Abstract
Multiscale, multiphysics computational chemistry methods based on the ultra-accelerated quantum chemical molecular dynamics (UA-QCMD) have been developed for automotive battery systems such as Li-ion battery, fuel cells, and solar cells. It has been demonstrated that the UA-QCMD method is effective in performing quantum chemical molecular dynamics calculations of crystals of metals used in various battery systems. UA-QCMD was around 10,000,000 times faster than a conventional first-principles molecular dynamics method based on density-functional theory (DFT). In this paper we developed a new function to stochastically deal with chemical reactions within the scheme of classical molecular dynamics, and applied it to large complex systems. The stochastic parameters used in the originally developed MD program, NEW-RYUDO-CR, are determined so as to reproduce the results by UA-QCMD. The simulation approach using the NEW-RYUDO-CR and the proton hopping function was applied to proton hopping conduction in Nafion membranes and in sulfuric acid solutions. Experimental values of ionic mobilities of protons in sulfuric acid solution were estimated from diffusion coefficients by using the Einstein relation. The experimental diffusion coefficients were translated into mobilities of 36.2×10-8[m2/sV] for the proton and 8.29×10-8 [m2/sV] for the SO42- . These mobilities agreed well with the calculated values. The monotonically increasing behavior of diffusion coefficient of proton in Nafion with water content qualitatively agreed with the experimental results.
Key Words Battery technologies; Computational chemistry; Quantum chemical molecular dynamics; Fuel cell