Molecular dynamics simulations (MD) hold promise as an independent route to determining physical and chemical properties of materials under reactive conditions. Such studies can provide simple chemical pictures of ionized intermediates and reaction mechanisms, and can help identify atomic-scale properties that determine observed macroscopic kinetics. Difficulty arises in determining models for chemical bonding that are both accurate and computationally efficient. Kohn-Sham Density Functional Theory (DFT) has been shown to accurately reproduce the phase boundaries and thermal decomposition of many materials, particularly at higher thermodynamic conditions. However, due to its extreme computational cost, simulations are generally limited to 10’s of picoseconds and nanometer system sizes, frequently far less than the time and length scales probed by experiments. Classical force fields usually exhibit many orders of magnitude increase in computational efficiency and scalability. However, these methods are generally fit to the energetics of small molecular clusters or very specific bulk data, and consequently can yield poor results outside of their fitting regime.<br/><br/>To address these issues, we have developed a self-adaptive reactive force, which allows us to overcome the extreme computational cost of standard DFT-MD while retaining most of its accuracy. Here, the potential energy surface for a given set of thermodynamic conditions is computed “on the fly” through iterative matching to DFT computed forces at fixed intervals. Interatomic interactions are represented by a linear combination of Chebyshev polynomials representing all of the two-body and three-body terms in the system, determined through use of linear least-squares methods. This allows for potential energy parameters to be rapidly modified during a simulation through repeated comparison to high-level quantum calculations. The reduced reliance on DFT yields approximately <i>five orders of magnitude</i> increase in computational efficiency and can exhibit linear computational scaling. We discuss applications of our method to water and metallic liquid carbon under the extreme conditions of planetary interiors. Ultimately, our simulation approach is completely general and will have particular impact in research areas where there is traditionally a reliance on expensive DFT calculations for interpretation of imaging and spectroscopy experiments, and prediction of properties to guide materials synthesis.

Self-adaptive force matching for molecular dynamics simulation of reactive materials under extreme conditions

254th National Meeting (2017)

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