Exploring Electrolyte Adsorption on the Different Types of Layered Cathode Surfaces in Lithium-Ion Batteries via a Universal Neural Network Potential Method.

LiNi Mn Co O (NCM) is a promising cathode material for lithium-ion batteries. Their long-term stability and impedance growth as cycles are strongly influenced by the properties of the cathode electrolyte interface (CEI), formed by the reaction between the electrolyte and electrode surface. Understanding of these interactions at the atomic level of the NCM electrode surface and electrolyte will provide a new strategic approach for the design of a highly functional CEI layer. In this study, we explored the influence of Ni content in transition metal layers on surface energies under different synthetic conditions and terminations using a density functional theory (DFT) validated universal neural network potential (UNNP) method. Furthermore, we investigated the adsorption of ethylene carbonate (EC) and dimethyl carbonate (DMC) on the most favorable NCM surfaces. EC and DMC displayed similar adsorption energy trends; however, differences were observed in the preferred configurations, which can affect the formation of the CEI.