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Neural Signatures Of Adhd: A Fast Periodic Visual Stimulation Eeg Study, Haleigh Brielle Davidson May 2025

Neural Signatures Of Adhd: A Fast Periodic Visual Stimulation Eeg Study, Haleigh Brielle Davidson

Theses and Dissertations

Fast Periodic Visual Stimulation (FPVS) offers an objective approach for investigating neural responses to emotional stimuli. This study explores the use of FPVS to identify neurophysiological markers associated with Attention Deficit Hyperactivity Disorder (ADHD) by comparing brain responses between ADHD and Non-ADHD participants. EEG data were collected while participants viewed sequences of neutral faces mixed with emotional oddball expressions (Angry, Fear, Happy, and Sad). Frequency-domain analyses were performed to compute Baseline-Corrected Amplitudes (BCA) and Signal-to-Noise Ratios (SNR) across occipitoparietal, occipitotemporal, parietal, and frontal regions of interest. Results revealed significantly reduced BCA and SNR values in ADHD participants, particularly in the …

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Optimizing Mars Terrain Segmentation With Weakly Supervised Learning: A Focus On Weighted Loss From Annotation Metadata, Malika Dutta May 2025

Optimizing Mars Terrain Segmentation With Weakly Supervised Learning: A Focus On Weighted Loss From Annotation Metadata, Malika Dutta

Theses and Dissertations

The study of planetary surfaces heavily depends upon space rovers that gather detailed images of terrain needed for analysis and navigation. Deep neural networks and other sophisticated machine learning techniques are necessary for autonomous navigation in challenging terrain. However, the inconsistent annotations by citizen scientists frequently hinder the performance of these models. This study seeks to optimize terrain segmentation to improve the autonomous capabilities of future Mars rovers by presenting a novel weakly supervised learning framework to handle noise and unreliability in datasets. Using factors like number of clicks, pixel accuracy, and annotator dependability, the method utilizes annotation metadata in …

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Multi-Modal Sensor Fusion Of Radar And Lidar For Enhanced Navigation In Obstacle-Occluded Environments, Kyler Ashton Farrar May 2025

Multi-Modal Sensor Fusion Of Radar And Lidar For Enhanced Navigation In Obstacle-Occluded Environments, Kyler Ashton Farrar

Theses and Dissertations

Multi-sensor fusion is a practical and well-researched methodology to combine a variety of incoming sensory data into an enhanced digital representation of a real-world environment. A typical use-case for multi-sensor fusion is the combination of LiDAR and RADAR data to obtain simultaneous 3D positioning and velocity measurements for a particular RoI (Region of Interest). This study investigates LiDAR/RADAR sensor fusion for enhanced navigation information when placed in obstacle-occluded environments such as highly vegetated areas. Specifically, a novel fusion-map approach is designed and evaluated for use with a LiDAR/RADAR sensor suite to produce a fused cost map to determine optimal and …

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Evaluation Of Municipal Solid Waste Gasification And The Water Gas Shift Reaction For Biomass Carbon Removal And Storage Via Pre-Combustion Carbon Capture, Colby Luke Freeman May 2025

Evaluation Of Municipal Solid Waste Gasification And The Water Gas Shift Reaction For Biomass Carbon Removal And Storage Via Pre-Combustion Carbon Capture, Colby Luke Freeman

Theses and Dissertations

The water gas shift reaction (WGSR) is a critical step in the pre-combustion capture of CO2 from syngas streams. Recent improvements in gasification technologies have improved the prospects of municipal solid waste (MSW) gasification as a tool for waste reduction and carbon dioxide removal (CDR). This study sought to improve the understanding of a biomass carbon removal and storage (BiCRS) system in which MSW gasification is paired with the WGSR. Sixteen MSW samples were gasified in a bench scale semi-batch reactor. A promising copper based WGSR catalyst was tested for activity from 240-300 degrees Celsius and gas hourly space velocities …

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Comprehensive Study On Bonding Performance, Durability, And Protective Measures Of Cross-Laminated Timber, Bradia Thelina Henfield May 2025

Comprehensive Study On Bonding Performance, Durability, And Protective Measures Of Cross-Laminated Timber, Bradia Thelina Henfield

