Lengthening The Timescale Reach Of Molecular Dynamics
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Lengthening The Timescale Reach Of Molecular Dynamics
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Author :
language : en
Publisher:
Release Date : 2012
Lengthening The Timescale Reach Of Molecular Dynamics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Extending The Time Scale In Atomistic Simulations
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Author : Sanket Sarkar
language : en
Publisher:
Release Date : 2011
Extending The Time Scale In Atomistic Simulations written by Sanket Sarkar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Abstract: Materials properties depend on processes that take place on a variety of time scales. These range from atomic vibrations or dislocation-mediated slip processes, which have typical time scales of hundreds of femtoseconds (fs) to hundreds of picoseconds (ps), to diffusion, which may take place on the order of seconds or longer. This disparity in time scales leads to difficulties when trying to model slower processes where individual atomic motions may be important, such as diffusion controlled boundary migration and dislocation climb. A straightforward molecular dynamics (MD) approach, with a typical time step of 1 fs, would require an enormous computation time to adequately capture these processes. This work presents a novel method, called Diffusive Molecular Dynamics (DMD), which can capture the diffusion time scale while retaining the atomic spatial resolution by coarse-graining over atomic vibrations and evolving a site-probability representation of atomic density clouds. DMD solves master equation on a moving atomic grid. It combines long-range elastic effects and short- range atomic interactions simultaneously with gradient thermodynamics.
Overcoming The Timescale Barrier In Molecular Dynamics
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Author : Christof Schütte
language : en
Publisher:
Release Date : 2022
Overcoming The Timescale Barrier In Molecular Dynamics written by Christof Schütte and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Molecular Dynamics
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Author : Ben Leimkuhler
language : en
Publisher: Springer
Release Date : 2015-05-18
Molecular Dynamics written by Ben Leimkuhler and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-18 with Mathematics categories.
This book describes the mathematical underpinnings of algorithms used for molecular dynamics simulation, including both deterministic and stochastic numerical methods. Molecular dynamics is one of the most versatile and powerful methods of modern computational science and engineering and is used widely in chemistry, physics, materials science and biology. Understanding the foundations of numerical methods means knowing how to select the best one for a given problem (from the wide range of techniques on offer) and how to create new, efficient methods to address particular challenges as they arise in complex applications. Aimed at a broad audience, this book presents the basic theory of Hamiltonian mechanics and stochastic differential equations, as well as topics including symplectic numerical methods, the handling of constraints and rigid bodies, the efficient treatment of Langevin dynamics, thermostats to control the molecular ensemble, multiple time-stepping, and the dissipative particle dynamics method.
Free Energy Calculations
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Author : Christophe Chipot
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-01-08
Free Energy Calculations written by Christophe Chipot and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-08 with Language Arts & Disciplines categories.
Free energy constitutes the most important thermodynamic quantity to understand how chemical species recognize each other, associate or react. Examples of problems in which knowledge of the underlying free energy behaviour is required, include conformational equilibria and molecular association, partitioning between immiscible liquids, receptor-drug interaction, protein-protein and protein-DNA association, and protein stability. This volume sets out to present a coherent and comprehensive account of the concepts that underlie different approaches devised for the determination of free energies. The reader will gain the necessary insight into the theoretical and computational foundations of the subject and will be presented with relevant applications from molecular-level modelling and simulations of chemical and biological systems. Both formally accurate and approximate methods are covered using both classical and quantum mechanical descriptions. A central theme of the book is that the wide variety of free energy calculation techniques available today can be understood as different implementations of a few basic principles. The book is aimed at a broad readership of graduate students and researchers having a background in chemistry, physics, engineering and physical biology.
Long Timescale Path Integral Molecular Dynamics From Equations Of Motion
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Author : Benjamin Angus Mee Gladwin
language : en
Publisher:
Release Date : 2007
Long Timescale Path Integral Molecular Dynamics From Equations Of Motion written by Benjamin Angus Mee Gladwin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Equations of motion categories.
