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Introduction to Computational Chemistry: Methods and Applications: Theoretical and Computational Chemistry

Autor John M. Galbraith, T. Daniel Crawford
en Limba Engleză Paperback – aug 2026
Introduction 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.

  • Provides upper level undergraduate and entry level graduate students with a basic knowledge of computational chemistry methods in a straightforward, non-mathematical format
  • Highlights the best and most useful computational chemistry, showing the reader how to access them, including software repositories, user groups, and online forums
  • Explores the way computational chemists think from historical, ethical, and sociological perspectives
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Specificații

ISBN-13: 9780443299216
ISBN-10: 0443299218
Pagini: 456
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
Seria Theoretical and Computational Chemistry


Cuprins

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