Importance of Equilibration Method and Sampling for Ab Initio Molecular Dynamics Simulations of Solvent-Lithium-Salt Systems in Lithium-Oxygen Batteries
E Crabb and A France-Lanord and G Leverick and R Stephens and Y Shao- Horn and JC Grossman, JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 16, 7255-7266 (2020).
We examine the effect of equilibration methodology and sampling on ab initio molecular dynamics (AIMD) simulations of systems of common solvents and salts found in lithium-oxygen batteries. We compare two equilibration methods: (1) using an AIMD temperature ramp and (2) using a classical MD simulation followed by a short AIMD simulation both at the target simulation temperature of 300 K We also compare two different classical allatom force fields: PCFF+ and OPLS. By comparing the simulated association/dissociation behavior of lithium salts in different solvents with the experimental behavior, we find that equilibration with the classical force field that produces more physically accurate behavior in the classical MD simulations, namely, OPLS, also results in more physically accurate behavior in the AIMD runs compared to equilibration with PCFF+ or with the AIMD temperature ramp. Equilibration with OPLS outperforms even the pure AIMD equilibration because the classical MD equilibration is much longer than the AIMD equilibration (nanosecond vs picosecond timescales). These longer classical simulations allow the systems to find a more physically accurate initial configuration, and in the short simulation times available for the AIMD production runs, the initial configuration has a large impact on the system behavior. We also demonstrate the importance of averaging coordination number over multiple starting configurations and Li+ ions, as the majority of Li+ ions do not undergo a single association or dissociation event even in an similar to 40 ps long simulation and thus do not sample a statistically significant portion of the phase space. These results show the importance of both equilibration method and sufficient independent sampling for extracting experimentally relevant quantities from AIMD simulations.
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