Theses and Dissertations

The increasing use of cross-laminated timber (CLT) in construction necessitates a deeper understanding of adhesive bonding properties, biological durability, and preservative treatments to enhance its performance. This dissertation investigates these aspects through three interrelated studies focusing on hardwood CLT and preservative-treated southern pine CLT. The first study evaluates the adhesive bonding performance of hardwood CLT fabricated from red oak (Quercus spp.), sweetgum (Liquidambar styraciflua), and yellow poplar (Liriodendron tulipifera), using southern pine (Pinus spp.) as a control. Shear block and delamination tests revealed significant variation in bond strength and moisture durability among species. While red oak exhibited the highest delamination, …

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An In Depth Examination Of Educational, Family, Economic, And Personal Determinants On Academic Performance, Engagement, And Stress: A Comprehensive Study Among Engineering Students, Oumaima Larif May 2025

An In Depth Examination Of Educational, Family, Economic, And Personal Determinants On Academic Performance, Engagement, And Stress: A Comprehensive Study Among Engineering Students, Oumaima Larif

Theses and Dissertations

This study explores the effects of family, education, economic, and personal factors on students’ decisions to pursue engineering as a profession and their long-term impact on performance as engineering students. We adopted a mixed-method approach, collecting data through surveys administered to undergraduate and graduate engineering students at Mississippi State University. The study results revealed that family, education, economic, and personal factors profoundly influence students' decisions to study engineering. We found that parental expectations, background information, and socioeconomic status, in conjunction with cultural norms, values, gender expectations, and religious beliefs, affect students. Additionally, this study identified gaps in the existing literature …

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Impact Of Circular And Non-Circular Nozzle Exit Geometries On Jet Flow Propagation And Turbulence Characteristics, Hiba Maazioui May 2025

Impact Of Circular And Non-Circular Nozzle Exit Geometries On Jet Flow Propagation And Turbulence Characteristics, Hiba Maazioui

Theses and Dissertations

This thesis aims to investigate the impact of nozzle exit geometry on jet flow propagation and turbulence characteristics. Computational fluid dynamics simulations were performed using ANSYS Fluent, employing the Reynolds-Averaged Navier-Stokes (RANS) approach, to compare circular, elliptic, and rectangular nozzle geometries. The analysis focused on velocity distributions, turbulence characteristics, and cross-flow interactions. Results indicate that circular jets have the longest potential core and slowest velocity decay, reflecting lower mixing rates. In contrast, elliptic and rectangular jets have shorter potential cores, faster velocity decay, and elevated TKE peaks, suggesting enhanced turbulence and mixing. These findings highlight the significant role of nozzle …

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A Rapid Artificial Neural Network Interatomic Potential For Bismuth, Lee Michael Mayfield Jr. May 2025

A Rapid Artificial Neural Network Interatomic Potential For Bismuth, Lee Michael Mayfield Jr.

Theses and Dissertations

To study molecular dynamics in bismuth, Quantum Espresso was used to create a density functional theory (DFT) database which was then used as the input for rapid artificial neural network (RANN). The RANN interatomic potential that was developed using this database was then validated. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) was used to create simulations and gather data using the RANN potential. The properties of bismuth, including elastic constants, melting points, and volume change, were calculated and compared to DFT and experimentally observed data. The RANN potential coincided well with these values. The RANN potential shows good predictive capabilities for …

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Integration Of Machine Learning Techniques With Computational Fluid Dynamics For Enhanced Backward-Facing Step Flow, Yahya Mekkaoui May 2025

Integration Of Machine Learning Techniques With Computational Fluid Dynamics For Enhanced Backward-Facing Step Flow, Yahya Mekkaoui

Theses and Dissertations

This research presents a novel integrated framework combining computational fluid dynamics (CFD) with machine learning techniques to enhance the analysis of backward-facing step flows. A high-fidelity OpenFOAM CFD simulation was developed and validated against experimental data, accurately predicting the reattachment length (��/�� ≈ 6.18) and velocity profiles throughout the domain. Machine learning models, including Random Forest, Gradient Boosting, and Support Vector Regression, were integrated through a robust data pipeline, with the ensemble approach demonstrating superior performance (RMSE of 1.18 m/s, ��2 of 0.951). Feature importance analysis revealed pressure (32%) and turbulent kinetic energy (28%) as the dominant physical parameters governing …

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Evaluation Of Soybean (Glycine Max (L.) Merr.) Yield Potential Following Simulated Population Loss And Replant Strategies, William Paul O'Neal May 2025

Evaluation Of Soybean (Glycine Max (L.) Merr.) Yield Potential Following Simulated Population Loss And Replant Strategies, William Paul O'Neal

