (human-mediated) closed-loop processing. We demonstrated the utility of this technique by systematically thinning five TEM samples to discretely target thicknesses ranging from 100 nm …

How Far Do A Smile And A Hand Held Tight Reach? Children’S Play As A Transdisciplinary Predictor Of The Trajectory Of Physicochemical Processes On Atomic, Molecular And Cellular Scales, Evangelina Wu Uskoković, Theo Wu Uskoković, Vuk Uskoković

Administration and Staff Articles and Research

The search for an intrinsically beautiful scientific project took two children and their parent to over 600 visits of 181 playgrounds scattered throughout northern, central and southern California over the period of more than three years. Their goal was to test the hypothesis that children’s happiness and fondness for communication at playgrounds could be used, through complexity and entropy as intermediary quantities, as predictors of the evolution of physical, chemical and biological phenomena on microscopic scales ranging from the atomic to the cellular. Specifically, a link was sought between the children’s responses at play and the reaction paths of physicochemical …

A Calibrated And Conformal Deep Learning Framework For Trustworthy Antinuclear Antibody Pattern Recognition With Selective Referral To Experts, Hussein Ali Hussein Al Naffakh, Ahmed Dheyaa Radhi, Raghdah Maytham Hameed, Muntaha Abdullah Reishaan, Fouad A. Majeed, Rozaida Ghazali

Karbala International Journal of Modern Science

Reading antinuclear antibody patterns on human epithelial cells by indirect immunofluorescence is the reference screen for systemic autoimmune rheumatic diseases, but it is slow, subjective, and variable between observers. Deep learning reaches high accuracy on this task, yet most systems return a single prediction without stating how reliable it is, which is unsafe in a diagnostic workflow. This paper presents an intelligent decision support framework built around a single calibrated uncertainty signal. That signal is the control variable for four reliability modules: confidence calibration, conformal prediction, error detection, and selective referral. A feature space out of distribution detector serves as …

Analysis Of The Influence Of Anthropometric Dimensions Of Postural Ergonomics Using Multiple Linear Regression, Gashbeen Faisal Najmaddin, Edrees Muhammed Tahir Harki

Al-Bahir

Ergonomics is the study of designing and arranging a workspace or product to optimize the “fit” between people and their work, ensuring safety, comfort, and efficiency. The scientific literature indicates that ergonomic perspectives on the workplace are connected to the anthropometrics of societies. This study primarily aims to create a model that integrates multiple predictive variables to estimate the target variable. Multiple linear regression analysis is used to identify how different anthropometric dimensions predict postural ergonomics during prolonged sitting. Based on the regression models’ results, the predicted can be calculated using user anthropometry and existing chair dimensions. Furthermore, the primary …

Libs-Based Detection And Preliminary Classification Of Microplastic Signatures In Soil Samples., Ekhlas Jabir Mahmood

Al-Bahir

Contamination of terrestrial systems by microplastics (MPs) has become a critical environmental hazard, but detection of such contaminants in a complex soil system is a challenge for conventional analytical techniques. This research aims to assess the potential of Laser-Induced Breakdown Spectroscopy (LIBS) for the detection and differentiation of different types of microplastics, including HDPE, LDPE, PP, PS, and PVC, dispersed in the soil of Al Najaf, Iraq. Soil samples were collected from different functional zones, namely, Industrial, Commercial, Agricultural, Residential, and Roadside, at the surface level and 30 cm depth. Detection was done by measuring the intensity of the C/H …

Development Of A Chip-Scale Optical Gyroscope With Weak Measurement Amplification Readout, Kagan Yanik, Meiting Song, Yuhan Mei, Jaime Cardenas, Andrew N. Jordan

Mathematics, Physics, and Computer Science Faculty Articles and Research

We establish the theoretical framework and investigate the fundamental limits for an integrated optical chip design containing a rotation sensing ring resonator coupled to an inverse weak value amplified Sagnac interferometer that amplifies the signal with phase information. We achieve, for conservative parameter choices, a minimum detectable angular rotation rate of ∼0.1 °/hr and an Allan deviation of∼0.08 °/hr assuming shot noise limited performance. For matched detected optical power, our design can improve the signal-to-noise ratio, reduce the minimum detectable angular rotation rate, and Allan deviation by more than ten times compared to an ideal standard Sagnac interferometer with balanced …

Cavity Optomechanics Via Mechanically Induced Coupling Of Optical Modes, Satyam S. Jha

