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Computer simulation of liquids / Michael P. Allen, Dominic J. Tildesley

Allen, Michael P.
Contributor(s): Tildesley, Dominic J.
Material type: materialTypeLabelBook; Format: print Publisher: Oxford, United Kingdom : Oxford University Press, 2017Edition: Second edition.Description: xiv, 626 pages : illustrations ; 25 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9780198803201 (pbk.).Subject(s): Líquidos -- Modelos matemáticos | Líquidos -- Procesamiento de datos | Dinámica molecular | Liquids -- Mathematical models | Liquids -- Data processing | Molecular dynamics | Monte Carlo method
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Manuales (7 días) 02. BIBLIOTECA CAMPUS PUERTO REAL
532/ALL/com (Browse shelf)   Shelving location | Bibliomaps® BIBLIOG. RECOM. 3744565697

QUÍMICA FÍSICA II GRADO EN QUÍMICA Asignatura actualizada 2017-2018

Monografías 02. BIBLIOTECA CAMPUS PUERTO REAL
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Enhanced descriptions from Syndetics:

This book provides a practical guide to molecular dynamics and Monte Carlo simulation techniques used in the modelling of simple and complex liquids. Computer simulation is an essential tool in studying the chemistry and physics of condensed matter, complementing and reinforcing bothexperiment and theory. Simulations provide detailed information about structure and dynamics, essential to understand the many fluid systems that play a key role in our daily lives: polymers, gels, colloidal suspensions, liquid crystals, biological membranes, and glasses. The second edition of thispioneering book aims to explain how simulation programs work, how to use them, and how to interpret the results, with examples of the latest research in this rapidly evolving field. Accompanying programs in Fortran and Python provide practical, hands-on, illustrations of the ideas in thetext.

Includes bibliographical references (pages 536-621) and index.