Theses and Dissertations

Soybean producers are often faced with challenges regarding stand loss situations that can be caused by many different things. Often, in a replant situation, producers must decide if it is best to keep the failed stand without replanting, keep the failed stand and replant at a lower rate, or terminate the failed stand and replant at a full rate. Therefore, the objectives of this research were to evaluate soybean yield potential following differing levels of simulated stand loss as well as to evaluate soybean yield potential following simulated stand loss with different levels of replant. Experiments were conducted in 2023 …

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An Overview Of Global Navigation Satellite System Reflectometry In Coastal Wetlands, Luke Andrew Redwine May 2025

An Overview Of Global Navigation Satellite System Reflectometry In Coastal Wetlands, Luke Andrew Redwine

Theses and Dissertations

With rising global temperatures, increasing sea levels, and the accelerated erosion of coastal wetlands, efficient methods for monitoring this vulnerable ecosystem are crucial. Traditional approaches, such as manual surveys, are labor-intensive, hazardous, and invasive to the environment they are attempting to protect, while current remote sensing methods are cost prohibitive and rely on irregular data collection techniques. To address these challenges, a scalable solution is needed for reliable and frequent data collection. This study explores the use of GNSS Reflectometry (GNSS-R) combined with unmanned aerial vehicles (UAVs) to monitor the shifting topology in wetlands with minimal human invasion. By leveraging …

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Raad-Llm: Adaptive Anomaly Detection Using Llms And Rag Integration, Alicia Russell-Gilbert May 2025

Raad-Llm: Adaptive Anomaly Detection Using Llms And Rag Integration, Alicia Russell-Gilbert

Theses and Dissertations

Anomaly detection in complex industrial environments poses unique challenges, particularly in contexts characterized by data sparsity and evolving operational conditions. Predictive maintenance (PdM) in such settings demands methodologies that are adaptive, transferable, and capable of integrating domain-specific knowledge. This work presents RAAD-LLM, a novel framework for adaptive anomaly detection, leveraging large language models (LLMs) integrated with Retrieval-Augmented Generation (RAG). This approach addresses the aforementioned PdM challenges. By effectively utilizing domain-specific knowledge, RAAD-LLM enhances the detection of anomalies in time-series data without requiring fine-tuning on specific datasets. The framework's adaptability mechanism enables it to adjust its understanding of normal operating conditions …

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Application Of Pu Learning In Detection Of Ddos Attacks, Gagana Sathya Narayana Prasad May 2025

Application Of Pu Learning In Detection Of Ddos Attacks, Gagana Sathya Narayana Prasad

Theses and Dissertations

The gcore radar 2024 says, the number of DDoS attacks has been increased by 46% in 12 months. Supervised and unsupervised techniques struggle detecting DDoS attacks due to the scarcity of labeled attack samples and an overwhelming presence of benign traffic. In contrast PU- Learning offers a promising solutions by dividing the data into positive and unlabeled data. This study explores the effectiveness of PU-learning in detecting DDoS attacks by comparing it with unsupervised methods. This method employs PU Bagging, Two Step method and auto-encoder based models to extract meaningful patters from network traffic data, utilizing CICDDoS2017 dataset for evaluation. …

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Costs And Challenges In The Mississippi Log Trucking Industry, James Tucker Shannon May 2025

Costs And Challenges In The Mississippi Log Trucking Industry, James Tucker Shannon

Theses and Dissertations

Challenges impacting Mississippi log trucking businesses include escalating production costs, labor shortages, aging ownership, and rising liability insurance premiums. These concerns are transmitted back to loggers, landowners, and the entire forest products industry, reducing their contributions to the state’s economy. Lack of current knowledge concerning the adaptation of Mississippi log trucking companies under adverse business conditions necessitated a statewide mixed-mode survey to determine the industry’s structure, the nature of liability insurance premiums, and business owner perceptions about driver hiring and profitability. Mississippi log trucking business owners and drivers were predominantly middle-aged, with fewer individuals under the age of 40. Log …

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Evaluating Rainfall Sensitivity Over Land To Tropical Cyclone Parameters Using Idealized Wrf, Madison C. Yawn May 2025

Evaluating Rainfall Sensitivity Over Land To Tropical Cyclone Parameters Using Idealized Wrf, Madison C. Yawn

