Published in Journal of Power Sources

“Autonomous Electrolyte Optimizer” by Akitoshi Suzumura et al., was published in the Journal of Power Sources.

We are working on the development of electrolytes to improve lithium-ion battery performance. The process of determining the optimal mixing ratio of materials can be automated to increase experimental speed and reproducibility, and optimization algorithms can autonomously determine the optimal composition with desired properties. In this study, we performed experiments 10 times faster than manual method by automating the mixing of electrolytes and measurement of ionic conductivity, and combining them with a unique optimization algorithm to determine the ratio that maximizes ionic conductivity from four different electrolyte solutions. Therefore, an increase in ionic conductivity was observed when only a few percent of a second solution was added to the main solution; moreover, this was confirmed by manual confirmation experiments. Furthermore, molecular dynamics simulations of the electrolyte solution composition were performed based on the experimental optimization results. We confirmed that addition of small amount of the second component increase the mobility of lithium ions in the electrolyte solution due to a change in the lithium ion perimeter (decrease in solvation radius). Finally, we believe that the automation and autonomy of experiments reduce human labor and promote the remoteness of experiments.

Title: Finding a Novel Electrolyte Solution of Lithium-ion Batteries Using an Autonomous Search System Based on Ensemble Optimization
Authors:Suzumura, A., Ohno, H., Kikkawa, N., Takechi, K.
Journal Name: Journal of Power Sources
Published: June 4, 2022
https://doi.org/10.1016/j.jpowsour.2022.231698