A5006692106- Machine Learning in Materials Science
- Boron and Carbon Nanomaterials Research
- Advanced Chemical Physics Studies
- Metal and Thin Film Mechanics
- Rare-earth and actinide compounds
- Catalytic Processes in Materials Science
- Nuclear Physics and Applications
- Electronic and Structural Properties of Oxides
- Photoreceptor and optogenetics research
- Photochromic and Fluorescence Chemistry
- Ammonia Synthesis and Nitrogen Reduction
- Thermal properties of materials
- Advanced Materials Characterization Techniques
- Quantum and electron transport phenomena
- Inorganic Chemistry and Materials
- Advanced Photocatalysis Techniques
- Organic Chemistry Cycloaddition Reactions
- Forensic Fingerprint Detection Methods
- Caching and Content Delivery
- Surface and Thin Film Phenomena
- MXene and MAX Phase Materials
- Aluminum Alloys Composites Properties
- Advanced ceramic materials synthesis
- Hydrogen Storage and Materials
- Industrial Vision Systems and Defect Detection
West Virginia University
2017-2025
Opexa Therapeutics (United States)
2024
American Academy of Forensic Sciences
2024
Morgantown High School
2021
Azobenzene is a very important system that often studied for better understanding light-activated mechanical transformations via photoisomerization. The central C-N═N-C dihedral angle widely recognized as the primary reaction coordinate changing cis- to trans-azobenzene and vice versa. We report on global (containing all internal coordinates) thoroughly describe mechanism azobenzene Our includes of coordinates contributing photoisomerization coordinate. quantify contribution each overall...
Thermocatalytic decomposition (TCD) of methane can produce hydrogen and valuable nanocarbon co-products with low to near-zero CO<sub>2</sub> emission.
The search for new superhard materials is of great interest extreme industrial applications. However, the theoretical prediction hardness still a challenge scientific community, given difficulty modeling plastic behavior solids. Different models have been proposed over years. Still, they are either too complicated to use, inaccurate when extrapolating wide variety solids or require coding knowledge. In this investigation, we built successful machine learning model that implements Gradient...
Solar-driven production of renewable energy (e.g., H2) has been investigated for decades. To date, the applications are limited by low efficiency due to rapid charge recombination (both radiative and nonradiative modes) slow reaction rates. Tremendous efforts have focused on reducing enhancing interfacial transfer engineering geometric electronic structure photocatalysts. However, fine-tuning processes optimization target paths still lack effective control. Here we show that minimizing...
Abstract The density-functional theory is widely used to predict the physical properties of materials. However, it usually fails for strongly correlated A popular solution use Hubbard correction treat electronic states. Unfortunately, values U and J parameters are initially unknown, they can vary from one material another. In this semi-empirical study, we explore parameter space a group iron-based compounds simultaneously improve prediction (volume, magnetic moment, bandgap). We Bayesian...
Density-functional theory is widely used to predict the physical properties of materials. However, it usually fails for strongly correlated A popular solution use Hubbard corrections treat electronic states. Unfortunately, exact values $U$ and $J$ parameters are initially unknown, they can vary from one material another. In this semi-empirical study, we explore parameter space a group iron-based compounds simultaneously improve prediction (volume, magnetic moment, bandgap). We Bayesian...
This paper presents a comprehensive update to PyProcar, versatile Python package for analyzing and visualizing density functional theory (DFT) calculations in materials science. The latest version introduces modularized codebase, centralized example data repository, robust testing framework, offering more reliable, maintainable, scalable platform. Expanded support various DFT codes broadens its applicability across research environments. Enhanced documentation an gallery make the accessible...
Abstract A physical fit is an important observation that can result from the forensic analysis of trace evidence as it conveys a high degree association between two items. However, examinations be time‐consuming, and potential bias analysts may affect judgment. To overcome these shortcomings, data algorithm using mutual information decision tree has been developed to support practitioners in interpreting evidence. We created tools obtained duct tape textiles analyzed previous studies, along...
Abstract This investigation has studied the six most-used macroscopic models to compute hardness from elastic constants, using an experimental database of 143 materials. "The Hardness Calculator" is proposed as a solution estimate in easy, fast and confident manner. study divides into two stages. The first approach, referred Classic Calculator", selection model based on simple properties solid such crystal system, bandgap, density. second phase machine learning (ML) based, it Machine...