Work

AI-assisted quantitative deciphering of molecular configuration and steric effects for high-performance zinc battery electrolytes

Year: 2026

Type: article

Abstract: Zinc-ion batteries depend on molecular design of electrolyte additives for performance optimization. However, the influence of molecular structure and steric effects on solvation behavior has not been systematically quantified. This research combines Retrieval-Augmented Generation (RAG) technology with large language models, establishing a system from intelligent literature analysis to molecular screening. Through prompt engineering optimization, screening precision under defined criteria improved from 30.0% to 100%, identifying two structurally distinct additives from over twenty thousand molecules—rigid cyclic 2-methylimidazole (MI) and flexible chain-like 3-aminopropanol (AP). Through theoretical calculations and experimental validation, we demonstrate that MI’s rigid structure restricted solvation shell adaptability, whereas AP’s conformational flexibility enhanced zinc-ion migration efficiency, suppressed hydrogen evolution and dendrite formation, and extended battery cycle life. This study quantitatively elucidates molecular structure and steric effects in zinc battery performance, establishes principles for electrolyte design, and develops an AI-driven precision screening methodology. Zinc‑ion battery performance depends on the molecular design of electrolyte additives, but the effects of molecular structure and steric factors on solvation behavior remain unquantified. Here, Retrieval‑Augmented Generation screening identifies rigid cyclic 2‑methylimidazole and flexible chain-like 3‑aminopropanol: 2‑methylimidazole limits solvation, whereas 3‑aminopropanol improves ion transport and extends battery life.

Source: Communications Materials

DOI: 10.1038/s43246-026-01100-5

Authors: Yizhan Gao, Rongkun Sun, Yiqian Shi, Zhigang Shao

Institutions: South China Normal University, Beijing Jiaotong University

Language: English

Topic: Advanced battery technologies research

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: gold

Estimated APC paid: $3,690