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Understanding Molecular Simulation: From Algorithms to Applications

Understanding Molecular Simulation: From Algorithms to Applications

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  • More about Understanding Molecular Simulation: From Algorithms to Applications


Understanding Molecular Simulation provides readers with the foundational knowledge to learn about, select, and apply the most appropriate computational techniques to their work. It highlights how physical concepts are used to develop better algorithms and expand the range of applicability of simulations.

Format: Paperback / softback
Length: 679 pages
Publication date: 26 July 2023
Publisher: Elsevier Science & Technology


Understanding Molecular Simulation delves into the realm of molecular simulation, offering a comprehensive perspective from both chemical physics and statistical mechanics. It sheds light on the utilization of physical concepts to enhance algorithms and broaden the scope of simulation applications. This knowledge holds significance for both developers of new code and users of existing simulation packages. Both groups frequently face the challenge of selecting the most suitable computational technique for specific applications.

Understanding Molecular Simulation serves as a valuable resource for readers seeking to acquire a foundational understanding of molecular simulation. It provides a systematic approach to learning about, selecting, and applying the most appropriate simulation tools to their own work. The implementation of simulation methods is presented through pseudocodes, accompanied by practical examples showcased throughout the text. Since the second edition's publication, the simulation world has witnessed significant expansion, with existing techniques continuously evolving and new ones emerging. This new edition aims to provide an overview of these advancements without becoming exhaustive. Examples are included to illustrate current applications, and several new examples have been added to showcase recent applications. Additionally, examples, case studies, questions, and downloadable algorithms are provided to support learning. No prior knowledge of computer simulation is assumed.

Weight: 1170g
Dimension: 156 x 230 x 42 (mm)
ISBN-13: 9780323902922
Edition number: 3 ed

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