Towards AI^2 Electrochemistry (AI^2 = AI * ab initio)
Jun Cheng, Xiamen University, China
It is known that electrode materials undergo dynamic structural changes at in-situ/in-operando conditions. Yet, the majority of computational studies only consider the static structures of electrode materials. When the materials are submerged in liquid solution, dynamic solvation effects are often completely ignored, or treated with dielectric continuum models, often lacking validation. The situations are about to change. Thanks to the latest development of in-situ experimental techniques and state-of-the-art computational methods, dynamics of electrode materials has recently drawn more and more attentions in many research areas. In this talk, I will present our recent progress on modeling dynamic catalysis and electrochemistry using ab initio molecular dynamics (AIMD). The high computational cost of AIMD however limits its application to small model systems consisting of hundreds of atoms at timescale of tens of ps. While, the latest development of AI accelerated AIMD (AI2MD) significantly increases the size and timescale, showing great promise for in situ modeling of realistic electrochemical systems.