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Understanding Molecular Simulation
From Algorithms to Applications
Fully updated edition of this key text that supports those involved with studying, developing or applying molecular simulations
Daan Frenkel (Author), Berend Smit (Author)
9780323902922, Elsevier Science
Paperback / softback, published 18 July 2023
679 pages
22.9 x 15.2 x 4.1 cm, 0.45 kg
From the previous edition: "... this book brilliantly lays down the scientific foundations of the simulational approach ..." --Prof. Kurt Binder in Physics World, 1997 "... a treasure. The book is a marvellous mix of just enough formalism with an informal and readable style, sufficient detail to understand methodological advances, appropriate mathematics ..." --Prof. Mark A. Ratner in Physics Today, 1997
Understanding Molecular Simulation explains molecular simulation from a chemical-physics and statistical-mechanics perspective. It highlights how physical concepts are used to develop better algorithms and expand the range of applicability of simulations. Understanding Molecular Simulation is equally relevant for those who develop new code and those who use existing packages. Both groups are continuously confronted with the question of which computational technique best suits a given application. Understanding Molecular Simulation provides readers with the foundational knowledge they need to learn about, select and apply the most appropriate of these tools to their own work. The implementation of simulation methods is illustrated in pseudocodes, and their practical use is shown via case studies presented throughout the text. Since the second edition’s publication, the simulation world has expanded significantly: existing techniques have continued to develop, and new ones have emerged, opening up novel application areas. This new edition aims to describe these new developments without becoming exhaustive; examples are included that highlight current uses, and several new examples have been added to illustrate recent applications. Examples, case studies, questions, and downloadable algorithms are also included to support learning. No prior knowledge of computer simulation is assumed.
1. Introduction Part I: Basics 2. Thermodynamics and Statistical Mechanics 3. Monte Carlo Simulations 4. Molecular Dynamics Simulations 5. Computer Experiments Part II: Ensembles 6. Monte Carlo Simulations in Various Ensembles 7. Molecular Dynamics in Various Ensembles Part III: Free -Energy Calculations 8. Free Energy Calculations 9. Free Energies of Solids 10. Free Energy of Chain Molecules Part IV: Advanced Techniques 11. Long-Ranged Interactions 12. Configurational Bias Monte Carlo 13. Accelerating Monte Carlo Sampling 14. Time-Scale-separation Problems in MD 15. Rare Events 16. Mesoscopic Fluid Models Part V: Appendices A: Lagrangian and Hamiltonian B: Non-Hamiltonian Dynamics C: Non-equilibrium Thermodynamics D: Smoothed Dissipative Particle Dynamics E: Committor for 1-D diffusive barrier crossing F: Linear Response Theory: examples G: Statistical Errors H: Integration Schemes I: Saving CPU Time J: Reference States K: Statistical Mechanics of the Gibbs "Ensemble" L: Overlapping Distribution for Polymers M: Some General Purpose Algorithms
Subject Areas: Quantum & theoretical chemistry [PNRP]
