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Here, we employ a large language model (LLM)\u2010driven screening workflow to efficiently shortlist crosslinkers from a curated knowledge base, guiding the rational design of a hybrid dual network (H\u2010DN) membrane. The workflow identifies N,N,N\u2032,N\u2032\u2010tetramethylethylenediamine as the optimal candidate to build a robust, chemically crosslinked polysulfone network interpenetrated within a widely used sulfonated poly(ether ether ketone) (SPEEK) matrix. Mechanistically, the in situ formed quaternary ammonium motifs strongly ion\u2010pair with sulfonic acid groups, effectively suppressing chain motion without blocking ion transport channels. Consequently, the H\u2010DN membrane exhibits a 68% reduction in swelling and an ultra\u2010high wet\u2010state hardness of 216\u00a0MPa (a sixfold increase over SPEEK), while retaining high ionic conductivity (10.7 mS cm\n                    <jats:sup>\u22121<\/jats:sup>\n                    ). Enabled by this mechanically robust and highly selective architecture, the alkaline zinc\u2010iron flow battery achieves an energy efficiency of 88.87% at a challenging areal capacity of 240 mAh cm\n                    <jats:sup>\u22122<\/jats:sup>\n                    and operates stably for over 820\u00a0h without dendrite\u2010induced failure, which surpassed the commercial Nafion212 and SPEEK benchmarks by threefold and sevenfold, respectively. This work establishes a paradigm for LLM\u2010accelerated material discovery in addressing the stability\u2010selectivity dilemma of ion\u2010exchange membranes.\n                  <\/jats:p>","DOI":"10.1002\/smll.73664","type":"journal-article","created":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T08:34:31Z","timestamp":1778056471000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Large Language Model\u2010Guided Design of Anti\u2010Swelling Hybrid Dual Network Membranes for Long\u2010Duration Alkaline Zinc Iron Flow Batteries"],"prefix":"10.1002","volume":"22","author":[{"given":"Yu","family":"Mu","sequence":"first","affiliation":[{"name":"School of Materials Science and Engineering Anhui University  Hefei China"},{"name":"Faculty of Materials Science and Energy Engineering Shenzhen University of Advanced Technology  Shenzhen 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