Abstract
We present methods for the creation of semi-empirical quantum approaches and reactive force fields through force matching to quantum simulation data for materials under reactive conditions. Our methodologies overcome the extreme computational cost of standard Kohn–Sham Density Functional Theory (DFT) by mapping DFT computed simulation data onto functional forms with linear dependence on their parameters. This allows for quick parameterization of our models by avoiding the nonlinear fitting bottlenecks associated with most molecular dynamics model development. We illustrate our approach with two different systems: (i) determination of density functional tight binding models for aqueous glycine dimerization, and (ii) determination of the Chebyshev Interactional Model for Efficient Simulation (ChIMES) reactive force field for metallic liquid carbon. In each case, we observe that our approach is easy to parametrize and yields a model that is orders of magnitude faster than DFT while largely retaining its accuracy. Overall, our methods have potential use for studying complex long time and length scale chemical reactivity at extreme conditions, where there is a significant need for computationally efficient atomistic simulations methods to aid in the interpretation and design of experiments.
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Acknowledgements
This work was partially supported by NASA Astrobiology: Exobiology and Evolutionary Biology Program Element NNH14ZDA001N. Work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. The project 16-LW-020 was funded by the Laboratory Directed Research and Development Program at LLNL with N.G. as principal investigator.
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Lindsey, R.K., Kroonblawd, M.P., Fried, L.E., Goldman, N. (2019). Force Matching Approaches to Extend Density Functional Theory to Large Time and Length Scales. In: Goldman, N. (eds) Computational Approaches for Chemistry Under Extreme Conditions. Challenges and Advances in Computational Chemistry and Physics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-030-05600-1_4
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