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Evolving Molecular Force Field Parameters for Si and Ge

Al Globus, Ecleamus Ricks, Madhu Menon, and Deepak Srivastava
CSC at NASA Ames, US

Keywords: force field, parameterization, genetic algorithm, molecular dynamics

Abstract:
A genetic algorithm (GA) has been developed to fit parameters for multi-species reactive inter-atomic force field functions. While GA has successfully parameterized force fields in the past [Hunger, Beyreuther, Huttner, Allinger, Radelof, Zsolnai (1998); Hunger, Huttner (1999); Cundari, Fu (2000)], until now GA has not been applied to parameterization of reactive force fields suitable for critical nanotechnology tasks. Given an analytic form (of which several are available), fitting parameters to multi-species reactive force fields is extremely tedious and error prone because the parameter space is large and includes complex correlations. As a result, parameters are available for only a few reactive systems (Si, C, and a few others). By automating parameter fitting, we seek to significantly expand the reactive systems that may be investigated using molecular dynamics. The ability to model reactive solid systems with fast molecular dynamics, as opposed to much more compute-intensive quantum calculations, will enable a wide variety of crack propagation, thin-film deposition and etching, ion and cluster bombardment, surface diffusion and reactions, molecular machine manufacture, nanotubes strength and dynamics, and many other studies of critical importance for the development of nanotechnology. Our method, involving both near equilibrium and far from equilibrium configurations in the fitting procedure, is unlikely to get trapped in any local minima and can be extended to incorporate direct experimental measures as well. As a proof of concept, we demonstrate the procedure for the Stillinger-Weber (S-W) potential [Stillinger, Weber (1985)] by (a) reproducing the published parameters for Si by using S-W energetics in the fitness function, (b) evolving a “new” set of parameters, with a fitness function based on a non-orthogonal tight-binding method [Menon, M.; Subbaswamy, K. R. (1993)] better suited to Si cluster energetics than the published S-W potential, and (c) evolving parameters for Ge clusters, for which S-W parameters were previously unavailable. Evolution was driven by a fitness function based on the energies and forces calculated for Sin and Gen clusters (n<7) and was able to predict accurate energies for minimum energy and deformed configurations of Sin (n = 7, 8, 33) clusters, which were not used in the fitness function. Cundari, T. R.; Fu, W. T. (2000): Genetic algorithm optimization of a molecular mechanics force field for technetium. Inorganica Chimica Acta 300-302, pp.113-124 Hunger, J.; Beyreuther, S.; Huttner, G.; Allinger, K.; Radelof , U.; Zsolnai, L. (1998): How to derive force field parameters by genetic algorithms: modeling tripod-Mo(CO)3 compounds as an example. European Journal of Inorganic Chemistry, pp, 693-702 Hunger, J.; Huttner, G. (1999): Optimization and analysis of force field parameters by a combination of genetic algorithms and neural networks. Journal of Computational Chemistry, vol. 20, pp. 455-471 Menon, M.; Subbaswamy, K. R. (1993): Non-orthogonal tight-binding molecular-dynamics study of silicon clusters. Physical Review B, vol. 47, no. 19, pp. 754-759 Stillinger, F. H.; Weber, T. A. (1985): Computer simulation of local order in condensed phases of silicon. Physical Review B, vol. 31, no. 8, pp. 5262-5271

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