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| | Home Understanding Molecular Simulation, Second Edition: From Algorithms to Applications (Computational Science) | |
|  | |  | | | Understanding Molecular Simulation, Second Edition: From Algorithms to Applications (Computational Science) | | | | | SKU:
R2794 | | In Stock | | Availability:
Usually ships in 1 business days | | | | | | Understanding Molecular Simulation: From Algorithms to Applications explains the physics behind the "recipes" of molecular simulation for materials science. Computer simulators are continuously confronted with questions concerning the choice of a particular technique for a given application. A wide variety of tools exist, so the choice of technique requires a good understanding of the basic principles. More importantly, such understanding may greatly improve the efficiency of a simulation program. The implementation of simulation methods is illustrated in pseudocodes and their practical use in the case studies used in the text.
Since the first edition only five years ago, the simulation world has changed significantly -- current techniques have matured and new ones have appeared. This new edition deals with these new developments; in particular, there are sections on:
· Transition path sampling and diffusive barrier crossing to simulaterare events
· Dissipative particle dynamic as a course-grained simulation technique
· Novel schemes to compute the long-ranged forces
· Hamiltonian and non-Hamiltonian dynamics in the context constant-temperature and constant-pressure molecular dynamics simulations
· Multiple-time step algorithms as an alternative for constraints
· Defects in solids
· The pruned-enriched Rosenbluth sampling, recoil-growth, and concerted rotations for complex molecules
· Parallel tempering for glassy Hamiltonians
Examples are included that highlight current applications and the codes of case studies are available on the World Wide Web. Several new examples have been added since the first edition to illustrate recent applications. Questions are included in this new edition. No prior knowledge of computer simulation is assumed. | | | |
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| | Product Details | | Author: | Daan Frenkel | | Hardcover: | 664 pages | | Publisher: | Academic Press | | Publication Date: | November 07, 2001 | | Language: | English | | ISBN: | 0122673514 | | Product Length: | 9.36 inches | | Product Width: | 5.64 inches | | Product Height: | 1.58 inches | | Product Weight: | 2.24 pounds | | Package Length: | 9.1 inches | | Package Width: | 6.3 inches | | Package Height: | 1.6 inches | | Package Weight: | 2.25 pounds | | Average Customer Rating: |  based on 12 reviews |
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| | Customer Reviews | Average Customer Review: ( 12 customer reviews )
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Most Helpful Customer Reviews
22 of 22 found the following review helpful:
 A great book for begginers. May 17, 1999
By saras@servidor.unam.mx
This book covers many interesting topics in molecular simulation, both Monte Carlo and M.D. It focuses on understanding the main ideas rather than giving long codes. It's a good place to start, but it also covers some ideas not found in many other books. When I try to extend my molecular dynamics program I always check what Frenkel and Smit have to say about it.
33 of 36 found the following review helpful:
 A nice disappointment Aug 30, 2001
By Jose R. Valverde Carrillo
"jrvalverde"
The title of the book is overly ambitious and falls short on its promises. The book is a good introduction to Molecular Mechanics (MM), Molecular Dynamics (MD) and Monte Carlo (MC) methods, with detailed descriptions of the methods used and FORTRAN (pseudo)code, covering from the basics to some middle-level and some advanced algorithms.
But it does NOT cover all the fields of Molecular Modelling, just the three mentioned (MM, MD and MC), there's no coverage of quantum mechanics methods, nor QSAR or other technologies. And, while it described the algorithms, I can't think of it going all the way through up to building applications. For this, Rapaport's makes a better job, and for a general intro to Molecular Modelling, Grant & Richards' Computational Chemistry is more comprehensive (albeit at a more superficial level). Nor does it provide much detail on the methods used in modelling biological macromolecules, an increasing application field for the methods discussed in the book.
All in all, this book fails to satisfy its cover title, it won't introduce to the whole field (just the areas of MM, MD and MC) nor does it go up to application level. But it IS a REAL GOOD introduction to the subjects covered and their basic algorithms,
with sample code, detailed descriptions and plenty of references to specialized articles, texts and resources.
20 of 21 found the following review helpful:
Perfect for New Grad Students Nov 24, 2002
By Owen Hehmeyer
This book is how I bootstrapped my way into being a molecular simulationist. Anyone who can program in some language can get started writing simple routines for the basic MD and MC simulations.I do Monte Carlo simulations at Princeton, and found this book to be the most helpful available for getting my research started. It is my most common reference, and is used extensively in writing background information for various research documents. However, after you have written your first few codes, you will pass the level of this book and need to move on. I use it less now than I did my first year. Every student in my group (Panagiotopoulos) has this book I think. And like me, they started with it, but moved on.
8 of 9 found the following review helpful:
Excellent text for beginners in simulation Nov 19, 2004
By Kanishk Rastogi
"Freelenser"
Its an excellent book for those who are just beginners in MC & MD simulations. everything is very clearly explained with lot of examples and some related unsolved problems. the text explores this topic indetails with advanced chapters in later sections. Good for anybody int hsi field be it in materials science, physics or related fields.
3 of 4 found the following review helpful:
 Totally misses the mark, waste of time Jun 08, 2010
By Omega
While the book is a legitimate effort to codify the study of molecular mechanics, etc...I found it to be obtuse and wholly frustrating. I often write programs to solve problems in chemistry and biology, and the underlying tenets that serve me well are ignored in this book. The book has a huge discussion about what other people have done to write Monte Carlo algorithms, for example. But they fail to emphasize the algorithmic nature of the computer program, instead aiming to teach graduate students how to reproduce code that other people have already written. Monte Carlo: works on everything, but good for little if you don't already know the answer.
A good program makes the right assumptions about the problem, and this book fails to communicate this essential balance at the core of molecular modeling: treatment of complexity vs. exhaustiveness of sampling. There is a huge discussion of thermostats, etc. It is like trying to have a friendly debate with a friend who can't let go of the details to agree that the whole discussion is focused on the wrong topic. We write programs to solve problems algorithmically....the focus should be the algorithms, not the programs.
Unfortunately, I can't recommend a good alternative textbook. Rather, there is a wealth of information in journal articles and in the source code of several excellent open source projects. A reader/student would be well-served to identify those articles/projects that are personally most interesting, and study these rather than read this textbook.
See all 12 customer reviews on Amazon.com
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