Author

Jinliang Li

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#explainable ai Review Sep 2026

A Data‐to‐Interface Framework for AI‐Guided Sodium‐Ion Battery Materials Discovery: From Descriptors to Full‐Cell Decisions

For sodium‐ion batteries (SIBs), the central obstacle to artificial intelligence (AI)‐guided discovery is not simply data volume or algorithm choice, but the conditional nature of electrochemical labels. Capacity, voltage, initial Coulombic efficiency (ICE), rate capability, and retention depend on synthesis, disorde...

Gang Chen, Hong-Yang Zhao, Jun-Feng Li et al. · Advanced Functional Material... · 0 citations

Open access Jul 2026

A Quantitative Electrostatic Potential Descriptor Enables Deep Learning-Accelerated Discovery of High-Performance Lithium-Ion Battery Electrolytes.

Rational electrolyte design for high-energy-density lithium-ion batteries (LIBs) urgently demands precise and quantitative molecular descriptors of solvation power to enable deep learning (DL)-accelerated screening, yet such descriptors remain lacking. Here, we introduce the electrostatic potential ratio |ESPmin|/ESPma...

Kun Han, Yu Lou, Jun-Feng Li et al. · Angewandte Chemie · 1 citation