Accelerated Molecular Dynamics Methods
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Author :
language : en
Publisher:
Release Date : 2009
Accelerated Molecular Dynamics Methods written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
A long-standing limitation in the use of molecular dynamics (MD) simulation is that it can only be applied directly to processes that take place on very short timescales: nanoseconds if empirical potentials are employed, or picoseconds if we rely on electronic structure methods. Many processes of interest in chemistry, biochemistry, and materials science require study over microseconds and beyond, due either to the natural timescale for the evolution or to the duration of the experiment of interest. Ignoring the case of liquids xxx, the dynamics on these time scales is typically characterized by infrequent-event transitions, from state to state, usually involving an energy barrier. There is a long and venerable tradition in chemistry of using transition state theory (TST) [10, 19, 23] to directly compute rate constants for these kinds of activated processes. If needed dynamical corrections to the TST rate, and even quantum corrections, can be computed to achieve an accuracy suitable for the problem at hand. These rate constants then allow them to understand the system behavior on longer time scales than we can directly reach with MD. For complex systems with many reaction paths, the TST rates can be fed into a stochastic simulation procedure such as kinetic Monte Carlo xxx, and a direct simulation of the advance of the system through its possible states can be obtained in a probabilistically exact way. A problem that has become more evident in recent years, however, is that for many systems of interest there is a complexity that makes it difficult, if not impossible, to determine all the relevant reaction paths to which TST should be applied. This is a serious issue, as omitted transition pathways can have uncontrollable consequences on the simulated long-time kinetics. Over the last decade or so, we have been developing a new class of methods for treating the long-time dynamics in these complex, infrequent-event systems. Rather than trying to guess in advance what reaction pathways may be important, we return instead to a molecular dynamics treatment, in which the trajectory itself finds an appropriate way to escape from each state of the system. Since a direct integration of the trajectory would be limited to nanoseconds, while we are seeking to follow the system for much longer times, we modify the dynamics in some way to cause the first escape to happen much more quickly, thereby accelerating the dynamics. The key is to design the modified dynamics in a way that does as little damage as possible to the probability for escaping along a given pathway - i.e., we try to preserve the relative rate constants for the different possible escape paths out of the state. We can then use this modified dynamics to follow the system from state to state, reaching much longer times than we could reach with direct MD. The dynamics within any one state may no longer be meaningful, but the state-to-state dynamics, in the best case, as we discuss in the paper, can be exact. We have developed three methods in this accelerated molecular dynamics (AMD) class, in each case appealing to TST, either implicitly or explicitly, to design the modified dynamics. Each of these methods has its own advantages, and we and others have applied these methods to a wide range of problems. The purpose of this article is to give the reader a brief introduction to how these methods work, and discuss some of the recent developments that have been made to improve their power and applicability. Note that this brief review does not claim to be exhaustive: various other methods aiming at similar goals have been proposed in the literature. For the sake of brevity, our focus will exclusively be on the methods developed by the group.
Multiscale Modeling In Biomechanics And Mechanobiology
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Author : Suvranu De
language : en
Publisher: Springer
Release Date : 2014-10-10
Multiscale Modeling In Biomechanics And Mechanobiology written by Suvranu De and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-10 with Technology & Engineering categories.
Presenting a state-of-the-art overview of theoretical and computational models that link characteristic biomechanical phenomena, this book provides guidelines and examples for creating multiscale models in representative systems and organisms. It develops the reader's understanding of and intuition for multiscale phenomena in biomechanics and mechanobiology, and introduces a mathematical framework and computational techniques paramount to creating predictive multiscale models. Biomechanics involves the study of the interactions of physical forces with biological systems at all scales – including molecular, cellular, tissue and organ scales. The emerging field of mechanobiology focuses on the way that cells produce and respond to mechanical forces – bridging the science of mechanics with the disciplines of genetics and molecular biology. Linking disparate spatial and temporal scales using computational techniques is emerging as a key concept in investigating some of the complex problems underlying these disciplines. Providing an invaluable field manual for graduate students and researchers of theoretical and computational modelling in biology, this book is also intended for readers interested in biomedical engineering, applied mechanics and mathematical biology.
Intermolecular Forces
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Author : A. Pullman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Intermolecular Forces written by A. Pullman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Science categories.
Proceedings of the 14th Jerusalem Symposium on Quantum Chemistry and Biochemistry, Jerusalem, Israel, April 13-16, 1981
Machine Learning Meets Quantum Physics
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Author : Kristof T. Schütt
language : en
Publisher: Springer Nature
Release Date : 2020-06-03
Machine Learning Meets Quantum Physics written by Kristof T. Schütt and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-03 with Science categories.
Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.