פלטפורמת AI לניתוח חומרה-ליבה של אלקטרוליטים לתאי סוללות ליתיום

תקציר מקורי באנגליתarXiv:2607.25597v3 Announce Type: replace Abstract: Electrolyte reactivity in lithium batteries is shaped by molecular functional groups, Li$^{+}$ solvation and salt-anion participation. Conventional quantum chemistry is too computationally expensive for systematic analysis of diverse electrolyte molecules and their local solvation environments. Here we present EMolStudio, a density-matrix-centered AI platform for electronic-structure prediction and analysis. Its workflow integrates molecular functionalization, explicit Li$^{+}$ first-shell assembly, density-matrix prediction, and electronic-structure parsing. Applied to 163,655 functionalized molecules and 22,500 first-shell clusters across four lithium salts, we find that 1) functionalization separates CO$_{2}$Me, CN, F/CF$_{3}$, and sul