{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:53:56Z","timestamp":1792785236612,"version":"4.5.0"},"reference-count":39,"publisher":"National Academy of Sciences","issue":"42","license":[{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"JSPS KAKENHI","award":["JP25H01508"],"award-info":[{"award-number":["JP25H01508"]}]},{"name":"JSPS KAKENHI","award":["JP25K17991"],"award-info":[{"award-number":["JP25K17991"]}]},{"name":"JSPS KAKENHI","award":["JP24K23068"],"award-info":[{"award-number":["JP24K23068"]}]},{"name":"National Natural Science Foundation of China","award":["22309109"],"award-info":[{"award-number":["22309109"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2026,10,20]]},"abstract":"<jats:p>Aluminum nanoparticles (ANPs) are among the most energy-dense solid fuels, yet the atomic mechanisms governing their transition from passivated particles to highly reactive states remain elusive. This stems from a fundamental computational bottleneck: Ab initio methods offer quantum-level fidelity but are restricted to small spatiotemporal scales (&lt;500 atoms, picoseconds), while empirical force fields lack the reactive fidelity required for complex combustion environments. Here, we bridge this gap by employing a human-audited, multiagent framework to make the development and validation of a task-specific machine learning potential (MLP) more traceable and auditable. The workflow coordinates active learning, model evaluation, validation evidence, and human expert review, while leaving scientific interpretation and model-use decisions under researcher control. This collaborative cycle ensures quantum mechanical accuracy while exhibiting near-linear scalability. Strikingly, our simulations reveal a temperature-regulated dual-mode oxidation mechanism: At moderate temperatures, the oxide shell acts as a dynamic \u201cgatekeeper,\u201d regulating oxidation through a \u201cbreathing mode\u201d of transient nanochannels; above a critical threshold, a \u201crupture mode\u201d leads to shell failure and rapid combustion. Importantly, we resolve a decades-old controversy by demonstrating that aluminum cation outward diffusion, rather than oxygen transport, dominates mass transfer in studied regimes, with diffusion coefficients consistently exceeding those of oxygen by 2 to 3 orders of magnitude. These results provide an atomistic framework for interpreting ANP reactivity and illustrate how human-audited agentic workflows can make domain-specific reactive MLP development and deployment more reproducible.<\/jats:p>","DOI":"10.1073\/pnas.2537780123","type":"journal-article","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T17:37:33Z","timestamp":1792085853000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":0,"title":["Multi-AI agent framework reveals the \u201coxide gatekeeper\u201d in aluminum nanoparticle oxidation"],"prefix":"10.1073","volume":"123","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-6161-1505","authenticated-orcid":false,"given":"Yiming","family":"Lu","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01dq60k83","id-type":"ROR","asserted-by":"publisher"}],"name":"Advanced Institute for Materials Research (WPI-AIMR), Tohoku University","place":["Sendai, Japan"]},{"id":[{"id":"https:\/\/ror.org\/023hj5876","id-type":"ROR","asserted-by":"publisher"}],"name":"School of Chemical Engineering, Dalian University of Technology","place":["Dalian, China"]},{"name":"Suzhou MatSource Technology Co., Ltd.","place":["Suzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6620-9516","authenticated-orcid":false,"given":"Tingyu","family":"Lu","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01dq60k83","id-type":"ROR","asserted-by":"publisher"}],"name":"Advanced Institute for Materials Research (WPI-AIMR), Tohoku University","place":["Sendai, Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6347-9344","authenticated-orcid":false,"given":"Di","family":"Zhang","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01dq60k83","id-type":"ROR","asserted-by":"publisher"}],"name":"Advanced Institute for Materials Research (WPI-AIMR), Tohoku University","place":["Sendai, Japan"]},{"id":[{"id":"https:\/\/ror.org\/01dq60k83","id-type":"ROR","asserted-by":"publisher"}],"name":"Frontier Research Institute for Interdisciplinary Sciences, Tohoku University","place":["Sendai, Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Ye","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/023hj5876","id-type":"ROR","asserted-by":"publisher"}],"name":"School of Chemical Engineering, Dalian University of Technology","place":["Dalian, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7577-1366","authenticated-orcid":false,"given":"Hao","family":"Li","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01dq60k83","id-type":"ROR","asserted-by":"publisher"}],"name":"Advanced