Autorentext

John M. Galbraith is a Computational Chemist with more than 30 years' experience in molecular orbital and valence bond theory calculations of small molecules. He has 20+ years teaching undergraduate courses in Computational, Physical, Inorganic, and General Chemistry. He is currently an Associate Professor of Chemistry at the Department of Chemistry, Biochemistry, and Physics, Marist University, USA. T. Daniel Crawford is University Distinguished Professor of Chemistry at Virginia Tech, USA and the Director of the Molecular Sciences Software Institute in Blacksburg, Virginia. He received his bachelor's degree in 1992 from Duke University and his Ph.D. in 1996 from the University of Georgia, working with Prof. Fritz Schaefer. His research focuses on quantum chemical models of molecular properties, particularly the spectroscopic responses of chiral compounds. He is a Fellow of the American Chemical Society and the winner of 2010 Dirac Medal of the World Association of Theoretical and Computational Chemists.

Klappentext

A Beginner's Guide to Computational Chemistry: Methods and Applications provides a basic discussion of computer functionality through operating systems, system administration, and programming followed by a look at key computational methods for electronic structure methods and molecular mechanics, hybrid methods, and solid-state materials. For each topic, essential non-mathematical information is provided so readers can immediately begin to effectively use computational chemistry software. Sections quickly present essential information regarding the fundamental approaches and applications in a down to earth and uncluttered manner.

This book is ideal for is upper level undergraduate and entry level graduate students completely new to the field of computational chemistry, and those with little background knowledge. It is well-suited to entry level courses at this level.

Inhalt

Section I. Computers

1. System administration and operating systems
2. Math Packages
3. Programming

Section II. Electronic Structure Methods
4. Basis sets
5. Molecular Orbital Methods
6. Valence Bond Methods
7. Density Functional Methods
8. Semi-empirical methods
9. Applications
10. Data analysis

Section III. Molecular Mechanics Methods
11. Force Field models
12. Applications

Section IV. Hybrid Methods
13. QM/MM
14. Empirical Valence Bond Methods

Section V. Solids and Surfaces:
15. Periodic systems
16. Applications

Section VI. Simulation Techniques
17. Molecular Dynamics Methods
18. Monte Carlo Methods
19. Applications

Section VII. Large Data Sets
20. Machine Learning

Section VIII. Resources
21. MolSSI
22. Computer resources
23. Software resources