Theses and Dissertations

Tropical cyclones (TCs) are extreme weather events impacting the United States nearly every year. These events often cause severe damage due to the associated responses they produce including storm surge and rainfall, and the accurate estimation of these TC hazards is necessary to support coastal engineering, risk assessment, and emergency management activities. Evaluating TC-driven hazards is often done in combination with numerical models to simulate how environmental interactions alter the physical processes and responses of these storms. The purpose of this study was to simulate synthetic TC events using the Advanced Weather Research and Forecasting (WRF) model to understand how …

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Lateral Control Of Autonomous Vehicle Using Deep Cnn And Ampc, Iffat Ara Ebu May 2025

Lateral Control Of Autonomous Vehicle Using Deep Cnn And Ampc, Iffat Ara Ebu

Theses and Dissertations

Autonomous functionalities are pivotal for the advancement of Advanced Driver Assistance Systems (ADAS), driving towards collision-free and environmentally sustainable transportation. This thesis presents two distinct studies addressing critical aspects of autonomous vehicle control: lane centering via deep learning and lateral vehicle control using model predictive control. The first study explores end-to-end learning f or autonomous s teering command generation, focusing on lane centering. A convolutional neural network (CNN) model, inspired by NVIDIA’s PilotNet, is employed to directly map raw camera pixel inputs to steering commands, eliminating the need for intermediate feature engineering. The model is trained and validated using datasets …

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Unraveling Exoplanetary Signatures From Stellar Activity: A Journey Beyond The Known In Rv Mass Measurements Of K Dwarf Planets, Claire Susanne Geneser May 2025

Unraveling Exoplanetary Signatures From Stellar Activity: A Journey Beyond The Known In Rv Mass Measurements Of K Dwarf Planets, Claire Susanne Geneser

Theses and Dissertations

A precise radial velocity (RV) monitoring campaign was conducted for two Targets of Interest (TOI), TOI-2443 b and TOI-139 b, identified by the Transiting Exoplanet Survey Satellite (TESS) as exoplanet candidates orbiting K dwarf stars. Preliminary estimates of the transmission spectroscopy metric (TSM) indicate that the transiting planets are promising targets for atmospheric follow-up. I perform a multi-planet RV analysis of the TOI-2443 system, combining infrared and optical RV data. The model robustly recovers the signal of TOI-2443 b, an eccentric warm sub-Neptune, with a semi-amplitude of 2.54 ± 0.24 m/s, corresponding to a mass of 7.11 ± 0.67 ��⊕ …

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Atmospheric Turbulence Education Effects On Flight Anxiety, Megan A. Hanna May 2025

Atmospheric Turbulence Education Effects On Flight Anxiety, Megan A. Hanna

Theses and Dissertations

This study examines the effect of turbulence education on flight anxiety. A pre-post methodology measured students’ anxiety levels before and after a study abroad flight, using an educational video during the pre-flight survey to change their feelings. The Flight Anxiety Situations (FAS) questionnaire assessed anxiety at three survey points: pre-video, post-video, and post-flight. Qualitative analysis using Friedman’s test and the Wilcoxon Signed-rank test, indicated that turbulence education effectively decreased generalized and anticipatory flight anxiety, particularly in non-phobic students. Text analysis of open-ended responses suggested increased scientific knowledge post-video helped students apply technical atmospheric processes to their feelings. Turbulence education was …

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Interactions Between Different Deformation Mechanisms In Magnesium, Ethan T. Holder May 2025

Interactions Between Different Deformation Mechanisms In Magnesium, Ethan T. Holder

Theses and Dissertations

Magnesium is a strong and lightweight material with the potential to be used for weight reduction in various industries. However, manufacturing magnesium parts is difficult because magnesium is brittle at room temperature. Understanding the underlying deformation mechanisms in magnesium is critical to improving its ductility. In this work a Rapid Artificial Neural Network (RANN) potential was used to perform a Molecular Dynamics (MD) simulation in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to study twin formation and growth as well as interactions between different twin modes in a magnesium bicrystal. This work offers insight into the mechanisms of plastic deformation in …

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Investigating Structure-Property Relationships Of Bio-Inspired Gel, Mohammad Moinul Hossain May 2025

Investigating Structure-Property Relationships Of Bio-Inspired Gel, Mohammad Moinul Hossain

