Reviews in Computational Chemistry, Volume 31

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 31 include:

Lattice-Boltzmann Modeling of Multicomponent Systems: An Introduction
Modeling Mechanochemistry from First Principles
Mapping Energy Transport Networks in Proteins
The Role of Computations in Catalysis
The Construction of Ab Initio Based Potential Energy Surfaces
Uncertainty Quantification for Molecular Dynamics

List of Contributors ix

Preface xi

Contributors to Previous Volumes xv

1 Lattice-Boltzmann Modeling of Multicomponent Systems: An Introduction 1
Ulf D. Schiller and Olga Kuksenok

Introduction 1

The Lattice Boltzmann Equation: A Modern Introduction 4

A Brief History of the LBM 5

The Lattice Boltzmann Equation 7

The Fluctuating Lattice Boltzmann Equation 23

Boundary Conditions 25

Fluid–Particle Coupling 30

LBM for Multiphase Fluids 37

Governing Continuum Equations 37

Lattice Boltzmann Algorithm for Binary Fluid: Free-Energy Approach 42

Minimizing Spurious Velocities 47

Conclusions 50

References 51

2 Mapping Energy Transport Networks in Proteins 63
David M. Leitner and Takahisa Yamato

Introduction 63

Thermal and Energy Flow in Macromolecules 65

Normal Modes of Proteins 65

Simulating Energy Transport in Terms of Normal Modes 69

Energy Diffusion in Terms of Normal Modes 70

Energy Transport from Time Correlation Functions 73

Energy Transport in Proteins is Inherently Anisotropic 75

Locating Energy Transport Networks 77

Communication Maps 77

CURrent calculations for Proteins (CURP) 80

Applications 83

Communication Maps: Illustrative Examples 83

CURP: Illustrative Examples 89

Future Directions 98

Summary 99

Acknowledgments 100

References 100

3 Uncertainty Quantification for Molecular Dynamics 115
Paul N. Patrone and Andrew Dienstfrey

Introduction 115

From Dynamical to Random: An Overview of MD 118

System Specification 119

Interatomic Potentials 121

Hamilton’s Equations 123

Thermodynamic Ensembles 128

Where Does This Leave Us? 131

Uncertainty Quantification 131

What is UQ? 132

Tools for UQ 136

UQ of MD 143

Tutorial: Trajectory Analysis 143

Tutorial: Ensemble Verification 148

Tutorial: UQ of Data Analysis for the Glass-Transition Temperature 151

Concluding Thoughts 161

References 162

4 The Role of Computations in Catalysis 171
Horia Metiu, Vishal Agarwal, and Henrik H. Kristoffersen

Introduction 171

Screening 172

Sabatier Principle 173

Scaling Relations 175

BEP Relationship 176

Volcano Plots 180

Some Rules for Oxide Catalysts 189

Let Us Examine Some Industrial Catalysts 191

Sometimes Selectivity is More Important than Rate 191

Sometimes We Want a Smaller Rate! 191

Sometimes Product Separation is More Important than the Reaction Rate 193

Some Reactions are Equilibrium-limited 193

The Cost of Making the Catalyst is Important 194

The Catalyst Should Contain Abundant Elements 194

A Good Catalyst Should not be Easily Poisoned 195

Summary 195

References 196

5 The Construction of Ab Initio-Based Potential Energy Surfaces 199
Richard Dawes and Ernesto Quintas-Sánchez

Introduction and Overview 199

What is a PES? 199

Significance and Range of Applications of PESs 204

Challenges for Theory 207

Terminology and Concepts 209

The Schrödinger Equation 209

The BO Approximation 210

Mathematical Foundations of (Linear) Fitting 215

Quantum Chemistry Methods 221

General Considerations 221

Single Reference Methods 223

Multireference Methods 225

Compound Methods or Protocols 227

Fitting Methods 229

General Considerations and Desirable Attributes of a PES 229

Non-Interpolative Fitting Methods 231

Interpolative Fitting Methods 239

Applications 242

The Automated Construction of PESs 242

Concluding Remarks 248

Acknowledgements 250

Acronyms/Abbreviations 250

References 251

6 Modeling Mechanochemistry from First Principles 265
Heather J. Kulik

Introduction and Scope 265

Potential Energy Surfaces and Reaction Coordinates 266

Theoretical Models of Mechanochemical Bond Cleavage 268

Linear Model (Kauzmann, Eyring, and Bell) 268

Tilted Potential Energy Profile Model 270

First-Principles Models for Mechanochemical Bond Cleavage 271

Constrained Geometries Simulate External Force (COGEF) 271

Force-Modified Potential Energy Surfaces 273

Covalent Mechanochemistry 278

Overview of Characterization Methods 278

Representative Mechanophores 280

Representative Mechanochemistry Case Studies 281

Benzocyclobutene 281

gem-Difluorocyclopropane 285

PPA: Heterolytic Bond Cleavage 288

Mechanical Force for Sampling: Application to Lignin 292

Best Practices for Mechanochemical Simulation 296

Conclusions 298

Acknowledgments 299

References 300

Index 313

ABBY L. PARRILL, Ph.D., is a Professor in the Department of Chemistry at the University of Memphis, TN. Her research interests are in bioorganic chemistry, protein modeling, and rational ligand design and synthesis.

KENNY B. LIPKOWITZ, Ph.D., was one of the founding co-editors of Reviews in Computational Chemistry. He spent 28 years as an academician and then moved to the Office of Naval Research where he is a Program Manager in Computer-Aided Materials Design.

A VALUABLE REFERENCE TO THE METHODS AND TECHNIQUES IN COMPUTATIONAL CHEMISTRY

Reviews in Computational Chemistry, Volume 31 brings together in one book a collection of writings from noted authorities in the field. Volume 31 is designed for use by both those new to the field and for seasoned researchers to aid them in selecting and applying new computational chemistry methods to their own research problems. The book's tutorial-style chapters provide both mini-tutorials for novices as well as critical literature reviews highlighting advanced applications.

Two themes connect many of the chapters: modeling of soft matter systems such as polymers and proteins and the first principle methods necessary for modeling chemical reactions. The contributors cover a wealth of topics centered on molecular modeling, such as modeling mechanochemical processes and protein internal energy transfer networks, lattice Boltzmann simulations, ab initio potential energy surface construction, catalyst optimization, and uncertainty quantification. This important resource:

• Offers a guide to the both the background and theory and the strategies for using methods correctly
• Includes information on the pitfalls to avoid, applications, and references
• Presents a detailed subject index to help quickly discover particular topics
• Uses a tutorial manner and non-mathematical style, that helps to access computational methods outside one's immediate area of expertise

Written for computational chemists, theoretical chemists, pharmaceutical chemists, biological chemists, chemical engineers, and others. Reviews in Computational Chemistry, Volume 31 is an essential guide to the modeling of soft manner systems and explains the principle methods needed for modeling chemical reactions.