Computational chemistry.
概要
作品: | 82 作品在 7 項出版品 7 種語言 |
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書目資訊
A Mapping-Variable Ring Polymer Molecular Dynamics Study of Multi-State Reaction Mechanisms in the Condensed Phase.
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Open Source Software for the Prediction of Crystal Structures and the Analysis of Their Properties.
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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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Integrated in silico-in vitro Approaches to Toxicity Assessment and Molecular Design in 21st Century.
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Understanding and Predicting the Kinetic Behavior of Metal Oxide Materials for Solar Thermochemical Hydrogen Production.
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Accounting for Chemical Change in Classical and QM-Hybrid Molecular Dynamics Simulations of Proteins and Metalloproteins.
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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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Computational Studies of the Photophysical, Structural, and Catalytic Properties of Complex Chemical Systems.
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Importance Learning: New Methods to Efficiently Model Heterogeneous Catalysts with Quenched Disorder.
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Expanding the Electronic Structure Toolkit for f-Element Chemistry : = Advances, Best Practices, and Examples.
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A Molecular Dynamics Study of Structural Modifications of Perarylphosphonium Based Ionic Liquids on the Melting Point.
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Investigating the Fundamental Kinetics of BiofuelCombustion Behavior via a Semi-Automated, Theory-based approach.
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Computational Methods Applied to the Study of the Structure, Spectra, and Reactivity of Small Organic Molecules.
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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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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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Computational Studies of Catalysis: Bioinorganic, Inorganic, and Organometallic Chemistry.
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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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Exploring Complex Cellular Membranes Containing Lipids, Cholesterols, Proteins, and Gangliosides Using Molecular Simulations.
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Developing and Applying Nonadiabatic Dynamics Methods for Nanoscale and Periodic Systems.
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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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Using Molecular Simulations as an Integral Tool for Modeling Ionic Liquid Crystals and Colloidal Clusters.
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Dynamics of Surfaces and Interfaces : = From First-Principles Modeling to Machine-Learning Molecular Dynamics.
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Domain-Knowledge-Guided Machine Learning towards Accurate Materials Property Prediction and Materials Discovery.
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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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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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Expanding the Capabilities of Atmospheric Chemistry Models and Datasets Using Machine Learning and Data-Driven Methods.
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