Accelerated Discovery of Solvation Structure Engineering for Stable Aqueous Rechargeable Zinc Batteries via Physics‐Guided Bayesian Active Learning (Small 23/2025)
Source abstract
Abstract
Aqueous Zinc Batteries Aqueous zinc batteries, despite their advantages in safety and performance, suffer from water-based side reactions like hydrogen evolution and corrosion. In article number 2411632, Jonggeol Na, Kwan Woo Nam, and co-workers propose a novel electrolyte that enhances stability by suppressing these side reactions and maximizing performance through solvation structure optimization. In particular, it is noteworthy that only 26 experiments were conducted based on physics-guided Bayesian active learning.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Machine Learning and Algorithms
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Affiliations
Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA 02139 USA
Department of Chemical Engineering and Materials Science Graduate Program in System Health Science and Engineering Ewha Womans University Seoul 03760 Republic of Korea
References
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