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Informationen zum Autor Abby L. Parrill, PhD, is Professor of Chemistry in the Department of Chemistry at the University of Memphis, TN. Her research interests are in bioorganic chemistry, protein modeling and NMR Spectroscopy and rational ligand design and synthesis. In 2011, she was awarded the Distinguished Research Award by University of Memphis Alumni Association. She has given more than 100 presentations, more than 100 papers and books. Kenny B. Lipkowitz , PhD, is a recently retired Professor of Chemistry from North Dakota State University. Klappentext The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered on molecular modeling, such as computer-assisted molecular design (CAMD), quantum chemistry, molecular mechanics and dynamics, and quantitative structure-activity relationships (QSAR). This volume, like those prior to it, features chapters by experts in various fields of computational chemistry. Topics in Volume 29 include:* Noncovalent Interactions in Density-Functional Theory* Long-Range Inter-Particle Interactions: Insights from Molecular Quantum Electrodynamics (QED) Theory* Efficient Transition-State Modeling using Molecular Mechanics Force Fields for the Everyday Chemist* Machine Learning in Materials Science: Recent Progress and Emerging Applications* Discovering New Materials via a priori Crystal Structure Prediction* Introduction to Maximally Localized Wannier Functions* Methods for a Rapid and Automated Description of Proteins: Protein Structure, Protein Similarity, and Protein Folding Zusammenfassung The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered on molecular modeling! such as computer-assisted molecular design (CAMD)! quantum chemistry! molecular mechanics and dynamics! and quantitative structure-activity relationships (QSAR). This volume! like those prior to it! features chapters by experts in various fields of computational chemistry. Topics in Volume 29 include:* Noncovalent Interactions in Density-Functional Theory* Long-Range Inter-Particle Interactions: Insights from Molecular Quantum Electrodynamics (QED) Theory* Efficient Transition-State Modeling using Molecular Mechanics Force Fields for the Everyday Chemist* Machine Learning in Materials Science: Recent Progress and Emerging Applications* Discovering New Materials via a priori Crystal Structure Prediction* Introduction to Maximally Localized Wannier Functions* Methods for a Rapid and Automated Description of Proteins: Protein Structure! Protein Similarity! and Protein Folding Inhaltsverzeichnis Contributors x Preface xii Contributors to Previous Volumes xv 1 Noncovalent Interactions in Density Functional Theory 1 Gino A. DiLabio and Alberto Otero-de-la-Roza Introduction 1 Overview of Noncovalent Interactions 3 Theory Background 9 Density?-Functional Theory 9 Failure of Conventional DFT for Noncovalent Interactions 17 Noncovalent Interactions in DFT 20 Pairwise Dispersion Corrections 20 Potential-Based Methods 42 Minnesota Functionals 47 Nonlocal Functionals 54 Performance of Density Functionals for Noncovalent Interactions 59 Description of Noncovalent Interactions Benchmarks 59 Performance of Dispersion-Corrected Methods 66 Noncovalent Interactions in Perspective 74 Acknowledgments 78 References 79 2 Long?-Range Interparticle Interactions: Insights from Molecular Quantum Electrodynamics (QED) Theory 98 Akbar Salam Introduction 98 The Interaction Energy at Long Range 101 Molecular QED Theory 104 Electrostatic Interaction in Multipolar QED 112
Sommario
Contributors x
Preface xii
Contributors to Previous Volumes xv
1 Noncovalent Interactions in Density Functional Theory 1
Gino A. DiLabio and Alberto Otero-de-la-Roza
Introduction 1
Overview of Noncovalent Interactions 3
Theory Background 9
Density?-Functional Theory 9
Failure of Conventional DFT for Noncovalent Interactions 17
Noncovalent Interactions in DFT 20
Pairwise Dispersion Corrections 20
Potential-Based Methods 42
Minnesota Functionals 47
Nonlocal Functionals 54
Performance of Density Functionals for Noncovalent Interactions 59
Description of Noncovalent Interactions Benchmarks 59
Performance of Dispersion-Corrected Methods 66
Noncovalent Interactions in Perspective 74
Acknowledgments 78
References 79
2 Long?-Range Interparticle Interactions: Insights from Molecular Quantum Electrodynamics (QED) Theory 98
Akbar Salam
Introduction 98
The Interaction Energy at Long Range 101
Molecular QED Theory 104
Electrostatic Interaction in Multipolar QED 112
Energy Transfer 114
Mediation of RET by a Third Body 119
Dispersion Potential between a Pair of Atoms or Molecules 123
Triple-Dipole Dispersion Potential 128
Dispersion Force Induced by External Radiation 132
Macroscopic QED 136
Summary 141
References 143
3 Efficient Transition State Modeling Using Molecular Mechanics Force Fields for the Everyday Chemist 152
Joshua Pottel and Nicolas Moitessier
Introduction 152
Molecular Mechanics and Transition State Basics 154
Molecular Mechanics 154
Transition States 157
Ground State Force Field Techniques 158
Introduction 158
ReaxFF 159
Reaction Force Field 161
Seam 163
Empirical Valence Bond/Multiconfiguration Molecular Dynamics 166
Asymmetric Catalyst Evaluation 169
TSFF Techniques 173
Introduction 173
Q2MM 175
Conclusion and Prospects 178
References 178
4 Machine Learning in Materials Science: Recent Progress and Emerging Applications 186
Tim Mueller, Aaron Gilad Kusne, and Rampi Ramprasad
Introduction 186
Supervised Learning 188
A Formal Probabilistic Basis for Supervised Learning 189
Supervised Learning Algorithms 199
Unsupervised Learning 213
Cluster Analysis 215
Dimensionality Reduction 226
Selected Materials Science Applications 237
Phase Diagram Determination 237
Materials Property Predictions Based on Data from Quantum Mechanical Computations 240
Development of Interatomic Potentials 245
Crystal Structure Predictions (CSPs) 249
Developing and Discovering Density Functionals 250
Lattice Models 251
Materials Processing and Complex Materials Behavior 256
Automated Micrograph Analysis 257
Structure-Property Relationships in Amorphous Materials 260
Additional Resources 263
Summary 263
Acknowledgments 264
References 264
5 Discovering New Materials via A Priori Crystal Structure Prediction 274
Eva Zurek
Introduction and Scope 274
Crystal Lattices and Potential Energy Surfaces 276
Calculating Energies and Optimizing Geometries 281
Methods to Predict Crystal Structures 282
Following Soft Vibrational Modes 283
Random (Sensible) Str
