Computational materials science : from Ab Initio to Monte Carlo methods / Kaoru Ohno, Keivan Esfarjani, Yoshiyuki Kawazoe.
2018
TA404.23
Linked e-resources
Linked Resource
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Computational materials science : from Ab Initio to Monte Carlo methods / Kaoru Ohno, Keivan Esfarjani, Yoshiyuki Kawazoe.
Edition
Second edition.
ISBN
9783662565421 (electronic book)
3662565420 (electronic book)
9783662565407
3662565420 (electronic book)
9783662565407
Published
Berlin, Germany : Springer, 2018.
Language
English
Description
1 online resource (xii, 425 pages)
Item Number
10.1007/978-3-662-56542-1 doi
Call Number
TA404.23
Dewey Decimal Classification
620.1/1011
Summary
This textbook introduces modern techniques based on computer simulation to study materials science. It starts from first principles calculations enabling to calculate the physical and chemical properties by solving a many-body Schroedinger equation with Coulomb forces. For the exchange-correlation term, the local density approximation is usually applied. After the introduction of the first principles treatment, tight-binding and classical potential methods are briefly introduced to indicate how one can increase the number of atoms in the system. In the second half of the book, Monte Carlo simulation is discussed in detail. Problems and solutions are provided to facilitate understanding. Readers will gain sufficient knowledge to begin theoretical studies in modern materials research. This second edition includes a lot of recent theoretical techniques in materials research. With the computers power now available, it is possible to use these numerical techniques to study various physical and chemical properties of complex materials from first principles. The new edition also covers empirical methods, such as tight-binding and molecular dynamics. .
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed April 16, 2018).
Linked Resources
Record Appears in
Table of Contents
Ab-Initio Methods
Tight-Binding Methods
Empirical Methods and Coarse-Graining
Monte Carlo Methods
Quantum Monte Carlo (QMC) Methods.
Tight-Binding Methods
Empirical Methods and Coarse-Graining
Monte Carlo Methods
Quantum Monte Carlo (QMC) Methods.