Dissertations, Theses, and Capstone Projects

This thesis introduces a transverse, symmetry-breaking mode of optomechanical coupling that departs from the conventional dispersive and dissipative interactions, taking its motivating platform from whispering-gallery-mode (WGM) resonators, where a mechanical displacement lifts the near-degeneracy of azimuthal mode pairs and couples them. After reviewing the standard optomechanical model and the sideband-cooling phenomenology it underlies, we derive the Hamiltonian for the transverse-coupling system and first study its Hamiltonian dynamics, without drive or dissipation. Recast in terms of Schwinger pseudospin operators, the model exhibits a Hamiltonian Hopf bifurcation separating stable and unstable dynamical regimes. In the stable regime, the mechanical nonlinearity permits controlled …

Potential Energy Landscape Formalism For Quantum Liquids, Yang Zhou

Dissertations, Theses, and Capstone Projects

Atomic delocalization due to nuclear quantum effects (NQE) remains poorly understood in low-temperature liquids near the glass state and during vitrification. Many liquids can be described accurately by treating their nuclei as classical particles, but this approximation fails for light elements such as He and H₂, small hydrogen-containing molecules such as water, and systems in which zero-point motion or isotope-substitution effects are important. Developing a general thermodynamic and statistical-mechanical description of such liquids has been challenging. This dissertation extends the potential energy landscape (PEL) formalism, originally developed for classical liquids and glasses, to liquids that obey quantum mechanics and exhibit …

Ultrafast Spectroscopy Of Organic Materials In Strong Light–Matter Interaction And Terahertz Optics, Kamyar Rashidi

Dissertations, Theses, and Capstone Projects

Ultrafast spectroscopy is a powerful tool for investigating phenomena that occur on extremely short timescales and for probing ultrabroadband spectral responses enabled by its ultrashort laser pulses. These capabilities are essential for advancing both the fundamental understanding of light–matter interactions and the development of next-generation optoelectronic technologies. The first part of this thesis investigates the ultrafast dynamics of organic exciton–polaritons and their application to controlling molecular excited-state processes using momentum-resolved pump–probe spectroscopy. A major challenge in these systems is the dark-state problem, where photoexcitation predominantly populates long-lived excitonic reservoir states that obscure the in trinsic dynamics of the hybrid light–matter …

Karhunen-Loève Modes For Coherent Arrays, Jack E. Mccrae, Santasri R. Bose-Pillai, Steven T. Fiorino

Faculty Publications

The optimal modes for correcting atmospheric turbulence on coherent arrays are determined. These Karhunen-Loève modes are eigenvectors of a covariance matrix. Creating this covariance matrix requires knowledge of the power spectrum of the turbulence, the aperture geometry, and a basis set for the matrix. The Kolmogorov power law is ordinarily chosen here for the turbulence spectrum. By choosing the phase on each array subaperture element minus the phase averaged over all subapertures as this basis, infinite values in the variances and covariances can be avoided. The piston mode of the whole array, which would otherwise also be infinite, is thus …

Mesoscopic Scaling Of Microwave Transmittance And Disorder-Induced Alignment, Israel Kurtz

Dissertations, Theses, and Capstone Projects

This thesis presents microwave measurements and numerical simulations of wave propagation and transmission through random mesoscopic waveguides. We analyze the scaling of mesoscopic microwave conductance, including departures from Ohm’s law near channel openings, which are frequencies at which new propagating modes enter the system, and the evolution of modal phase alignment within the medium, which leads to the observed diversity of transmission eigenvalues. We extend the transmission matrix formalism to all sample depths using the flux matrix, which relates the flux amplitude within the sample to the incident flux, and decompose the flux at each sample depth into forward- and …

The Inverse Elasto-Acoustic Problem, Patrick Grice

Dissertations

A stable and numerically efficient boundary integral method formulation of the elasto-acoustic problem is presented, based on Fourier analysis. The method generalizes well to multiple scattering. The Frechet derivative of the elasto-acoustic problem with respect to shape perturbations is derived, and geometric flow theory is used to design stable numerical methods for the simulation of moving boundaries. The shape derivative is used to define a regularized Gauss-Newton algorithm for shape fitting of elasto-acoustic scatterers.

