Exploring the Mechanisms of Reactions in Solution from Transition Path Sampling Molecular Dynamics Simulations

2005 ◽  
Vol 2 (1) ◽  
pp. 107-114 ◽  
Author(s):  
Dirk Zahn
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Path Sampling ◽  
Transition Path ◽  
Transition Path Sampling ◽  
Dynamics Simulations ◽  
Mechanisms Of Reactions

Putting the squeeze on NaCl: modelling and simulation of the pressure driven B1-B2 phase transition

2004 ◽  
Vol 219 (6) ◽  
Author(s):  
Stefano Leoni ◽  
Dirk Zahn
Keyword(s):  
Phase Transition ◽  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Geometric Approach ◽  
Path Sampling ◽  
Dynamical Transition ◽  
Cscl Type ◽  
B2 Phase ◽  
The Difference ◽  
Dynamics Simulations

AbstractWe used a geometric approach to derive models for the transition B1 (NaCl) to B2 (CsCl) type structure. This enabled us to construct several dynamical transition states, corresponding to different mechanistic pathways. From this, transition trajectories were obtained, which served as starting points for path sampling molecular dynamics simulations. We point out the difference of this approach from approaches based on energy calculations, and demonstrate that a preferred mechanism can be clearly discriminated.

Monomolecular cracking of propane over acidic chabazite: An ab initio molecular dynamics and transition path sampling study

2011 ◽  
Vol 279 (1) ◽  
pp. 220-228 ◽  
Author(s):  
Tomáš Bučko ◽  
Lubomir Benco ◽  
Jürgen Hafner ◽  
János G. Ángyán
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Ab Initio Molecular Dynamics ◽  
Path Sampling ◽  
Transition Path ◽  
Transition Path Sampling

scholarly journals OpenPathSampling: A Python framework for path sampling simulations. I. Basics

2018 ◽  
Author(s):  
David W.H. Swenson ◽  
Jan-Hendrik Prinz ◽  
Frank Noe ◽  
John D. Chodera ◽  
Peter G. Bolhuis
Keyword(s):  
Benchmark Problems ◽  
Path Sampling ◽  
Transition Path ◽  
Transition Path Sampling ◽  
Molecular Systems ◽  
Sampling Schemes ◽  
Initial Release ◽  
Sampling Algorithms ◽  
Dynamics Simulations ◽  
Transition Interface

Transition path sampling techniques allow molecular dynamics simulations of complex systems to focuson rare dynamical events, providing insight into mechanisms and the ability to calculate rates inaccessibleby ordinary dynamics simulations. While path sampling algorithms are conceptually as simple as importancesampling Monte Carlo, the technical complexity of their implementation has kept these techniquesout of reach of the broad community. Here, we introduce an easy-to-use Python framework called Open-PathSampling (OPS) that facilitates path sampling for (bio)molecular systems with minimal effort and yetis still extensible. Interfaces to OpenMM and an internal dynamics engine for simple models are providedin the initial release, but new molecular simulation packages can easily be added. Multiple ready-to-usetransition path sampling methodologies are implemented, including standard transition path sampling (TPS)between reactant and product states, transition interface sampling (TIS) and its replica exchange variant(RETIS), as well as recent multistate and multiset extensions of transition interface sampling (MSTIS, MISTIS).In addition, tools are provided to facilitate the implementation of new path sampling schemes built on basicpath sampling components. In this paper, we give an overview of the design of this framework and illustratethe simplicity of applying the available path sampling algorithms to a variety of benchmark problems.

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