Computational chemistry.
Overview
| Works: | 107 works in 8 publications in 8 languages | |
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Titles
A Mapping-Variable Ring Polymer Molecular Dynamics Study of Multi-State Reaction Mechanisms in the Condensed Phase.
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Molecular Simulations of Phase Behavior for Polymer Blends and Block Polymers.
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Computational materials, chemistry, and biochemistry = from bold initiatives to the last mile : in honor of William A. Goddard's contributions to science and engineering.. Volume 2 /
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Computational Studies of the Photophysical, Structural, and Catalytic Properties of Complex Chemical Systems.
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Computational Approach Toward Rational Device Engineering of Organic Photovoltaics.
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Unraveling Foldamer Secondary Structure: A Computational Investigation of New Folding Oligomers.
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Analyzing and Optimizing an Array of Low-Cost Gas Sensors for use in an Air Quality Measurement Device with Machine Learning.
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Uncertainty in Combustion Reaction Rates and Its Effects on Combustion Simulations.
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Surface Chemistry of Model Oxygenates on Nickel and Platinum Single Crystals for Bio-Oil Upgrading and Synthesis of Renewable Chemicals.
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Integrated in silico-in vitro Approaches to Toxicity Assessment and Molecular Design in 21st Century.
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Exploring Complex Cellular Membranes Containing Lipids, Cholesterols, Proteins, and Gangliosides Using Molecular Simulations.
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Modern Computational Approaches to Nonlinear Discrete Optimization and Applications in Process Systems Engineering = = Enfoques Computacionales Modernos a la Optimizacion Discreta No Lineal y Aplicaciones en la Ingenieria de Procesos.
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Improving Wavefunction Efficiency by Tessellating Correlation Factors and Coupled State-Specific Optimization.
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Uv-Curable Hybrid Sol-Gel Materials: The Development and Application of a 3-Methacryloxypropytrimethoxysilane-Derived Coating.
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Importance Learning: New Methods to Efficiently Model Heterogeneous Catalysts with Quenched Disorder.
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Computational and Theoretical Methods for Stress Modulated Phase Transition in Solid State Materials with Applications to Two Dimensional MoTe2.
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Dynamics of Surfaces and Interfaces : = From First-Principles Modeling to Machine-Learning Molecular Dynamics.
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Expanding the Electronic Structure Toolkit for f-Element Chemistry : = Advances, Best Practices, and Examples.
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Process Design, Techno-Economic Analysis, and Life Cycle Assessment of Adipic Acid Production from Lignin.
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Understanding Gas and Energy Storage in Geological Formations With Molecular Simulations.
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A Molecular Dynamics Study of Structural Modifications of Perarylphosphonium Based Ionic Liquids on the Melting Point.
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Expanding the Capabilities of Atmospheric Chemistry Models and Datasets Using Machine Learning and Data-Driven Methods.
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Investigating the Fundamental Kinetics of BiofuelCombustion Behavior via a Semi-Automated, Theory-based approach.
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The Study of Nitrogen-Containing Molecules of Astrochemical Importance Using Rotational Spectroscopy and Computational Chemistry.
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Evaluation of the Energetic Factors in Crystalline Pharmaceuticals Using Solid-State Density Functional Theory and Low-Frequency Vibrational Spectroscopy.
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Computational Methods Applied to the Study of the Structure, Spectra, and Reactivity of Small Organic Molecules.
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Electronic Structure Based Investigations of Hybrid Perovskites and their Nanostructures.
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Predictive Spectroscopic and Thermodynamic Properties of Complex Solutions and Interfaces.
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Computational chemistry = introduction to the theory and applications of molecular and quantum mechanics /
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Chemical and Physical Interfacial Processes Underlying Environmental Water.
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Integrating Machine Learning and Protein Structural Features to Predict Drug Toxicity.
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Machine Learning Interatomic Potentials for First-Principles Electrochemistry.
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An Optimization Framework for Kinetic Model Building from Concentration and Spectroscopic Data.
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Investigation of Organic Dyes for Dye-Sensitized and Organic Solar Cell Applications.
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Accounting for Chemical Change in Classical and QM-Hybrid Molecular Dynamics Simulations of Proteins and Metalloproteins.
