Parameterization of a reactive force field using a Monte Carlo algorithm

• Published in: Journal of computational chemistry Vol. 34; no. 13; pp. 1143 - 1154
• Main Authors: Iype, E., Hütter, M., Jansen, A. P. J., Nedea, S. V., Rindt, C. C. M.
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 15.05.2013; Wiley Subscription Services, Inc
• Subjects: Algorithms; Chemistry; force field; Magnesium Sulfate - chemistry; metropolis Monte Carlo; molecular dynamics; Molecular Dynamics Simulation; Monte Carlo Method; Monte Carlo simulation; optimization; Optimization algorithms; ReaxFF
• ISSN: 0192-8651; 1096-987X
• DOI: 10.1002/jcc.23246

Parameterization of a molecular dynamics force field is essential in realistically modeling the physicochemical 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 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 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 MgSO4 hydrates. The optimized force field reproduced the chemical structures, the equations of state, and the water binding curves of MgSO4 hydrates. The transferability test of the ReaxFF force field shows the extend of transferability for a particular molecular system. This study points out that the ReaxFF force field is not indefinitely transferable. © 2013 Wiley Periodicals, Inc. Parameterization of a reactive force field (ReaxFF) is performed using a robust Metropolis Monte Carlo algorithm for a system of magnesium sulfate hydrates. This new method for optimizing the force field is more efficient than the previous single parameter parabolic search method, especially when one does not have a good initial condition. The stochastic nature of the method enables one to arrive at the global minimum in the parameter space and thereby the best obtainable force field.