Theses and Dissertations

High-modulus, stretchable, and resilient hydrogels possess a wide array of promising applications across multiple fields, such as the development of sophisticated prosthetic devices, artificial skin, electronic devices, and soft robotics. Elastomeric biopolymers, like resilin, show high stretchability and resilience, facilitating power-amplified movement in various species essential for feeding and defense mechanisms. To mimic the properties of resilin, we developed a hydrogel system of hydrophobic and hydrophilic components. These gels are synthesized by free radical polymerization of acrylic acid (AAc), methacrylamide (MAM), n-tert-beutylacrylamide (BAM) or n-isopropylacrylamide (NIPAM), and poly (propylene glycol) diacrylate (PPGDA). This research aims to compare the large-strain mechanical …

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Wildfire Hydrologic Impacts, Kathleen E. Inman May 2025

Wildfire Hydrologic Impacts, Kathleen E. Inman

Theses and Dissertations

Wildfires are essential processes for certain ecosystems but are increasing in severity and occurrence. These increases are negatively changing hydrology. Anticipating the hydrologic changes is necessary for management of effected watersheds, infrastructure, and downstream users. This study hypothesized land cover changes post-fire would increase water temperature and discharge in burned watersheds located in the Willamette Basin. This study (1) evaluated the change in estimated curve numbers (CN) from land cover pre-fire and post-fire to assess expected runoff impacts in watersheds, and (2) identified the significance of actual water temperature and discharge changes using non-parametric statistical analysis. An unburned watershed and …

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Semantic Segmentation Via Transfer Learning For Off-Road Data, Haley Breann Honigfort May 2025

Semantic Segmentation Via Transfer Learning For Off-Road Data, Haley Breann Honigfort

Theses and Dissertations

In autonomous driving, utilizing deep learning models to help make decisions has become a popular theme, particularly in the realm of computer vision. Deep learning models are heavily influenced to make decisions based on the environments in which they are trained. Currently, very few datasets exist for off-road autonomy that include visual semantic segmentation labels. Traditional semantic segmentation requires hand-labeling large imagery datasets or using synthetically generated imagery to train a model. This study aims to apply transfer learning techniques to automatically label a new off-road dataset. That objective will be accomplished in two phases: first, by utilizing pre-existing labels …

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A Systematic Literature Review Of The Implementation Of High-Quality Instructional Materials (Hqims) In K-12 Education, Melanie Jackson May 2025

A Systematic Literature Review Of The Implementation Of High-Quality Instructional Materials (Hqims) In K-12 Education, Melanie Jackson

Theses and Dissertations

The implementation of High-Quality Instructional Materials (HQIMs) in K–12 education is essential for promoting equitable and effective learning outcomes. Additionally, HQIMs ensure that students are engaged with grade-level material, which is critical for achieving mastery of grade-level standards, thereby fostering deeper understanding and academic success across all student populations. However, challenges such as misalignment with curriculum standards, insufficient professional development, limited teacher buy-in, and resource disparities continue to hinder successful implementation. This study aims to examine these barriers and identify evidence-based strategies to support effective HQIMs implementation. Specifically, this research seeks to answer the question: "What are the key factors …

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Finite Element Analysis Of Hydroxyapatite (Ha) Coated Porous We43 Magnesium Scaffolds For Simulating Long-Time In Vitro Degradation Using A Continuum Damage Model, Dam Kim May 2025

Finite Element Analysis Of Hydroxyapatite (Ha) Coated Porous We43 Magnesium Scaffolds For Simulating Long-Time In Vitro Degradation Using A Continuum Damage Model, Dam Kim

Theses and Dissertations

While magnesium and its alloys are viable biodegradable implant candidates for its similarity of Young’s modulus with human bone and its strong biocompatibility, a pure magnesium scaffold degrades too rapidly to be used in many orthopedic implications. Overcoming this high degradation rate has been one of the biggest technical challenges for Mg-based biomedical applications. This research focuses on validating a finite element analysis framework using a continuum damage model and its application to simulate the degradation process of non-coated additively manufactured WE43 and HA-coated WE43 magnesium scaffolds. This work includes determining model input parameters by matching in vitro experiment results …

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Apatite Entrapment Of Iodine For Nuclear Waste Disposal Applications, William E. Laird May 2025

Apatite Entrapment Of Iodine For Nuclear Waste Disposal Applications, William E. Laird

Theses and Dissertations

The purpose of this thesis is to provide baseline knowledge of iodine incorporation into calcium phosphate minerals, specifically apatite. Iodine-129 is a fission product in Spent Nuclear Fuel (SNF) that can administer significant amounts of radiation in small quantities. Apatite (Ca10(PO4)6 (OH, F, Cl)) has been studied for the use of radionuclide confinement. Experimental design was set up to mimic temperatures expected in geologic repositories from 40 to 250℃. Experiments are broken into 2 groups based on iodine species being examined. The first group focuses on iodate (IO3-) which is prevalent under oxidized conditions, and the second handles iodide (I-) …

