A Coupled Molecular Dynamics/Kinetic Monte Carlo Approach for Protonation Dynamics in Extended Systems

2014 ◽  
Vol 10 (10) ◽  
pp. 4221-4228 ◽  
Author(s):  
Gabriel Kabbe ◽  
Christoph Wehmeyer ◽  
Daniel Sebastiani
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Approach ◽  
Extended Systems

Modeling Investigation of the Local Electrochemistry in Lithium-O2Batteries: A Kinetic Monte Carlo Approach

2015 ◽  
Vol 163 (3) ◽  
pp. A329-A337 ◽  
Author(s):  
Guillaume Blanquer ◽  
Yinghui Yin ◽  
Matias A. Quiroga ◽  
Alejandro A. Franco
Keyword(s):  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Approach

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent

2016 ◽  
Vol 18 (18) ◽  
pp. 13052-13065 ◽  
Author(s):  
Emanuel K. Peter ◽  
Joan-Emma Shea ◽  
Igor V. Pivkin
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Protein Folding ◽  
Kinetic Monte Carlo ◽  
Replica Exchange ◽  
Replica Exchange Molecular Dynamics ◽  
Accelerated Simulation ◽  
Explicit Solvent ◽  
Exchange Algorithms

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC).

L1 Regularization-Based Model Reduction of Complex Chemistry Molecular Dynamics for Statistical Learning of Kinetic Monte Carlo Models

MRS Advances ◽  
2016 ◽  
Vol 1 (24) ◽  
pp. 1767-1772 ◽  
Author(s):  
Qian Yang ◽  
Carlos A. Sing-Long ◽  
Evan J. Reed
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
A Priori ◽  
Reaction Network ◽  
Md Simulations ◽  
Rate Coefficients ◽  
Elementary Reactions ◽  
L1 Regularization ◽  
Complex Chemistry

ABSTRACTKinetic Monte Carlo (KMC) methods have been a successful technique for accelerating time scales and increasing system sizes beyond those achievable with fully atomistic simulations. However, a requirement for its success is a priori knowledge of all relevant reaction pathways and their rate coefficients. This can be difficult for systems with complex chemistry, such as shock-compressed materials at high temperatures and pressures or phenolic spacecraft heat shields undergoing pyrolysis, which can consist of hundreds of molecular species and thousands of distinct reactions. In this work, we develop a method for first estimating a KMC model composed of elementary reactions and rate coefficients by using large datasets derived from a few molecular dynamics (MD) simulations of shock compressed liquid methane, and then using L1 regularization to reduce the estimated chemical reaction network. We find that the full network of 2613 reactions can be reduced by 89% while incurring approximately 9% error in the dominant species (CH4) population. We find that the degree of sparsity achievable decreases when similar accuracy is required for additional populations of species.

Improvement of nanowire distributions with a STM tip: a kinetic Monte Carlo approach

2003 ◽  
Vol 532-535 ◽  
pp. 531-535
Author(s):  
S. Baud ◽  
F. Picaud ◽  
C. Ramseyer
Keyword(s):  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Approach

An Integrated Molecular Dynamics and Monte Carlo Approach to Study Epitaxial Deposition of Silicon

2001 ◽  
Vol 672 ◽  
Author(s):  
Sweta Somasi ◽  
Bamin Khomami ◽  
Ronald Lovett
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Time Scales ◽  
Atomistic Simulation ◽  
Effective Coverage ◽  
Monte Carlo Approach ◽  
Epitaxial Deposition

ABSTRACTThe length and time scales of an atomistic simulation are often too small for any direct comparison with experimental observations. In order to study the coverage of pits (COPs) found on the Si (100) surface by epitaxial deposition, we first calculate rate of individual steps using molecular dynamics and then define a sequence of Monte-Carlo steps to study the effect of various factors on effective coverage of COPs.

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