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Here, we establish an interpretable machine\u2010learning\u2010guided design framework that quantitatively links ionic descriptors with polarization behavior in ABO\n                    <jats:sub>3<\/jats:sub>\n                    \u2010based dielectric matrices, enabling the rational identification of compositions with intrinsically high polarization potential. Guided by this strategy, a (Bi\n                    <jats:sub>0.275<\/jats:sub>\n                    Na\n                    <jats:sub>0.2255<\/jats:sub>\n                    K\n                    <jats:sub>0.0495<\/jats:sub>\n                    Ba\n                    <jats:sub>0.3<\/jats:sub>\n                    )(Ti\n                    <jats:sub>0.985<\/jats:sub>\n                    Hf\n                    <jats:sub>0.015<\/jats:sub>\n                    )O\n                    <jats:sub>3<\/jats:sub>\n                    \u20100.15(La\n                    <jats:sub>0.5<\/jats:sub>\n                    Sm\n                    <jats:sub>0.5<\/jats:sub>\n                    )\n                    <jats:sub>2<\/jats:sub>\n                    Ti\n                    <jats:sub>2<\/jats:sub>\n                    O\n                    <jats:sub>7<\/jats:sub>\n                    (BNBT\u20103) composition is discovered that exhibits an exceptional maximum polarization of 50.19 \u00b5C cm\n                    <jats:sup>\u22122<\/jats:sup>\n                    . When processed via a viscous polymer process, the resulting BNBT\u20103\u2010VPP capacitors achieve an ultrahigh breakdown strength of 1400\u00a0kV cm\n                    <jats:sup>\u22121<\/jats:sup>\n                    and a recoverable energy density of 25.1 J cm\n                    <jats:sup>\u22123<\/jats:sup>\n                    with high efficiency, placing them among the best\u2010performing lead\u2010free dielectric ceramics reported to date. Structural characterization combined with phase\u2010field simulations reveals that the outstanding performance originates from polarization\u2010lattice decoupling, where nanoscale polarization clusters and multiphase coexistence suppress long\u2010range ferroelectric order while enabling reversible polarization rotation. This work establishes a generalizable strategy that integrates interpretable machine learning with physically grounded materials design, providing a powerful route for discovering high\u2010performance dielectric energy storage materials.\n                  <\/jats:p>","DOI":"10.1002\/adma.73801","type":"journal-article","created":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T14:03:21Z","timestamp":1785938601000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Machine\u2010Learning\u2010Guided Polarization\u2010Lattice Decoupling Enables Ultrahigh Energy Storage in Lead\u2010Free Dielectric Ceramics"],"prefix":"10.1002","author":[{"given":"Zixiong","family":"Sun","sequence":"first","affiliation":[{"name":"School of Electronic Information and Artificial Intelligence Shaanxi University of Science and Technology  Xi'an 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Science and Engineering Harbin Institute of Technology  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Lei","sequence":"additional","affiliation":[{"name":"School of Electronic Information and Artificial Intelligence Shaanxi University of Science and Technology  Xi'an China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"He","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Materials Science and Technology Hainan University  Hainan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7144-1861","authenticated-orcid":false,"given":"Zibin","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering The Hong Kong Polytechnic University  Hong Kong 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