Computationally aided design of single-ion-conducting block copolymer electrolytes to boost lithium-ion conductivity

In this work, we implement a combinatory approach that integrates molecular dynamics (MD) simulation and a Gaussian process regression (GPR) algorithm to explore optimal design strategies for a generic single-ion-conducting block copolymer electrolyte (SIC-BCPE) model system that covers a rich design parameter space inspired by recently established poly(ethylene oxide)-based block copolymer electrolytes. The GPR algorithm is employed to efficiently reveal the relationships between the desired lithium-ion conductivity and four design parameters reflecting both chain architectural control and specific tuning of molecular chemistry. Guided by the GPR results, an optimal combination of four parameter values is inferred, and MD simulation confirms that the corresponding SIC-BCPE system produces relatively higher lithium-ion conductivity. To further understand the influence of each molecular parameter on the trends of lithium-ion conductivity, we analyse the proportion variation of different types of lithium-ion coordination and identify a strong correlation between the ion coordination pattern and ionic conductivity. Due to its generality, we expect that the MD-GPR combinatory approach reported in this work is applicable to a broad range of other polymer-based ion transport systems. (c) 2024 Society of Chemical Industry.