Symmetry Breaking And Restoration In The Grasshopper Ising Model, Aradh Bisarya

Graduate Masters Theses

Distance-selective interactions in Ising systems give rise to a range of rich and unexpected phenomena. A notable example is the so-called Grasshopper Ising model, a conserved spin Ising model with interactions only between spins at a fixed distance. This model is the discrete version of the following mathematical problem: A grasshopper lands at a random point on a planar lawn of area one. It then makes one jump of fixed distance in a random direction. What lawn shape maximizes the probability that the grasshopper lands on the lawn after the jump? The solution to this problem, corresponding to the ground …

A Variational Algorithm For Preparing Superoptimal Thermal States For Quantum Thermometric Measurement Adaptable To Nisq Hardware, Nicholas Donatelli

Graduate Masters Theses

The conditional thermal state (CTS) is a probe-specific quantum thermal state that is known to outperform the Gibbs state in quantum thermometric measurements at sufficiently low temperatures. This thesis introduces a variational quantum algorithm designed to prepare the CTS on quantum computing hardware which optimizes the angular parameters of the quantum gates that comprise the ansatz circuit and, for the one-qubit case, minimizes relative infidelity of the output state with the known CTS. Using noiseless numerical simulations (SPSA with Qiskit), attempting to prepare the CTS yielded relative infidelities with the known CTS on the order of $10^{-5}$ for most parameter …

Synthesizing Viscoelasticity: Living Polymers, Micro-Macro Relations, And Paths For Resolution, Adam M. Hasler

Graduate Masters Theses

This thesis investigates the relationship between macroscopic rheological signals and underlying microscopic dynamics in complex fluids, specifically focusing on ”living polymers” within the cetyltrimethylammonium bromide (CTAB) and sodium salicylate (NaSal) surfactant system. The research addresses the inverse parameterization problem, demonstrating how bulk measurements like zero-shear viscosity can mask fundamentally different physical topologies, such as purely cylindrical, reptating micelles versus highly branched networks. Through the successful synthesis of viscoelastically ”degenerate” samples, the study utilizes an array of characterization techniques including frequency sweeps, Large Amplitude Oscillatory Shear (LAOS) to resolve these unique underlying states. Furthermore, the work explores further avenues of study …

The Sliding Aperture Transform: A Mathematical Method Applied To Radiation-Induced Dlts Capacitance Transients, Md Abu Bakkar Siddique

Graduate Masters Theses

This thesis presents the Sliding Aperture Transform (SLAPt), a novel mathematical technique for extracting exponential argument and pre-factor  from experimental data. The method transforms measured waveforms into an inverse-domain representation where exponential decay processes appear as distinct peaks, simplifying data analysis and reducing the effects of baseline offsets and noise. The technique is here applied to time dependent capacitance transients associated with irradiated and non-irradiated silicon pn junction diodes. The technique is further developed and applied to positive argument exponentials using an axillary function. This allows forward bias  current-voltage measurements, and forward pulse-bias current transient measurements to be SLAP analyzed, …

Modeling Kinetics Of 5-Aminolevulinic Acid-Induced Protoporphyrin Ix Accumulation For Optimal Photodynamic Therapy, Priscilla Melebor

Graduate Masters Theses

Photodynamic therapy (PDT) is a minimally invasive treatment that uses light-activated photosensitizers to selectively destroy diseased tissue through the generation of reactive oxygen species. However, conventional in vitro models often fail to accurately reproduce the pharmacokinetics of photosensitizer accumulation and clearance observed in vivo. This study investigated protoporphyrin IX (PpIX) accumulation following 5-aminolevulinic acid (ALA) exposure under physiologically relevant conditions using two-dimensional (2D) monolayers and three-dimensional (3D) spheroids. By comparing continuous ALA exposure with transient exposure followed by ALA washout, this work provides a more biologically relevant framework for studying PpIX kinetics and optimizing photodynamic therapy.

A Statistical Mechanics Approach To Reinforcement Learning, Jacob Adamczyk

Graduate Doctoral Dissertations

Reinforcement learning (RL), the study of optimal decision-making over long timescales in stochastic systems, has recently seen remarkable advances due in large part to the efforts of the deep learning community. RL has witnessed great success in solving problems in video games, robotics, biological control, and language modeling. However, a unified statistical mechanics framework to understand and develop the corresponding algorithms is lacking. To address this issue, we begin by showing that the reinforcement learning problem can be formulated and solved using the tools of statistical mechanics. Drawing on physical principles of free energy minimization and invariance, we address important …