<\/p>\n\n\n\n
Proton-conducting solid acids could enable water-free operation of high-temperature fuel cells. However, systematic materials screening has, hitherto, been computationally prohibitive. Here, we introduce a two-stage high-throughput screening strategy that directly computes proton diffusion coefficients, enabled by machine-learned interatomic potentials fine-tuned to ab initio data. Starting from more than six million materials, our screening\u2014based on structural motifs rather than empirical descriptors\u2014identifies 27 high-performing proton conductors, including over ten previously unexplored compounds. These include sustainable and commercially available materials, candidates that have not yet been synthesized, organic systems that fall outside conventional design rules, and known proton conductors that validate our approach. Importantly, our findings reveal a universal oxygen\u2013oxygen distance of approximately 2.5 \u212b at the moment of proton transfer across diverse chemistries, providing mechanistic insight and showing that macroscopic proton conductivity emerges from the interplay between anion rotational dynamics, hydrogen-bond network connectivity, and proton-transfer probability. Proton-conducting solid acids could enable water-free high-temperature fuel cells, but systematic screening is computationally prohibitive. Here, the authors present a high-throughput screening framework that identifies 27 promising proton conductors from over six million materials and reveals a universal ~ 2.5\u212b proton-transfer distance.<\/p>\n","protected":false},"excerpt":{"rendered":"
Proton-conducting solid acids could enable water-free operation of high-temperature fuel cells. However, systematic materials screening has, hitherto, been computationally prohibitive. Here, we introduce a two-stage high-throughput screening strategy that directly computes proton diffusion coefficients, enabled by machine-learned interatomic potentials fine-tuned to ab initio data. Starting from more than six million materials, our screening\u2014based on structural […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":[{"type":"text","value":"Jonas Hänseroth","user_id":0},{"type":"text","value":"Max Großmann","user_id":0},{"type":"text","value":"M. 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