Authors: Guilherme Vieira da Motta Missaka | Jeffrey Lopez
Source: ECS Meeting Abstracts (article, 2025-11-24)
Field: Materials Science — Materials Chemistry

Mitigating HER in Aqueous Lithium Electrolytes Using a High-Throughput Formulation and Characterization Platform Developing new and safe electrolyte formulations is a major challenge for the adoption of higher energy electrode chemistries in electrochemical energy storage devices. Electrolyte engineering must balance performance, affordability, and safety in new formulations. There are hundreds of possible solvents, salts and additives to tailor the electrolyte to the right application. Computational tools are a promising solution to accelerate the process through machine learning, 1 thermodynamic calculations, 2 and molecular dynamics. 3 These techniques can be computationally expensive and, without a substantial training set, still require extensive experimental validation of their results. Experimental electrolyte dataset availability is still limited due to the absence of standardization in the field, and it is challenging to scrape the literature. Therefore, there is a need for experimental tools to generate new electrolyte datasets for powerful data analysis techniques to enable novel battery chemistries. In this presentation I will discuss our automated system for electrolyte formulation and characterization in the context of aqueous electrolyte discovery. The platform autonomously handles electrolyte components and conducts electrochemical tests including Coulombic efficiency, cyclic voltammetry and impedance spectroscopy. Here we screen possible combinations of widely used aqueous electrolyte salts including lithium acetate, lithium bis(fluorosulfonyl)imide (LiFSI), lithium bis(trifluoromethane)sulfonimide (LiTFSI), lithium nitrate, and lithium sulfate . The chosen salts contain anions spanning a wide range of the Hofmeister series, which classifies them between chaotropic (structure breaking) and kosmotropic (structure making). It has been shown that chaotropic anions expand the Electrochemical Stability Window (ESW), specifically, increasing the potential at which OER occurs, though there is still a debate in the literature about the true impact of anions on the stability window. 4,5 Moreover, enabling aqueous electrolytes depends on enabling high energy anodes. Currently, various +3 V lithium aqueous battery chemistries rely on using high concentrations of LiTFSI. Here we outline possible strategies to enable higher energy anodes such as lithium titanate while constraining our material use. We leverage our high-throughput electrolyte characterization platform to produce high quality, consistent, open-source databases of electrolyte properties that we envision will assist and accelerate the entire field’s research. Our long-term goal is to go beyond aqueous electrolytes and to use the comprehensive data generated to make fundamental advances in developing new electrolyte models that will allow researchers to quickly predict optimal formulations and device performance. 1 S. C. Kim et al., Proceedings of the National Academy of Sciences , 120, e2214357120 (2023). 2 A. Dave, K. L. Gering, J. M. Mitchell, J. Whitacre, and V. Viswanathan, J. Electrochem. Soc. , 167, 013514 (2019). 3 B. Ravikumar, M. Mynam, and B. Rai, J. Phys. Chem. C , 122, 8173–8181 (2018). 4 D. Reber, R. Grissa, M. Becker, R.-S. Kühnel, and C. Battaglia, Advanced Energy Materials , 11, 2002913 (2021). 5 D. Dong, C.-X. Zhao, X. Zhang, and C. Wang, Advanced Materials , n/a, 2418700. Electrolyte ; Electrochemistry ; Context (archaeology) ; Lithium (medication) ; Chaotropic agent ; Battery (electricity) ; Cyclic voltammetry ; Faraday efficiency Machine Learning in Materials Science ; Advanced Battery Materials and Technologies ; Advanced battery technologies research