Aqueous zinc-ion batteries face significant challenges including dendrite growth and hydrogen evolution, which limit their practical application. Electrolyte additives offer a promising solution, yet traditional discovery methods remain inefficient. In this highlight, we found an exciting study that an AI-driven high-throughput screening strategy is employed to identify potential electrolyte additives from over 75,000 organic molecules. By evaluating adsorption energy on Zn(002) surfaces, electrochemical stability, and solubility, 48 candidate molecules were identified. Experimental validation confirmed that selected additives significantly enhance the performance of aqueous zinc-ion batteries.
- Open Access
- Editorial
AI-Driven Screening of Electrolyte Additives for Aqueous Zinc-Ion Batteries
- Long Wang,
- Peng Sun *
Author Information
Received: 01 Sep 2025 | Accepted: 22 Sep 2025 | Published: 17 Oct 2025
Abstract
Keywords
aqueous zinc-ion batteries | Electrolyte additives | AI-driven high-throughput screening strategy
References
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Issue
Volume 1, Issue 1How to Cite
Wang, L.; Sun, P. AI-Driven Screening of Electrolyte Additives for Aqueous Zinc-Ion Batteries. AI for Energy and Environment 2025, 1 (1), 2.
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Copyright (c) 2025 by the authors.
This work is licensed under a Creative Commons Attribution 4.0 International License.
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