Essentials of Computational Chemistry : Theories and Models [0470091827]

Essentials of Computational Chemistry : Theories and Models

Essentials of Computational Chemistry: Theories and Models
By Christopher J. Cramer

* Publisher: Wiley
* Number Of Pages: 618
* Publication Date: 2004-11-15
* ISBN-10 / ASIN: 0470091827
* ISBN-13 / EAN: 9780470091821
* Binding: Paperback

Book Description:

Essentials of Computational Chemistry provides a balanced introduction to this dynamic subject. Suitable for both experimentalists and theorists, a wide range of samples and applications are included drawn from all key areas. The book carefully leads the reader thorough the necessary equations providing information explanations and reasoning where necessary and firmly placing each equation in context.

Summary: Great conceptual books
Rating: 5

It is a good book to start with for computational chemistry. It covers the concepts and suitable for newbies. However, you need a better book if you are looking how to apply the concepts into computational software.

Summary: Great primer for students and faculty alike
Rating: 5

This summer one undergraduate and I made my first research foray into computation chemistry. This book from one of the best names in the field was a useful and approachable primer to the uninitiated, but also had sufficient depth to be meaningful to a broad audience. The student took this book as a springboard and reference into the primary literature and her own research, and was able to work independently - I finally have the book back for a long enough amount of time to get to read a lot of it for myself! We're writing our first computational communication this fall, so obviously we learned what we're doing!

Summary: Excellent treatise
Rating: 4

This book is a follow-up to a previous release and is a great textbook for learning how to simulate atoms, molecules, and fluid mixtures using a variety of techniques. Its positive attributes includes the following:

1. The author makes it a point to explain the various phrases, acronyms, and terms common in the field, but which may confuse the novice or outsider. For example, the first chapter explains the concept of a potential energy surface, how it can be obtained, and the information that can be gleaned from it. These are simple concepts to those experienced in atomistic modeling but can be mysterious to newcomers.

2. The mathematics in the text are simple enough to be understood without the reader having to resort to proving things herself, but they are complete enough to understand how physical concepts are represented and solved. The equations are also set apart from the text such that they are easy to read.

3. There are a lot of diagrammatic figures that explain what is going on; i.e. how atoms interact via certain empirical potentials. One can also tell that the figures were made specifically to teach a concept, and are not reproductions from a publication.

4. The text is appropriate for first-year graduate students in physics, engineering, and chemistry, and the book provides chapters dedicated to quantum mechanics and thermodynamics, the two topics science and engineering students have the most difficulty in.

5. The case study at the end of each chapter are well laid out and do a good job of illustrating the concepts taught in that chapter.

6. There are a lot of flowcharts that show the process by which a calculation is carried out. See for example the appendix on determining the point symmetry of a molecule. Flowcharts are essentiall to understanding how software works, and is probably the biggest difference between computer science and all the other sciences. Computers execute instructions and programmers use flowcharts to decide how a software is put together. Classes and books in the other science and engineering majors are often devoid of flowcharts, so the use of flowcharts in this book helps the reader get into the computational mindset.

7. The list of references at the end of each chapter are primarily to review articles and articles that introduced important concepts. This provides the reader alternate sources of learning. Gone are long lists of case studies and published data.

With so many pluses, why did I give four stars instead of five? Four reasons mainly.

A. There is almost no coverage of the algorithms used to do the mathematics, whether it be diagonalizing the Hamiltonian, or an Ewald summation of interatomic potentials. For example, I do not recall reading anything about the conjugate gradient method anywhere in the book, yet this algorithm is coded into most major codes in computational chemistry like VASP, SIESTA, ADF, etc...

B. There was minimal discussion of techniques for modeling solids. There were chapters dedicated to modeling gases and liquids, but nothing on solids. This is especially disheartening considering that most of the funded chemistry (theoretical and experimental) going on today involves solids; whether it is designing new polymers, hydrogen storage for fuel cells, or examining surface catalysis.

C. A lot of the research going on today in chemistry is in the properties of surfaces and interfaces. Yet there is little mention on modeling of the concepts related to this; such as surface and interface energy, interface lattice msimatch, symmetry of slabs, etc...

D. The book emphasizes the theories behind doing a calculation, such as the Hartree-Fock method, DFT, force fields, etc.. But there is only some mention on the data that can be generated by a simulation software, and how to use them. The examples I can recall are bond orders, population analysis, radial distribution function, and charge density. Other items that should have been included include density of states (vibrational and electronic), electron localization function, and optical properties such as refractive index or dielectric constant.

Overall, it is still a great book and one worth reading.

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