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On reverse Monte Carlo constraints and model reproduction
Author(s) -
Opletal George,
Petersen Timothy C.,
Barnard Amanda S.,
Russo Salvy P.
Publication year - 2017
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.24799
Subject(s) - monte carlo method , reverse monte carlo , constraint (computer aided design) , statistical physics , ternary operation , computer science , ab initio , variety (cybernetics) , chemistry , mathematics , physics , crystallography , statistics , artificial intelligence , neutron diffraction , geometry , organic chemistry , crystal structure , programming language
Reverse Monte Carlo (RMC) simulations were performed to investigate the effectiveness of any combination of five experimentally motivated constraints on the reproduction of a test case, a ternary ab initio model. It was found that low energy structures fitting a variety of constraints commonly used in the RMC methodology could still provide an incorrect description of the chemical structural unit populations in multi‐elemental systems. It is shown that the use of an elemental bond type constraint is an effective way to avoid this. © 2017 Wiley Periodicals, Inc.