Spectral Denoising for Accelerated Analysis of Correlated Ionic Transport

Electrolytes control battery recharge time and efficiency, anode/cathode stability, and ultimately safety, consequently electrolyte optimization is crucial for the design of modern energy storage devices. Herein, we propose a novel, general method for analyzing and calculating mass/charge transport in media with non-negligible correlations from atomistic simulations [1]. While being widely adopted thanks to its quick convergence, the dilute uncorrelated approximation often yields biased, i.e., inaccurate estimates of the transport properties. On the other hand, the exact Green-Kubo method is prohibitively expensive for complex and large systems, which is often the case for modern electrolyte design. The approach we present automatically calculates and utilizes the collective diffusion eigenmodes of the displacement correlation matrix to denoise the calculation of the transport properties. Additionally, it can be adopted to discover collective diffusion modes in an unsupervised fashion. The approach is universally applicable and provably superior to previously available methods, exhibiting speed ups of several orders of magnitude.<br/>[1] Molinari, N., Xie, Y., Leifer, I., Marcolongo, A., Kornbluth, M. and Kozinsky, B., 2021. Spectral denoising for accelerated analysis of correlated ionic transport. Physical Review Letters, 127(2), p.025901.