Open AccessBook
Understanding molecular simulation: from algorithms to applications
Daan Frenkel,Berend Smit +1 more
- Vol. 1, pp 1-638
TLDR
Understanding molecular simulation: From Algorithms to Applications explains the physics behind the "recipes" of molecular simulation for materials science as discussed by the authors, and provides a good understanding of the basic principles of simulation.Abstract:
Second and revised edition
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.read more
Citations
More filters
Journal ArticleDOI
Scalable molecular dynamics with NAMD
James C. Phillips,Rosemary Braun,Wei Wang,James C. Gumbart,Emad Tajkhorshid,Elizabeth Villa,Christophe Chipot,Robert D. Skeel,Laxmikant V. Kale,Klaus Schulten +9 more
TL;DR: NAMD as discussed by the authors is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems that scales to hundreds of processors on high-end parallel platforms, as well as tens of processors in low-cost commodity clusters, and also runs on individual desktop and laptop computers.
Journal ArticleDOI
The Amber biomolecular simulation programs
David A. Case,Thomas E. Cheatham,Tom Darden,Holger Gohlke,Ray Luo,Kenneth M. Merz,Alexey V. Onufriev,Carlos Simmerling,Bing Wang,Robert J. Woods +9 more
TL;DR: The development, current features, and some directions for future development of the Amber package of computer programs, which contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates.
Journal ArticleDOI
Carbon Dioxide Capture: Prospects for New Materials
TL;DR: The most recent developments and emerging concepts in CO(2) separations by solvent absorption, chemical and physical adsorption, and membranes, amongst others, will be discussed, with particular attention on progress in the burgeoning field of metal-organic frameworks.
BookDOI
MCMC using Hamiltonian dynamics
TL;DR: In this paper, the authors discuss theoretical and practical aspects of Hamiltonian Monte Carlo, and present some of its variations, including using windows of states for deciding on acceptance or rejection, computing trajectories using fast approximations, tempering during the course of a trajectory to handle isolated modes, and short-cut methods that prevent useless trajectories from taking much computation time.
Journal ArticleDOI
The Atomic Simulation Environment - A Python library for working with atoms
Ask Hjorth Larsen,Ask Hjorth Larsen,Jens Jørgen Mortensen,Jakob Blomqvist,Ivano E. Castelli,Rune Christensen,Marcin Dulak,Jesper Friis,Michael N. Groves,Bjørk Hammer,Cory Hargus,Eric D. Hermes,Paul C. Jennings,Peter Bjerre Jensen,James R. Kermode,John R. Kitchin,Esben L. Kolsbjerg,Joseph Kubal,Kristen Kaasbjerg,Steen Lysgaard,Jon Bergmann Maronsson,Tristan Maxson,Thomas Olsen,Lars Pastewka,Andrew A. Peterson,Carsten Rostgaard,Jakob Schiøtz,Ole Schütt,Mikkel Strange,Kristian Sommer Thygesen,Tejs Vegge,Lasse B. Vilhelmsen,Michael Walter,Zhenhua Zeng,Karsten Wedel Jacobsen +34 more
TL;DR: The atomic simulation environment (ASE) provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.