## Understanding Molecular Simulation: From Algorithms to ApplicationsUnderstanding 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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"Understanding Molecular Simulation : From Algorithm to Applications" - a nice option to enrich your knowledge in the field of computational physics and computational chemistry, although, some people may suggest the book by allen and tildesley as the first guide. The algorithms are discussed in proper way with illustrations as support. If you are motivated in research in the field of computational soft matter, this book need to be racked in your library.

### Contents

1 | |

7 | |

Ensembles | 109 |

Free Energies and Phase Equilibria | 165 |

Advanced Techniques | 289 |

Appendices | 479 |

589 | |

619 | |

628 | |

### Common terms and phrases

¹ ½ ½¼ ¼µ acc´Ó Òµ acceptance rule Æ ½ algorithm atoms Boltzmann bond calculation canonical ensemble CBMC center of mass chemical potential coefficient coexistence computer simulation configuration conformation consider constant constraints coordinates crystal denote density derive detailed balance distribution enddo ensemble simulation equations of motion equilibrium Ewald summation example Figure free energy Gibbs ensemble given grand-canonical Hamiltonian hard spheres Hence ideal gas integration interactions intermolecular Ìµ Lagrangian lattice Lennard-Jones fluid liquid method Molecular Dynamics Molecular Dynamics simulations monomer Monte Carlo method Monte Carlo scheme Monte Carlo simulations Nos´e-Hoover number of particles Øµ parallel tempering partition function phase space Phys polymer potential energy pressure probability random Rosenbluth factor sampling segment statistical step subroutine technique temperature thermodynamic tion total energy total number trajectory trial move trial orientations trial position velocity Verlet algorithm Verlet list