Parameterization of a reactive force field using a Monte Carlo algorithm

Abstract

Iype, E.; Hütter, M.; Jansen, A.P.J.; Gaastra -Nedea, S.V.; Rindt, C.C.M. • A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication Citation for published version (APA):Iype, E., Hutter, M., Jansen, A. P. J., Nedea, S. V., & Rindt, C. C. M. (2013). Parameterization of a reactive force field using a Monte Carlo algorithm. Journal of Computational Chemistry, 34(13), 1143-1154. DOI: 10.1002/jcc.23246 General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Parameterization of a Reactive Force Field using a Monte Carlo algorithmIype E * , Hütter M * , Jansen A P J † , Nedea S V * , Rindt C C M * ‡ November 6, 2015 AbstractParameterization of a Molecular Dynamics force field is essential in realistically modelling the physico-chemical processes involved in a molecular system. This step is often challenging when the equations involved in describing the force field are complicated as well as when the parameters are mostly empirical. ReaxFF is one such reactive force field which uses hundreds of parameters to describe the interactions between atoms. The optimization of the parameters in ReaxFF is done such that the the properties predicted by ReaxFF matches with a set of quantum chemical or experimental data. Usually, the optimization of the parameters is done by an inefficient single parameter parabolic-search algorithm. In this study, we use a robust Metropolis Monte-Carlo algorithm with Simulated Annealing (MMC-SA) to search for the optimum parameters for the ReaxFF force field in a high-dimensional parameter space. The optimization is done against a set of quantum chemical data for M gSO 4 hydrates. The optimized force field reproduced the chemical structures, the Equations of State and the water binding curves of M gSO 4 hydrates. The transferability test o...

The ReaxFF reactive force-field: development, applications and future directions

“…In particular, MC and genetic algorithm (GA) based approaches have risen in popularity. [145][146][147][148][149] So far, these methods have only been used for isolated force-field development efforts, and as such they still have to demonstrate their transferability and user friendliness. They do hold promise for reducing force-field development time, as well as for making the process more accessible to nonexpert users.…”

Molecular dynamics study on thermal dehydration process of epsomite (MgSO4·7H2O)

“…A molecular-scale investigation into the dehydration process seems necessary in order to unveil these details and to identify the factors that affect the diffusion through the surface layers. Iype et al [11] quantified the energies of distinct magnesium sulphate hydrates [11] and identified various hydrogen-bonding networks [12] from density functional theory (DFT) calculations. These calculations show that there is no significant charge transfer during the dehydration process, which opened up the possibility of performing a largescale non-reactive molecular dynamics (MD) simulation.…”

Parameterization of the ReaxFF reactive force field for a proline-catalyzed aldol reaction

“…However, as many parameters in ReaxFF are strongly interdependent, the optimal value of a given parameter is typically affected by the variation of other parameters, and multiple optimization cycles are necessary to reach a valuable parameterization. In addition, the assumed parabolic relationship may not be adequate for broad intervals of the parameters values . A Monte Carlo Simulated Annealing (MCSA) scheme was also proposed by Iype et al for the development of ReaxFF potentials.…”

“…In addition, the assumed parabolic relationship may not be adequate for broad intervals of the parameters values . A Monte Carlo Simulated Annealing (MCSA) scheme was also proposed by Iype et al for the development of ReaxFF potentials. In this approach, all parameters are optimized together, and, at each iteration of the MCSA process, a given number of randomly selected parameters are modified and the resulting error on the training set is computed.…”

“…The move is then accepted or rejected following a probability relationship: where is the difference between the current error and the one of the previously accepted move, is the Boltzmann constant, and gives the temperature. It was shown that such global optimization procedure performed better than the parabolic search for magnesium sulfate hydrates . The procedure has been implemented in the ReaxFF package of the commercial suite of programs SCM .…”