Institute for Materials Research (WPI-AIMR), Tohoku University","place":["Sendai, Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2026,10,15]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1021\/acsomega.0c03387"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.pecs.2008.09.001"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.3390\/nano14191574"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11705-018-1702-2"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1080\/00102200903341561"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1063\/1.2335362"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpcc.5b04650"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.3390\/ma12091368"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1021\/acsomega.1c03502"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1063\/1.4823984"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1038\/s42254-022-00470-2"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-71007-z"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1021\/jp004368u"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpclett.1c03867"},{"key":"e_1_3_4_15_2","doi-asserted-by":"crossref","unstructured":"I. Batatia D. P. Kov\u00e1cs G. N. C. Simm C. Ortner G. Cs\u00e1nyi MACE: Higher order equivariant message passing neural networks for fast and accurate force fields. arXiv [Preprint] (2023). https:\/\/doi.org\/10.48550\/arXiv.2206.07697 (Accessed 30 September 2026).","DOI":"10.52202\/068431-0830"},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-29939-5"},{"key":"e_1_3_4_17_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jctc.9b00181"},{"key":"e_1_3_4_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2018.03.016"},{"key":"e_1_3_4_19_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpclett.4c02224"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2020.107206"},{"key":"e_1_3_4_21_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-44525-z"},{"key":"e_1_3_4_22_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-026-10265-5"},{"key":"e_1_3_4_23_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06792-0"},{"key":"e_1_3_4_24_2","doi-asserted-by":"publisher","DOI":"10.1088\/2632-2153\/ae4b07"},{"key":"e_1_3_4_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.matt.2025.102263"},{"key":"e_1_3_4_26_2","unstructured":"Z. Wang DREAMS: Density functional theory based research engine for agentic materials simulation. arXiv [Preprint] (2025). https:\/\/doi.org\/10.48550\/arXiv.2507.14267 (Accessed 30 September 2026)."},{"key":"e_1_3_4_27_2","doi-asserted-by":"publisher","DOI":"10.1038\/s42004-025-01776-9"},{"key":"e_1_3_4_28_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.87.184115"},{"key":"e_1_3_4_29_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41524-018-0096-5"},{"key":"e_1_3_4_30_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12274-019-2593-3"},{"key":"e_1_3_4_31_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0506-8"},{"key":"e_1_3_4_32_2","doi-asserted-by":"publisher","DOI":"10.1021\/acsnano.8b07633"},{"key":"e_1_3_4_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.combustflame.2005.12.017"},{"key":"e_1_3_4_34_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpcc.5c01237"},{"key":"e_1_3_4_35_2","doi-asserted-by":"publisher","DOI":"10.3390\/nano14030265"},{"key":"e_1_3_4_36_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.commatsci.2018.04.054"},{"key":"e_1_3_4_37_2","doi-asserted-by":"publisher","DOI":"10.1063\/5.0007045"},{"key":"e_1_3_4_38_2","unstructured":"Y. Lu T. Lu D. Zhang H. Li Digital automation for scientific discovery. DFT Database. https:\/\/www.digauto.org\/dft-database. Accessed 30 September 2026."},{"key":"e_1_3_4_39_2","unstructured":"Y. Lu T. Lu D. Zhang H. Li MLP Copilot. GitHub. https:\/\/github.com\/flarecentury\/mlpcopilot. Accessed 30 September 2026."}],"container-title":["Proceedings of the National Academy of Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pnas.org\/doi\/pdf\/10.1073\/pnas.2537780123","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T17:37:39Z","timestamp":1792085859000},"score":1,"resource":{"primary":{"URL":"https:\/\/pnas.org\/doi\/10.1073\/pnas.2537780123"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,15]]},"references-count":39,"journal-issue":{"issue":"42","published-print":{"date-parts":[[2026,10,20]]}},"alternative-id":["10.1073\/pnas.2537780123"],"URL":"https:\/\/doi.org\/10.1073\/pnas.2537780123","relation":{},"ISSN":["0027-8424","1091-6490"],"issn-type":[{"value":"0027-8424","type":"print"},{"value":"1091-6490","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,15]]},"assertion":[{"value":"2026-01-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-01","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-10-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e2537780123"}}