# Computational Materials Science : An Introduction

₹695.00

- Author: June Gunn Lee
- Publisher: Taylor & Francis
- ISBN-13: 9781439836163
- Pages: 304
- Binding: Hard Binding
- Year of Pub / Reprint Year: 2015

## Description

**About The Book**

Computational Materials Science: An Introduction covers the essentials of computational science and explains how computational tools and techniques work to help solve materials science problems. The book focuses on two levels of a materials system: the electronic structure level of nuclei and electrons and the atomistic/molecular level. It presents computational treatments of these system levels using molecular dynamics (MD) and first-principles methods, since they are most relevant in materials science and engineering.

After a general overview of computational science, the text introduces MD methods based on classical mechanics and covers their implementation with run examples of XMD and LAMMPS. The author discusses first-principles methods based on quantum mechanics at an introductory level, using illustrations and analogies to assist students in understanding this difficult subject. The book then describes the density functional theory (DFT)—the first-principles method that can handle materials practically. It also reveals how each orbital of electron leads to particular properties of solids, such as total energy, band structure, and barrier energy. The final chapter implements the DFT into actual calculations with various run examples via the VASP program.

Computational methods are contributing more than ever to the development of advanced materials and new applications. For students and newcomers to computational science, this text shows how computational science can be used as a tool for solving materials problems. Further reading sections provide students with more advanced references.

**The Of Contents**

Introduction

Computational materials science

Methods in computational materials science

Computers

Molecular Dynamics**
**Introduction

Potentials

Solutions for Newton’s equations of motion

Initialization

Integration/equilibration

Data production

MD Exercises with XMD and LAMMPS**
**Potential curve of Al

Melting of Ni cluster

Sintering of Ni nanoparticles

Speed distribution of Ar gas: A computer experiment

SiC deposition on Si(001)

Yield mechanism of Au nanowire

Nanodroplet of water wrapped by graphene nanoribbon

First-Principles Methods**
**Quantum mechanics: The beginning

Schrödinger’s wave equation

Early first-principles calculations

Density Functional Theory**
**Introduction

Kohn–Sham approach

Kohn–Sham equations

Exchange-correlation functional

Solving Kohn–Sham equations

DFT extensions and limitations

Treating Solids**
**Pseudopotential approach

Reducing the calculation size

Bloch theorem

Plane-wave expansions

Some practical topics

Practical algorithms for DFT runs

DFT Exercises with VASP**
**VASP

Pt-atom

Pt-FCC

Convergence tests

Pt-bulk

Pt(111)-surface

Nudged elastic band method

Pt(111)-catalyst

Band structure of silicon

Phonon calculation for silicon

Appendix 1: List of symbols and abbreviations

Appendix 2: Linux basic commands

Appendix 3: Convenient scripts

Appendix 4: The Greek alphabet

Appendix 5: SI prefixes

Appendix 6: Atomic units

Index

**Salient Features**

- Provides a much-needed practical introduction to computational science for nonspecialist materials science students and engineers
- Employs XMD, LAMMPS, and VASP, the most frequently used computer programs in the field
- Offers the option of conducting lectures and running exercises simultaneously
- Includes exercises with XMD that can be carried out on PCs as well as exercises with LAMMPS and VASP that can be implemented on any mini-supercomputer via remote access from the classroom
- Contains numerous worked examples, references, and homework problems

**About The Author**

June Gunn Lee is an emeritus research fellow in the Computational Science Center at the Korea Institute of Science and Technology, where he has worked for 28 years. He has published roughly 70 papers on engineering ceramics and computational materials science. He earned a Ph.D. in materials science and engineering from the University of Utah.