Prototype-guided transfer of sparse literature knowledge for electrolyte additive discovery
Electrolyte additive discovery remains challenging because experimentally validated molecules are sparse, whereas accessible chemical spaces are vast and largely unlabeled. This challenge is amplified in lithium-ion batteries, where additive performance arises from coupled interfacial reactions rather than a single molecular property. Here, we develop a prototype-guided molecular intelligence, ProtoMI, a literature-driven framework that learns transferable structural priors from reported electrolyte additives and uses them to prioritize candidates in unlabeled chemical space. For boron-containing additives, ProtoMI combines 126 literature-reported molecules with 179,977 unlabeled candidat...
| Authors | Weixiang Hong, Hongting Du, Jiayue Tang et al. |
|---|---|
| Primary category | physics.chem-ph |
| Published | 2 September 2026 |
| Last updated at source | 2 September 2026 |
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