Fluoride Electrolyte Discovery via Reactivity Guided Genetic Algorithms

Fluoride-ion batteries (FIBs) present a promising alternative to lithium-ion technologies, offering superior theoretical energy densities. However, fluoride's high reactivity rapidly degrades traditional organic solvents via nucleophilic attack, limiting practical use. Here, chemical stability and fluoride solvation are simultaneously optimized through an evolutionary computational framework that integrates genetic algorithms, quantum chemistry-based stability screening, and machine-learned solvation models. The framework identifies nitrogen-containing heteroaromatic rings as optimal structural motifs, with pentafluoropyridine exhibiting exceptional stability and a 2.3-fold enhanced half-life compared to bis(2,2,2-trifluoroethyl) ether, the current benchmark organic solvent for fluoride salts. These computational insights establish clear design principles emphasizing heteroatom-induced charge localization and resonance stabilization that transform electrolyte development from empirical screening toward rational molecular engineering.