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Title: The adaptive buffered force QM/MM method in the CP2K and AMBER software packages

Journal Article · · Journal of Computational Chemistry
DOI:https://doi.org/10.1002/jcc.23839· OSTI ID:1345677
 [1];  [2];  [3];  [4];  [5];  [6];  [1];  [7]
  1. Engineering Department University of Cambridge Cambridge CB2 1PZ United Kingdom
  2. Institute for Condensed Matter and Complex Systems School of Physics and Astronomy University of Edinburgh Edinburgh EH9 3JZ United Kingdom
  3. San Diego Supercomputer Center University of California San Diego La Jolla California 92093
  4. Mathematical and Computational Sciences Department IBM Research–Zurich Säumerstrasse 4 8803 Rüschlikon Switzerland
  5. San Diego Supercomputer Center University of California San Diego La Jolla California 92093, Department of Chemistry and Biochemistry University of California San Diego La Jolla California 92093
  6. The Maxwell Institute and School of Mathematics, University of Edinburgh Edinburgh EH9 3JZ United Kingdom
  7. Center for Computational Material Science Naval Research Laboratory Washington DC 20375
+ Show Author Affiliations

We present the implementation and validation of the adaptive buffered force (AdBF) quantum-mechanics/molecular-mechanics (QM/MM) method in two popular packages, CP2K and AMBER. The implementations build on the existing QM/MM functionality in each code, extending it to allow for redefinition of the QM and MM regions during the simulation and reducing QM-MM interface errors by discarding forces near the boundary according to the buffered force-mixing approach. New adaptive thermostats, needed by force-mixing methods, are also implemented. Different variants of the method are benchmarked by simulating the structure of bulk water, water autoprotolysis in the presence of zinc and dimethyl-phosphate hydrolysis using various semiempirical Hamiltonians and density functional theory as the QM model. It is shown that with suitable parameters, based on force convergence tests, the AdBF QM/MM scheme can provide an accurate approximation of the structure in the dynamical QM region matching the corresponding fully QM simulations, as well as reproducing the correct energetics in all cases. Adaptive unbuffered force-mixing and adaptive conventional QM/MM methods also provide reasonable results for some systems, but are more likely to suffer from instabilities and inaccuracies.

Research Organization:
Univ. of California, San Diego, CA (United States)
Sponsoring Organization:
USDOE; National Institutes of Health (NIH); National Science Foundation (NSF)
Grant/Contract Number:
DE‐AC36‐99GO‐10337; AC36-99GO10337; OCI-1148358; ACI-1053575; EP/G036136/1; EP/J01298X/1; GM100934
OSTI ID:
1345677
Alternate ID(s):
OSTI ID: 1343098; OSTI ID: 1345678
Journal Information:
Journal of Computational Chemistry, Journal Name: Journal of Computational Chemistry Vol. 36 Journal Issue: 9; ISSN 0192-8651
Publisher:
Wiley Blackwell (John Wiley & Sons)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 36 works
Citation information provided by
Web of Science

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Related Subjects

97 MATHEMATICS AND COMPUTING
71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
quantum-mechanics/molecular-mechanics
adaptive quantum-mechanics/molecular-mechanics
force-mixing
multiscale