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General Multiobjective Force Field Optimization Framework, with Application to Reactive Force Fields for Silicon Carbide

Jaramillo-Botero, Andres and Naserifar, Saber and Goddard, William A., III (2014) General Multiobjective Force Field Optimization Framework, with Application to Reactive Force Fields for Silicon Carbide. Journal of Chemical Theory and Computation, 10 (4). pp. 1426-1439. ISSN 1549-9626. https://resolver.caltech.edu/CaltechAUTHORS:20140530-093650716

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Abstract

First-principles-based force fields prepared from large quantum mechanical data sets are now the norm in predictive molecular dynamics simulations for complex chemical processes, as opposed to force fields fitted solely from phenomenological data. In principle, the former allow improved accuracy and transferability over a wider range of molecular compositions, interactions, and environmental conditions unexplored by experiments. That is, assuming they have been optimally prepared from a diverse training set. The trade-off has been force field engines that are functionally complex, with a large number of nonbonded and bonded analytical forms that give rise to rather large parameter search spaces. To address this problem, we have developed GARFfield (genetic algorithm-based reactive force field optimizer method), a hybrid multiobjective Pareto-optimal parameter development scheme based on genetic algorithms, hill-climbing routines and conjugate-gradient minimization. To demonstrate the capabilities of GARFfield we use it to develop two very different force fields: (1) the ReaxFF reactive force field for modeling the adiabatic reactive dynamics of silicon carbide growth from an methyltrichlorosilane precursor and (2) the SiC electron force field with effective core pseudopotentials for modeling nonadiabatic dynamic phenomena with highly excited electronic states. The flexible and open architecture of GARFfield enables efficient and fast parallel optimization of parameters from quantum mechanical data sets for demanding applications like ReaxFF, electronic fast forward (or electron force field), and others including atomistic reactive charge-optimized many-body interatomic potentials, Morse, and coarse-grain force fields.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1021/ct5001044 DOIArticle
http://pubs.acs.org/doi/abs/10.1021/ct5001044PublisherArticle
http://pubs.acs.org/doi/suppl/10.1021/ct5001044PublisherSupporting Information
ORCID:
AuthorORCID
Jaramillo-Botero, Andres0000-0003-2844-0756
Naserifar, Saber0000-0002-1069-9789
Goddard, William A., III0000-0003-0097-5716
Additional Information:© 2014 American Chemical Society. Received: February 7, 2014; Published: March 18, 2014. This work was partially funded by the Defense Advanced Research Projects Agency (DARPA) (Grant No. N660011214037, Drs. Tyler McQuade and Anne Fischer) and by the US Department of Transportation (DOT), Federal Highway Administration (FHWA) (Award Number BAA No. DTFH61-09-R-00017, Dr. Kunik Lee). The authors thank Hai Xiao for his contributions on the eFF−ECP and Drs. Sergey Zybin and Qi An for insightful discussions.
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)N660011214037
Federal Highway Administration (FHWA)DTFH61-09-R-00017
Issue or Number:4
Record Number:CaltechAUTHORS:20140530-093650716
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20140530-093650716
Official Citation:General Multiobjective Force Field Optimization Framework, with Application to Reactive Force Fields for Silicon Carbide Andres Jaramillo-Botero, Saber Naserifar, and William A. Goddard, III Journal of Chemical Theory and Computation 2014 10 (4), 1426-1439
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:45993
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:30 May 2014 19:33
Last Modified:03 Oct 2019 06:39

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