Screening and Design of Aqueous Zinc Battery Electrolytes Based on the Multimodal Optimization of Molecular...

Aqueous batteries, such as aqueous zinc-ion batteries (AZIB), have garnered significant attention because of their advantages in intrinsic safety, low cost, and eco-friendliness. However, aqueous electrolytes tend to freeze at low temperatures, which limits their potential industrial applications. Thus, one of the core challenges in aqueous electrolyte design is optimizing the formula to prevent freezing while maintaining good ion conductivity. However, the experimental trial-and-error approach is inefficient for this purpose, and existing simulation tools are either inaccurate or too expensive for high-throughput phase transition predictions. In this work, we employ a small amount of experimental data and differentiable simulation techniques to develop a multimodal optimization workflow. With minimal human intervention, this workflow significantly enhances the prediction power of classical force fields for electrical conductivity. Most importantly, the simulated electrical conductivity can serve as an effective predictor of electrolyte freezing at low temperatures. Generally, the workflow developed in this work introduces a new paradigm for electrolyte design. This paradigm leverages both easily measurable experimental data and fast simulation techniques to predict properties that are challenging to access by using either approach alone.