Table of contents provided by Syndetics

  • 1 Introduction (p. 1)
  • 1.1 A short history of computer simulation (p. 1)
  • 1.2 Computer simulation: motivation and applications (p. 4)
  • 1.3 Model systems and interaction potentials (p. 5)
  • 1.4 Constructing an intermolecular potential from first principles (p. 25)
  • 1.5 Force fields (p. 29)
  • 1.6 Studying small systems (p. 35)
  • 2 Statistical mechanics (p. 46)
  • 2.1 Sampling from ensembles (p. 46)
  • 2.2 Common statistical ensembles (p. 52)
  • 2.3 Transforming between ensembles (p. 58)
  • 2.4 Simple thermodynamic averages (p. 60)
  • 2.5 Fluctuations (p. 66)
  • 2.6 Structural quantities (p. 69)
  • 2.7 Time correlation functions and transport coefficients (p. 73)
  • 2.8 Long-range corrections (p. 79)
  • 2.9 Quantum corrections (p. 81)
  • 2.10 Constraints (p. 83)
  • 2.11 Landau free energy (p. 85)
  • 2.12 Inhomogeneous systems (p. 86)
  • 2.13 Fluid membranes (p. 90)
  • 2.14 Liquid crystals (p. 92)
  • 3 Molecular dynamics (p. 95)
  • 3.1 Equations of motion for atomic systems (p. 95)
  • 3.2 Finite-difference methods (p. 97)
  • 3.3 Molecular dynamics of rigid non-spherical bodies (p. 106)
  • 3.4 Constraint dynamics (p. 113)
  • 3.5 Multiple-timestep algorithms (p. 120)
  • 3.6 Checks on accuracy (p. 121)
  • 3.7 Molecular dynamics of hard particles (p. 125)
  • 3.8 Constant-temperature molecular dynamics (p. 130)
  • 3.9 Constant-pressure molecular dynamics (p. 140)
  • 3.10 Grand canonical molecular dynamics (p. 144)
  • 3.11 Molecular dynamics of polarizable systems (p. 145)
  • 4 Monte Carlo methods (p. 147)
  • 4.1 Introduction (p. 147)
  • 4.2 Monte Carlo integration (p. 147)
  • 4.3 Importance sampling (p. 151)
  • 4.4 The Metropolis method (p. 155)
  • 4.5 Isothermal-isobaric Monte Carlo (p. 160)
  • 4.6 Grand canonical Monte Carlo (p. 164)
  • 4.7 Semi-grand Monte Carlo (p. 168)
  • 4.8 Molecular liquids (p. 169)
  • 4.9 Parallel tempering (p. 177)
  • 4.10 Other ensembles (p. 183)
  • 5 Some tricks of the trade (p. 185)
  • 5.1 Introduction (p. 185)
  • 5.2 The heart of the matter (p. 185)
  • 5.3 Neighbour lists (p. 193)
  • 5.4 Non-bonded interactions and multiple timesteps (p. 200)
  • 5.5 When the dust has settled (p. 201)
  • 5.6 Starting up (p. 204)
  • 5.7 Organization of the simulation (p. 210)
  • 5.8 Checks on self-consistency (p. 214)
  • 6 Long-range forces (p. 216)
  • 6.1 Introduction (p. 216)
  • 6.2 The Ewald sum (p. 217)
  • 6.3 The particle-particle particle-mesh method (p. 224)
  • 6.4 Spherical truncation (p. 231)
  • 6.5 Reaction field (p. 235)
  • 6.6 Fast multipole methods (p. 239)
  • 6.7 The multilevel summation methods (p. 243)
  • 6.8 Maxwell equation molecular dynamics (p. 247)
  • 6.9 Long-range potentials in slab geometry (p. 250)
  • 6.10 Which scheme to use? (p. 254)
  • 7 Parallel simulation (p. 258)
  • 7.1 Introduction (p. 258)
  • 7.2 Parallel loops (p. 260)
  • 7.3 Parallel replica exchange (p. 262)
  • 7.4 Parallel domain decomposition (p. 265)
  • 7.5 Parallel constraints (p. 269)
  • 8 How to analyse the results (p. 271)
  • 8.1 Introduction (p. 271)
  • 8.2 Liquid structure (p. 272)
  • 8.3 Time correlation functions (p. 274)
  • 8.4 Estimating errors (p. 281)
  • 8.5 Correcting the results (p. 289)
  • 9 Advanced Monte Carlo methods (p. 297)
  • 9.1 Introduction (p. 297)
  • 9.2 Estimation of the free energy (p. 298)
  • 9.3 Smarter Monte Carlo (p. 317)
  • 9.4 Simulation of phase equilibria (p. 333)
  • 9.5 Reactive Monte Carlo (p. 338)
  • 10 Rare event simulation (p. 342)
  • 10.1 Introduction (p. 342)
  • 10.2 Transition state approximation (p. 343)
  • 10.3 Bennett-Chandler approach (p. 345)
  • 10.4 Identifying reaction coordinates and paths (p. 346)
  • 10.5 Transition path sampling (p. 347)
  • 10.6 Forward flux and transition interface sampling (p. 350)
  • 10.7 Conclusions (p. 354)
  • 11 Nonequilibrium molecular dynamics (p. 355)
  • 11.1 Introduction (p. 355)
  • 11.2 Spatially oscillating perturbations (p. 357)
  • 11.3 Spatially homogeneous perturbations (p. 361)
  • 11.4 Inhomogeneous systems (p. 370)
  • 11.5 Flow in confined geometry (p. 371)
  • 11.6 Nonequilibrium free-energy measurements (p. 376)
  • 11.7 Pracical points (p. 379)
  • 11.8 Conclusions (p. 381)
  • 12 Mesoscale methods (p. 382)
  • 12.1 Introduction (p. 382)
  • 12.2 Langevin and Brownian dynamics (p. 383)
  • 12.3 Brownian dynamics, molecular dynamics, and Monte Carlo (p. 387)
  • 12.4 Dissipative particle dynamics (p. 390)
  • 12.5 Multiparticle collision dynamics (p. 392)
  • 12.6 The lattice-Boltzmann method (p. 394)
  • 12.7 Developing coarse-grained potentials (p. 397)
  • 13 Quantum simulations (p. 406)
  • 13.1 Introduction (p. 406)
  • 13.2 Ab-initio molecular dynamics (p. 408)
  • 13.3 Combining quantum and classical force-field simulations (p. 420)
  • 13.4 Path-integral simulations (p. 426)
  • 13.5 Quantum random walk simulations (p. 437)
  • 13.6 Over our horizon (p. 442)
  • 14 Inhomogeneous fluids (p. 446)
  • 14.1 The planar gas-liquid interface (p. 446)
  • 14.2 The gas-liquid interface of a molecular fluid (p. 462)
  • 14.3 The liquid-liquid interface (p. 464)
  • 14.4 The solid-liquid interface (p. 464)
  • 14.5 The liquid drop (p. 469)
  • 14.6 Fluid membranes (p. 475)
  • 14.7 Liquid crystals (p. 479)
  • Appendix A Computers and computer simulation (p. 481)
  • A.1 Computer hardware (p. 481)
  • A.2 Programming languages (p. 482)
  • A.3 Fortran programming considerations (p. 483)
  • Appendix B Reduced units (p. 487)
  • B.1 Reduced units (p. 487)
  • Appendix C Calculation of forces and torques (p. 491)
  • C.1 Introduction (p. 491)
  • C.2 The polymer chain (p. 491)
  • C.3 The molecular fluid with multipoles (p. 494)
  • C.4 The triple-dipole potential (p. 496)
  • C.5 Charged particles using Ewald sum (p. 497)
  • C.6 The Gay-Berne potential (p. 498)
  • C.7 Numerically testing forces and torques (p. 500)
  • Appendix D Fourier transforms and series (p. 501)
  • D.1 The Fourier transform (p. 501)
  • D.2 Spatial Fourier transforms and series (p. 502)
  • D.3 The discrete Fourier transform (p. 504)
  • D.4 Numerical Fourier transforms (p. 505)
  • Appendix E Random numbers (p. 509)
  • E.1 Random number generators (p. 509)
  • E.2 Uniformly distributed random numbers (p. 510)
  • E.3 Generating non-uniform distributions (p. 511)
  • E.4 Random vectors on the surface of a sphere (p. 514)
  • E.5 Choosing randomly and uniformly from complicated regions (p. 515)
  • E.6 Generating a random permutation (p. 516)
  • Appendix F Configurational temperature (p. 517)
  • F.1 Expression for configurational temperature (p. 517)
  • F.2 Implementation details (p. 517)
  • List of Acronyms (p. 521)
  • List of Greek Symbols (p. 527)
  • List of Roman Symbols (p. 529)
  • List of Examples (p. 533)
  • List of Codes (p. 534)
  • Bibliography (p. 536)
  • Index (p. 622)

Author notes provided by Syndetics

Michael P. Allen is Emeritus Professor at the University of Warwick and a Visiting Fellow at the University of Bristol.
Dominic J. Tildesley is Director of the Centre Europen de Calcul Atomique et Molculaire (CECAM), EPFL, Switzerland and Titulaire Professor of Chemistry at the cole Polytechnique Fdrale de Lausanne.

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