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Computational Generation of User‐Desired Multivariate Metal–Organic Framework Structures
Author(s) -
Kim Jihan
Publication year - 2014
Publication title -
chemphyschem
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 140
eISSN - 1439-7641
pISSN - 1439-4235
DOI - 10.1002/cphc.201300883
Subject(s) - multivariate statistics , metal organic framework , metal , computer science , materials science , chemistry , nanotechnology , organic chemistry , machine learning , adsorption
One small step: Various Monte Carlo moves are utilized to generate optimal, user‐desired MTV‐MOF structures during a single simulation run.