{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T16:37:07Z","timestamp":1793205427533,"version":"4.5.0"},"reference-count":37,"publisher":"Wiley","issue":"40","license":[{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92572204"],"award-info":[{"award-number":["92572204"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Energy Materials"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Complex degradation trajectories compromise the lifetime reliability and operational safety of lithium\u2010ion batteries in advanced energy\u2010storage systems. Aging pathways induced by temperature, rate, and voltage\u2010abuse stresses are often entangled in conventional health\u2010estimation models, limiting transferable degradation representation and future\u2010trajectory updating under distribution shifts. Here, a generalizable, mechanism\u2010anchored health\u2010management framework is developed for lithium\u2010ion batteries under heterogeneous aging conditions. Using aging\u2010condition identification as a proxy task, we identify a degradation\u2010sensitive 3.3\u20133.4\u00a0V charging window in LiFePO\n                    <jats:sub>4<\/jats:sub>\n                    \/graphite cells, where statistically selected features are linked to incremental\u2010capacity fingerprints. These electrochemically anchored features are integrated with a condition\u2010aware soft mixture\u2010of\u2010experts model to disentangle heterogeneous feature\u2013state\u2010of\u2010health (SOH) relationships with and without condition labels during inference. Cross\u2010dataset continual learning enables adaptation to an unseen data source while mitigating catastrophic forgetting. Finally, data\u2010driven SOH observations are assimilated into a physics\u2010inspired parametric degradation model through an adaptive unscented Kalman filter, converting pointwise health estimates into online\u2010updatable degradation trajectories. The framework achieves robust SOH estimation across multi\u2010stress aging conditions and stable 100\u2013300\u2010step look\u2010ahead trajectory prediction, establishing an interpretable route from electrochemical fingerprints to trajectory\u2010level battery prognostics.\n                  <\/jats:p>","DOI":"10.1002\/aenm.71572","type":"journal-article","created":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T11:03:32Z","timestamp":1789124612000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generalizable Mechanism\u2010Anchored Health Management for Lithium\u2010Ion Batteries Across Complex Degradation Trajectories"],"prefix":"10.1002","volume":"16","author":[{"given":"Yuanzhe","family":"Tao","sequence":"first","affiliation":[{"name":"State Key Laboratory For Physical Chemistry of Solid Surface, College of Chemistry and Chemical Engineering, Collaborative Innovation Center of Chemistry for Energy 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