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Yamashita T, Peng Y, Knight C, et al. Computationally Efficient Multiconfigurational Reactive Molecular Dynamics. J Chem Theory Comput. 2012;8(12):4863-4875doi: 10.1021/ct3006437.
Yamashita, T., Peng, Y., Knight, C., & Voth, G. A. (2012). Computationally Efficient Multiconfigurational Reactive Molecular Dynamics. Journal of chemical theory and computation, 8(12), 4863-4875. https://doi.org/10.1021/ct3006437
Yamashita, Takefumi, et al. "Computationally Efficient Multiconfigurational Reactive Molecular Dynamics." Journal of chemical theory and computation vol. 8,12 (2012): 4863-4875. doi: https://doi.org/10.1021/ct3006437
Yamashita T, Peng Y, Knight C, Voth GA. Computationally Efficient Multiconfigurational Reactive Molecular Dynamics. J Chem Theory Comput. 2012 Dec 11;8(12):4863-4875. doi: 10.1021/ct3006437. PMID: 25100924; PMCID: PMC4120847.
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J Chem Theory Comput. 2012 Dec 11;8(12):4863-4875. doi: 10.1021/ct3006437.

Computationally Efficient Multiconfigurational Reactive Molecular Dynamics.

Journal of chemical theory and computation

Takefumi Yamashita, Yuxing Peng, Chris Knight, Gregory A Voth

Affiliations

  1. Laboratory for Systems Biology and Medicine, Research Center for Advanced Science and Technology, the University of Tokyo, 4-6-1 Komaba, Tokyo, Japan.
  2. Department of Chemistry, James Franck Institute, and Computation Institute, University of Chicago, Chicago, IL 6063.
  3. Computing, Environment, and Life Sciences, Argonne National Laboratory, Argonne, IL 60439.
  4. Department of Chemistry, James Franck Institute, and Computation Institute, University of Chicago, Chicago, IL 6063 ; Computing, Environment, and Life Sciences, Argonne National Laboratory, Argonne, IL 60439.

PMID: 25100924 PMCID: PMC4120847 DOI: 10.1021/ct3006437

Abstract

It is a computationally demanding task to explicitly simulate the electronic degrees of freedom in a system to observe the chemical transformations of interest, while at the same time sampling the time and length scales required to converge statistical properties and thus reduce artifacts due to initial conditions, finite-size effects, and limited sampling. One solution that significantly reduces the computational expense consists of molecular models in which effective interactions between particles govern the dynamics of the system. If the interaction potentials in these models are developed to reproduce calculated properties from electronic structure calculations and/or ab initio molecular dynamics simulations, then one can calculate accurate properties at a fraction of the computational cost. Multiconfigurational algorithms model the system as a linear combination of several chemical bonding topologies to simulate chemical reactions, also sometimes referred to as "multistate". These algorithms typically utilize energy and force calculations already found in popular molecular dynamics software packages, thus facilitating their implementation without significant changes to the structure of the code. However, the evaluation of energies and forces for several bonding topologies per simulation step can lead to poor computational efficiency if redundancy is not efficiently removed, particularly with respect to the calculation of long-ranged Coulombic interactions. This paper presents accurate approximations (effective long-range interaction and resulting hybrid methods) and multiple-program parallelization strategies for the efficient calculation of electrostatic interactions in reactive molecular simulations.

Keywords: coarse-graining; effective long-range interaction; multiple-program parallelization; reactive molecular dynamics

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