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Efficient parametrization of complex molecule-surface force fields

delete2015-04-16
delete8
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OA
AI
D
David Gao *
F
Filippo Federici Canova
M
Matthew B. Watkins
A
Alexander L. Shluger
DOI:10.1002/jcc.23904delete
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摘要

摘要

En 中文
We present an efficient scheme for parametrizing complex molecule-surface force fields from ab initio data. The cost of producing a sufficient fitting library is mitigated using a 2D periodic embedded slab model made possible by the quantum mechanics/molecular mechanics scheme in CP2K. These results were then used in conjunction with genetic algorithm (GA) methods to optimize the large parameter sets needed to describe such systems. The derived potentials are able to well reproduce adsorption geometries and adsorption energies calculated using density functional theory. Finally, we discuss the challenges in creating a sufficient fitting library, determining whether or not the GA optimization has completed, and the transferability of such force fields to similar molecules. (c) 2015 Wiley Periodicals, Inc.
Keyword:
QM/MM
organic molecules
genetic algorithm
force field
optimization
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期刊

Journal of Computational Chemistry 封面图
Journal of Computational Chemistry
IF:
4.8
论文数:
7.1K
被引数:
6.1W

机构

U
University College London
学者数:
7.9W
论文数: 6.2W
被引数: 15.7W
U
university of london
学者数:
21.5W
论文数: 19.7W
被引数: 305
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