Computational Screening of Glyme-Based Room-Temperature Aluminum Plating Solutions

A computational data-driven approach is applied to the design of liquid electrolyte materials for a complex phenomenon, viz. electrochemical deposition. A protocol for the liquid electrolyte material exploration consists of (i) structure optimization, (ii) reduction mechanism elucidation, and (iii) computational screening. A case study is conducted targeting glyme-based room-temperature aluminum (Al) electroplating solutions, where how to achieve a higher plating speed has been an open issue. The determination of stable Al-Cl-glyme complex structures by density functional theory calculations enables the modeling for molecular dynamics simulations of the bulk electrolytes, namely, aluminum chloride (AlCl₃)-diglyme (G2)-cosolvent system. It is shown that a tridentate coordination of diglyme (G2) to [AlCl₂]⁺ is robust against desolvation and one-electron reduction, suggesting that the diffusion coefficients of the [AlCl₂]⁺ cationic complex are an indication of faster plating. Additionally, the calculated diffusion coefficients correlate weakly with the relative permittivity data of cosolvents in their pure state but strongly with viscosity data. This relationship can be used to design Al plating solutions.