The art of molecular dynamics simulation rapaport djvu

Language: English Summary: The extremely powerful technique of molecular dynamics simulation involves solving the classical many-body problem in contexts relevant to the study of matter at the atomistic level.

Since there is no alternative approach capable of handling this extremely broad range of problems at the required level of detail, molecular dynamics methods have proved themselves indispensable in both pure and applied research. Classical MD can be used to study systems with up to millions of atoms but cannot simulate phenomena that depend on electron behavior.

We will restrict our discussion to classical MD. The name molecular dynamics is misleading because given the almost universal nature of the many-body problem, MD can model any system that involves interaction between particles. MD is employed in materials science to study a variety of phenomena, including the behavior of materials under stress, crack propagation, and how various defects affect the strength of materials.

MD is also commonly used in biochemistry to study the behavior of macromolecules. The techniques of MD have also been generalized to thermal science and astrophysics, where particle models are used to study various hydrodynamic instabilities and phase transitions in thermal science and the structure of the universe in astrophysics. The computation of interactions between atoms is typically the most computationally expensive segment of a MD simulation.

For a pair-wise potential a potential described by a potential function that does not account for the environment of atoms , the interaction computations scale with order O N 2. Various methods have been developed that reduce the order to O N for short-range potentials potentials that decay faster with respect to distance than the dimension of the system are considered short-range and O NlogN for long-range potentials. The most common methods are the linked-cell and neighbor list methods for short range potentials and Ewald summation method for long-range potentials.

Both the linked-cell and neighbor-list method assume that the potential and its spatial derivative at the location of an atom can be approximated by the superposition of the potential contributions from atoms within a certain interaction cutoff distance. But to compute the distance between every atom pair costs O N 2 calculations.

The linked-list method decomposes the system spatially into cells of side length greater than or equal to the cutoff distance. Every atom only interacts with atoms in the same cell or an adjacent cell so only distances between atom pairs in the same and adjacent cells must be computed.

Atoms are resorted into cells every 10 to 20 timesteps. This reduces the complexity of the computation to O N. The linked-list method is commonly used in parallel molecular dynamics codes because it simplifies communications between threads.

Every thread is assigned a cell and is passed a list of the atoms in its cell and every adjacent cell every time atoms are resorted into cells. Figure 1 Linked-cell method: To compute the interactions of the filled in atom, only atoms in the same dark-shaded and adjacent light-shaded cells are considered.

Only atoms within the shaded disk interact with the darkened atom. The neighbor list method creates lists of all atoms within a certain distance of every atom so every atom only interacts with atoms in its neighbor list. The neighbor list cutoff distance must be greater than the interaction cutoff distance and the difference determines the frequency at which the neighbor lists must be recreated.

The neighbor list method also reduces the complexity of the computation to O N 2. Figure 2 Neighbor list method: The neighbor list for the filled-in atom contains all the atoms in the light-shaded disk.

The second part offers a potpourri of interesting topical applications, showing what can be achieved by computational modelling. Here the possibilities and the limits of the methods are stressed.

Its purpose is to help students and researchers in computational materials sciences to acquire practical knowledge of relevant simulation methods. Because their behavior spans multiple length and time scales, crystal dislocations present a common ground for an in-depth discussion of a variety of computational approaches, including their relative strengths, weaknesses and inter-connections.

The details of the covered methods are presented in the form of "numerical recipes" and illustrated by case studies. A suite of simulation codes and data files is made available on the book's website to help the reader "to learn-by-doing" through solving the exercise problems offered in the book. Landou- K.

After briefly recalling essential background in statistical mechanics and probability theory, it gives a succinct overview of simple sampling methods. The concepts behind the simulation algorithms are explained comprehensively, as are the techniques for efficient evaluation of system configurations generated by simulation. It contains many applications, examples, and exercises to help the reader and provides many new references to more specialized literature.

This edition includes a brief overview of other methods of computer simulation and an outlook for the use of Monte Carlo simulations in disciplines beyond physics. This is an excellent guide for graduate students and researchers who use computer simulations in their research. It can be used as a textbook for graduate courses on computer simulations in physics and related disciplines. RaabeComputational Materials Science Modeling and simulation play an ever increasing role in the development and optimization of materials.

Computational Materials Science presents the most important approaches in this new interdisciplinary field of materials science and engineering. The reader will learn to assess which numerical method is appropriate for performing simulations at the various microstructural levels and how they can be coupled.

This book addresses graduate students and professionals in materials science and engineering as well as materials-oriented physicists and mechanical engineers. This is due to a combination of three factors: the reduced size of nano-objects, the increasing power of computers, and the development of new theoretical methods. This book represents the first attempt to provide the theoretical background needed by physicists, engineers and students to simulate nanodevices, semiconductor quantum dots and molecular devices.

It presents in a unified way the theoretical concepts, the more recent semi-empirical and ab-initio methods, and their application to experiments. The topics include quantum confinement, dielectric and optical properties, non-radiative processes, defects and impurities, and quantum transport. Principles Of Nanotechnology Molecular-Based Study Of Condensed Matter In Small Systems Publisher: World Scientific Publishing Company This invaluable book provides a pointed introduction to the fascinating subject of bottom-up nanotechnology with emphasis on the molecular-based study of condensed matter in small systems.

Nanotechnology has its roots in the landmark lecture delivered by the famous Nobel Laureate physicist, Richard Feynman, on 29 December entitled "There's Plenty of Room at the Bottom. Today, nanotechnology promises to have a revolutionary impact on the way things are designed and manufactured in the future. Principles of Nanotechnology is self-contained and unified in presentation. Granular dynamics; Algorithms for supercomputers; More about software; The future.

Review quote From reviews of the first edition: 'The book is very thorough All in all a most useful book. I recommend it strongly to all researchers involved with molecular dynamics. Drew, Computers and Chemistry 'What Press et al. Rapaport's book is useful Blumberg Selinger, Computers in Physics 'The book takes the reader from the beginnings of MD through to a fully featured MD simulation program with each step along the way being explained clearly The book I would gladly recommend it to any researcher in the field.

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