Skip to content

Understanding Molecular Simulation From Algorithms to Applications

Best in textbook rentals since 2012!

ISBN-10: 0122673514

ISBN-13: 9780122673511

Edition: 2nd 2002 (Revised)

Authors: Daan Frenkel, Berend Smit

List price: $106.00
Shipping box This item qualifies for FREE shipping.
Blue ribbon 30 day, 100% satisfaction guarantee!
what's this?
Rush Rewards U
Members Receive:
Carrot Coin icon
XP icon
You have reached 400 XP and carrot coins. That is the daily max!


Providing a unified presentation of computational tools used to study molecular systems, this book explains the physics behind the recipes of molecular simulation for materials science.
Customers also bought

Book details

List price: $106.00
Edition: 2nd
Copyright year: 2002
Publisher: Elsevier Science & Technology
Publication date: 10/19/2001
Binding: Hardcover
Pages: 664
Size: 6.00" wide x 9.00" long x 1.50" tall
Weight: 1.914

Professor Emeritus Geoffrey A. Cordell obtained his Ph.D. in synthetic natural product chemistry at the University of Manchester in 1970. After two years as a NATO postdoctoral fellow at the Department of Chemistry, M.I.T., he joined the College of Pharmacy, University of Illinois at Chicago (UIC). A Professor since 1980, he served as a Department Head for 12 years and as Interim Dean of the College of Pharmacy for almost three years, as well as holding several other senior academic and research administrative positions at the Department, College, and Campus levels. He was the Co-founder of the US - Thai Consortium for Pharmacy Education, which developed and trained faculty for six new…    

Berend Smit is Professor at the Department of Chemical Engineering of the Faculty of Science, University of Amsterdam. His research focuses on novel Monte Carlo simulations. Smit applies this technique to problems that are of technological importance, particularly those of interest in chemical engineering.

Preface to the Second Edition
List of Symbols
Statistical Mechanics
Entropy and Temperature
Classical Statistical Mechanics
Questions and Exercises
Monte Carlo Simulations
The Monte Carlo Method
Importance Sampling
The Metropolis Method
A Basic Monte Carlo Algorithm
The Algorithm
Technical Details
Detailed Balance versus Balance
Trial Moves
Translational Moves
Orientational Moves
Questions and Exercises
Molecular Dynamics Simulations
Molecular Dynamics: The Idea
Molecular Dynamics: A Program
The Force Calculation
Integrating the Equations of Motion
Equations of Motion
Other Algorithms
Higher-Order Schemes
Liouville Formulation of Time-Reversible Algorithms
Lyapunov Instability
One More Way to Look at the Verlet Algorithm
Computer Experiments
Order-n Algorithm to Measure Correlations
Some Applications
Questions and Exercises
Monte Carlo Simulations in Various Ensembles
General Approach
Canonical Ensemble
Monte Carlo Simulations
Justification of the Algorithm
Microcanonical Monte Carlo
Isobaric-Isothermal Ensemble
Statistical Mechanical Basis
Monte Carlo Simulations
Isotension-Isothermal Ensemble
Grand-Canonical Ensemble
Statistical Mechanical Basis
Monte Carlo Simulations
Justification of the Algorithm
Questions and Exercises
Molecular Dynamics in Various Ensembles
Molecular Dynamics at Constant Temperature
The Andersen Thermostat
Nose-Hoover Thermostat
Nose-Hoover Chains
Molecular Dynamics at Constant Pressure
Questions and Exercises
Free Energies and Phase Equilibria
Free Energy Calculations
Thermodynamic Integration
Chemical Potentials
The Particle Insertion Method
Other Ensembles
Overlapping Distribution Method
Other Free Energy Methods
Multiple Histograms
Acceptance Ratio Method
Umbrella Sampling
Nonequilibrium Free Energy Methods
Questions and Exercises
The Gibbs Ensemble
The Gibbs Ensemble Technique
The Partition Function
Monte Carlo Simulations
Particle Displacement
Volume Change
Particle Exchange
Analyzing the Results
Questions and Exercises
Other Methods to Study Coexistence
Semigrand Ensemble
Tracing Coexistence Curves
Free Energies of Solids
Thermodynamic Integration
Free Energies of Solids
Atomic Solids with Continuous Potentials
Free Energies of Molecular Solids
Atomic Solids with Discontinuous Potentials
General Implementation Issues
Vacancies and Interstitials
Free Energies
Numerical Calculations
Free Energy of Chain Molecules
Chemical Potential as Reversible Work
Rosenbluth Sampling
Macromolecules with Discrete Conformations
Extension to Continuously Deformable Molecules
Overlapping Distribution Rosenbluth Method
Recursive Sampling
Pruned-Enriched Rosenbluth Method
Advanced Techniques
Long-Range Interactions
Ewald Sums
Point Charges
Dipolar Particles
Dielectric Constant
Boundary Conditions
Accuracy and Computational Complexity
Fast Multipole Method
Particle Mesh Approaches
Ewald Summation in a Slab Geometry
Biased Monte Carlo Schemes
Biased Sampling Techniques
Beyond Metropolis
Orientational Bias
Chain Molecules
Configurational-Bias Monte Carlo
Lattice Models
Off-lattice Case
Generation of Trial Orientations
Strong Intramolecular Interactions
Generation of Branched Molecules
Fixed Endpoints
Lattice Models
Fully Flexible Chain
Strong Intramolecular Interactions
Rebridging Monte Carlo
Beyond Polymers
Other Ensembles
Grand-Canonical Ensemble
Gibbs Ensemble Simulations
Recoil Growth
Justification of the Method
Questions and Exercises
Accelerating Monte Carlo Sampling
Parallel Tempering
Hybrid Monte Carlo
Cluster Moves
Early Rejection Scheme
Tackling Time-Scale Problems
Constrained and Unconstrained Averages
On-the-Fly Optimization: Car-Parrinello Approach
Multiple Time Steps
Rare Events
Theoretical Background
Bennett-Chandler Approach
Computational Aspects
Diffusive Barrier Crossing
Transition Path Ensemble
Path Ensemble
Monte Carlo Simulations
Searching for the Saddle Point
Dissipative Particle Dynamics
Description of the Technique
Justification of the Method
Implementation of the Method
DPD and Energy Conservation
Other Coarse-Grained Techniques
Lagrangian and Hamiltonian
Hamilton Dynamics and Statistical Mechanics
Canonical Transformation
Symplectic Condition
Statistical Mechanics
Non-Hamiltonian Dynamics
Theoretical Background
Non-Hamiltonian Simulation of the N, V, T Ensemble
The Nose-Hoover Algorithm
Nose-Hoover Chains
The N, P, T Ensemble
Linear Response Theory
Static Response
Dynamic Response
Electrical Conductivity
Elastic Constants
Statistical Errors
Static Properties: System Size
Correlation Functions
Block Averages
Integration Schemes
Higher-Order Schemes
Nose-Hoover Algorithms
Canonical Ensemble
The Isothermal-Isobaric Ensemble
Saving CPU Time
Verlet List
Cell Lists
Combining the Verlet and Cell Lists
Reference States
Grand-Canonical Ensemble Simulation
Statistical Mechanics of the Gibbs "Ensemble"
Free Energy of the Gibbs Ensemble
Basic Definitions
Free Energy Density
Chemical Potential in the Gibbs Ensemble
Overlapping Distribution for Polymers
Some General Purpose Algorithms
Small Research Projects
Adsorption in Porous Media
Transport Properties in Liquids
Diffusion in a Porous Media
Multiple-Time-Step Integrators
Thermodynamic Integration
Hints for Programming
Author Index