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Research Advancement Of Guayule Resin As A Natural Wood Preservative, Abigael Nasimiyu Laisa May 2025

Research Advancement Of Guayule Resin As A Natural Wood Preservative, Abigael Nasimiyu Laisa

Theses and Dissertations

Increasing concerns about human health and the environment have led to raised demand for eco-friendly wood preservatives. Guayule resin, extracted from Parthenium argentatum plant contains insecticidal and antifungal compounds making it a promising natural wood preservative. This study evaluated suitable carrier system for guayule resin, as well as leaching rate and termite resistance of treated yellow poplar and southern pine specimens. Wood specimens were treated with different concentrations of guayule in acetone, toluene, and ethyl acetate using vacuum impregnation. The leaching behavior and termite resistance of the treated specimens were assessed according to the AWPA Standard E11-16 and AWPA Standard …

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Cyber Security Threat Recognition And Preparedness Of Undergraduate Students, Litany Hope Lineberry May 2025

Cyber Security Threat Recognition And Preparedness Of Undergraduate Students, Litany Hope Lineberry

Theses and Dissertations

Cybersecurity awareness and preparedness are critical competencies for individuals across academic disciplines and professional sectors. However, undergraduate students often lack sufficient knowledge and skills to recognize and mitigate cybersecurity threats. This dissertation examines cybersecurity threat recognition and preparedness among undergraduate students through a three-phase research approach. Study 1 explores faculty perspectives on students' cybersecurity awareness, identifying gaps in knowledge and preparedness across various fields of study. Study 2 investigates industry professionals' perceptions of new hires’ cybersecurity readiness, assessing the alignment between academic training and industry expectations. Study 3 evaluates the effectiveness of an online intervention designed to enhance students' cybersecurity …

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Asphalt Durability Improvements By Way Of Specification Advancements, Jessica V. Lewis May 2025

Asphalt Durability Improvements By Way Of Specification Advancements, Jessica V. Lewis

Theses and Dissertations

The objective of this dissertation is to provide content through which industry and agencies can adjust and/or update standards and specifications, as appropriate, to accommodate the present-day needs of the asphalt industry towards producing more durable asphalt. A total of 78 asphalt mixtures and 9 asphalt binders were evaluated for up to 10 years of field aging to provide content that was analyzed to meet this objective. A full-scale aging site in Columbus, Mississippi was the focal point of the aging experiments. A major conclusion from this work was that Cantabro Mass Loss (CML) testing of cores was able to …

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Advancing Wood Chip Moisture Content Prediction Using Advanced Generative Ai Techniques, Daniel Esteban Marulanda May 2025

Advancing Wood Chip Moisture Content Prediction Using Advanced Generative Ai Techniques, Daniel Esteban Marulanda

Theses and Dissertations

In this study we propose a deep learning method to optimize the classification of wood chip moisture content levels using the Vision Transformer and then ultimately increase the classification performance by creating synthetic images using the diffusion transformer model. In the first chapter of our study, we complete a detailed explanation of how the moisture content levels of 10 different wood chips were gathered ranging from 2 to 50$\%$. This chapter serves as a foundation for subsequent sections, illustrating the challenges associated with the current data collection process, which is both time-consuming and inefficient. Accurately determining moisture content for wood …

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Atomistic Modeling Of Mg And Al Systems Using Rapid Artificial Neural Network Derived Interatomic Potential, Edward Omozusi Obasuyi May 2025

Atomistic Modeling Of Mg And Al Systems Using Rapid Artificial Neural Network Derived Interatomic Potential, Edward Omozusi Obasuyi

Theses and Dissertations

Machine learning derived interatomic potentials have proven to be effective tools in simulation that mimic the accuracy of ab-initio calculations to the sub meV/atom level. They offer the advantage of computational speed operating at linear scaling with respect to the system’s size making them more efficient than classical potentials like MEAM (modified embedded atom methods). In this work, interatomic potentials are created based on the rapid artificial neural network (RANN) formalism for magnesium (Mg), Aluminum (Al) and their alloys. From previous works, the RANN formalism produces high-fidelity atomic models with accurate force fields for several metals, offering new insights into …

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