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Multi-Scale Computational Chemistry Approach for Understanding the Porous Materials: The MOF-253-Based Catalyst Example = = 以多尺度計算化學方法理解孔洞材料： 以基於 MOF-253 的催化劑為例 /
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Investigations of Point Defect Properties and Dislocation Mechanisms in the Equiatomic Nb-Mo-Ta-W Refractory Alloy by Computational Modeling and Simulations.
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Grand Canonical Approach to Modeling Dynamic Catalysts: From Thermal to Electro-Catalysis, From Clusters to Surfaces.
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Computational Studies of Catalysis: Bioinorganic, Inorganic, and Organometallic Chemistry.
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From Virtual High-throughput Screening and Machine Learning to the Discovery and Rational Design of Polymers for Optical Applications.
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Fast, Atomic-Level Simulations of the Forced Unfolding of Proteins Using a New Membrane Burial Potential.
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Multiscale Modeling and Machine Learning Studies of the Diffusion of Silicon and Intrinsic Defects in III-V Semiconductors.
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Scalable Molecular Design Using Reversible Jump MCMC and Stochastic Approximation.
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Investigating Color Additive Molecules for Pharmaceutical and Cosmetic Applications: A Comparison of Theoretical and Experimental UV-Visible Absorbance Spectra in Tunable Solvents.
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Open Source Software for the Prediction of Crystal Structures and the Analysis of Their Properties.
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Data Science in Scanning Probe Microscopy: Advanced Analytics and Machine Learning.
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Multi-Scale Modeling of Lignin Biosynthesis and Other Wood Properties in Populus trichocarpa.
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First-Principles Study on the Structural and Thermal Properties of Molecular Crystals and Liquids.
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Prediction of Drug-drug Interaction Potential Using Machine Learning Approaches.
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Computational Modeling of (De)-Solvation Effects and Protein Flexibility in Protein-Ligand Binding Using Molecular Dynamics Simulations.
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First Principles Study of Spinel Electrode Materials in Lithium Ion Batteries.
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First Principles Studies of Aqueous Systems at Ambient and Extreme Conditions.
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Thermodynamic Screening of Reaction Chemistries for Atomic Layer Etching of Metals.
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Understanding and Predicting the Kinetic Behavior of Metal Oxide Materials for Solar Thermochemical Hydrogen Production.
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Current-Constrained Reduced-Density-Matrix Theory for Molecular Conductivity.
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Developing and Applying Nonadiabatic Dynamics Methods for Nanoscale and Periodic Systems.
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Machine Learning Towards Large-Scale Atomistic Simulation and Materials Discovery.
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A Combustion Model for Multi-Component Fuels Based on Relative Reactivity and Molecular Structure.
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Predicting, Engineering and Interpreting Gene Regulatory Sequences and Proteins with Deep Learning.
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Hydrated Proton Structure and Transport in Complex Heterogeneous Systems.
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Using Molecular Simulations as an Integral Tool for Modeling Ionic Liquid Crystals and Colloidal Clusters.
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Numerical and Machine Learning Assisted Simulations of Complex Polymer Systems.
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Domain-Knowledge-Guided Machine Learning towards Accurate Materials Property Prediction and Materials Discovery.
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Computational Molecular Design for Developing Metal-Free Organic Emissive Materials.
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Accelerating the Discovery of Materials for Energy Capture and Energy Storage Using Quantum Chemistry and Machine Learning.
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Deep Learning Accelerated Studies of Electrochemical Systems - Applications in the Analysis of Wire Electrodes and Cyclic Voltammetry.
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Nucleic Acid Structure and Interactions Revealed by Computer Simulations.
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Computational Studies of Biological Systems and Nanomaterials and Their Applications.
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Microwaves for Intensified Chemical Manufacturing: Applications to Biomass Processing.
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A Machine Learning-Driven Methodology for the Design of Exchange-Correlation Functionals.
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Investigations into Proton Transfer and Energy Conversion Using Machine Learning and Quantum Chemistry /
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Quantitative Evaluation of Simultaneous Selective Ion Clustering and Hydrogen/Deuterium Exchange.
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Expanding the Atomistic Study of the Optical and Electronic Properties of Nanomaterials.
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