Data-driven decoupling of electronic and geometric descriptors for fluorinated additives in lithium batteries
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Updated: Sep 19, 2026
Identification and Quantification of Decomposition Mechanisms in Lithium-Ion Batteries; Input to Heat Flow Simulation for Modeling Thermal Runaway
Published on: March 7, 2022
Jiayi Hu1, Haochen Shen2, Guanyu Wang1
1College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, China. renbohua@csu.edu.cn.
Abstract:
Lithium-coordinated LUMO energies of 1432 monofluorinated additives were predicted by interpretable machine learning (R2 = 0.89) to identify key structural descriptors. Decoupled electronic and geometric descriptors of polar accessibility and compact topology in cyclic carbonate scaffolds were revealed by Shapley analysis; one candidate exhibited an orbital energy of 1.76 eV, which is lower than that of conventional fluoroethylene carbonate.
