Reviews in Computational Chemistry, Volume 31

  • ID: 4536033
  • Book
  • 352 Pages
  • John Wiley and Sons Ltd
1 of 4

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 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 the methods correctly
  • Includes information on the pitfalls to avoid, applications, and references
  • Contains updated and comprehensive compendiums of molecular modeling software
  • Presents detailed indices 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.

Note: Product cover images may vary from those shown
2 of 4

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


The Lattice Boltzmann Equation: A Modern Introduction

A Brief History of the Lattice Boltzmann Method

The Lattice Boltzmann Equation

Continuum Kinetic Theory

Discrete Velocity Models

Space–Time Discretization

Common Lattice Boltzman Models

Parameter Choice in Lattice Boltzmann Simulations

The Fluctuating Lattice Boltzmann Equation

Boundary Conditions

Fluid–Particle Coupling

LBM for Multiphase Fluids

Governing Continuum Equations

Lattice Boltzmann Algorithm for Binary Fluid: A Free Energy Approach

Minimizing Spurious Velocities



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


Thermal and Energy Flow in Macromolecules

Normal Modes of Proteins

Simulating Energy Transport in Terms of Normal Modes

Energy Diffusion in Terms of Normal Modes

Energy Transport from Time Correlation Functions

Energy Transport in Proteins is Inherently Anisotropic

Locating Energy Transport Networks

Communication Maps

Current calculations for Proteins (CURP)


Communication Maps: Illustrative Examples

CURP: Illustrative Examples

Future Directions




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


From Dynamical to Random: Overview of MD

System Specification

Inter–atomic Potentials

Hamilton s Equations

Thermodynamic Ensembles

Uncertainty Quantification

What is UQ?

Tools for Uncertainty Quantification

Maximum Likelihood Estimation

Spectral Approach to Non–Parametric Inference

Uncertainty Propagation

UQ of MD

Tutorial: Trajectory Analysis


Tutorial: Ensemble Verification

Background and Main Ideas

Example: Application to Water Simulations

Tutorial: UQ of Data Analysis for the Glass–Transition Temperature

Background and Underlying Ideas

Simulations and Tg Estimates

Within–uncertainty Estimate for Tg

Between Uncertainty and Weighted–Mean Averages

Concluding Thoughts


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



Sabatier Principle

Scaling Relations

Brønstead–Evans–Polanyi Relationship

Volcano Plots

Some Rules for Oxide Catalysts

Let us Examine Some Industrial Catalysts

Sometimes Selectivity is More Important than Rate

Sometimes We Want a Smaller Rate!

Sometimes Product Separation is More Important than Reaction Rate

Some Reactions are Equilibrium–Limited

The Cost of Making the Catalyst is Important

The Catalyst Should Contain Abundant Elements

A Good Catalyst Should Not be Easily Poisoned



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

Introduction and Overview

What is a PES?

Scope of This Review

Significance and Range of Applications of PESs

Challenges for Theory

Terminology and Fundamental Concepts

The Schrödinger Equation

The Born–Oppenheimer Approximation

Mathematical Foundations of (Linear) Fitting

Moving Least Squares Fitting

IMLS Method

L–IMLS Method

Quantum Chemistry Methods

General Considerations

Single Reference Methods

Multireference Methods

Compound Methods or Protocols

Fitting Methods

General Considerations and Desirable Attributes of a PES

Non–Interpolative Fitting Methods

Interpolative Fitting Methods


The Automated Construction of PESs

Concluding Remarks


List of References

6. Modeling Mechanochemistry from First Principles
Heather J. Kulik

Introduction and Scope

Potential Energy Surfaces and Reaction Coordinates

Theoretical Models of Mechanochemical Bond Cleavage

Linear Model (Kauzmann, Eyring, and Bell)

Tilted Energy Profile Model

First–Principles Models for Mechanochemical Bond Cleavage

Constrained Geometries Simulate External Force (COGEF)

Force–Modified Potential Energy Surfaces

Covalent Mechanochemistry

Overview of Characterization Methods

Representative Mechanophores

Representative Mechanochemistry Case Studies



PPA: Heterolytic Bond Cleavage

Mechanical Force for Sampling: Application to Lignin

Best Practices for Mechanochemical Simulation





Subject Index

Note: Product cover images may vary from those shown
3 of 4


4 of 4

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 rational ligand design and synthesis.

Kenny B. Lipkowitz, PhD, 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.

Note: Product cover images may vary from those shown
5 of 4
Note: Product cover images may vary from those shown