{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T17:55:14Z","timestamp":1782323714133,"version":"3.54.5"},"reference-count":22,"publisher":"Wiley","issue":"27","license":[{"start":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:00:00Z","timestamp":1760400000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52474328"],"award-info":[{"award-number":["52474328"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Comput Chem"],"published-print":{"date-parts":[[2025,10,15]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>LiF\u2010SmF<jats:sub>3<\/jats:sub> systems are the basic medium for the electrolytic preparation of Sm\u2010Fe alloys by molten salt electrolysis. An in\u2010depth analysis of its properties and local structural features is of great theoretical and practical significance for optimizing the electrolytic preparation process of Sm\u2010Fe alloys. Owing to the long lead time and high cost of systematic measurements of the properties of high\u2010temperature fluoride molten salts, machine learning\u2010based calculations have become an efficient way to obtain the properties and structural features of molten salt systems. In this study, a machine learning potential model for the analysis of LiF\u2010SmF<jats:sub>3<\/jats:sub> systems is developed. Its computational accuracy can reach 96.92%, with root\u2010mean\u2010square deviations of 5.48\u2009\u00d7\u200910<jats:sup>\u22123<\/jats:sup>\u2009eV\/atom and 6.23\u2009\u00d7\u200910<jats:sup>\u22122<\/jats:sup>\u2009eV\/\u00c5 for energy and force, respectively, indicating an accuracy comparable to that of density functional calculations. The machine learning potential model was used to perform molecular dynamics simulations of the LiF\u2010SmF<jats:sub>3<\/jats:sub> system in the temperature range of 1100\u20131350\u2009K. The density and viscosity of the system were calculated, and their deviations from the experimental measurements ranged from about 1.03%\u20132.77% and 3.36%\u20134.58%, respectively. The ion self\u2010diffusion coefficients of the system were calculated, and the structural features of the system were analyzed using the radial distribution function of the ion pairs.<\/jats:p>","DOI":"10.1002\/jcc.70246","type":"journal-article","created":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T12:38:26Z","timestamp":1760445506000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Machine Learning\u2010Driven Molecular Dynamics Study of\u00a0<scp>LiF<\/scp>\u2010<scp>SmF<sub>3<\/sub><\/scp> Molten Salts"],"prefix":"10.1002","volume":"46","author":[{"given":"Fei","family":"Liu","sequence":"first","affiliation":[{"name":"School of Metallurgical Engineering Jiangxi University of Science and Technology  Ganzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kailei","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Metallurgical Engineering Jiangxi University of Science and Technology  Ganzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7051-6983","authenticated-orcid":false,"given":"Xu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Metallurgical Engineering Jiangxi University of Science and Technology  Ganzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,10,14]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12598-017-0943-4"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12598-015-0584-4"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12613-020-2228-4"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jallcom.2018.03.048"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1134\/S106377452003013X"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmst.2020.09.040"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1039\/D3TA03434H"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ces.2024.119836"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/adts.202000180"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1063\/5.0007045"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2004.12.014"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/00268979709482119"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1063\/1.2770708"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.54.1703"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.77.3865"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1063\/1.3382344"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/jcc.21224"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2020.107206"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2018.03.016"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2021.108171"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnucmat.2012.12.006"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.commatsci.2015.09.052"}],"container-title":["Journal of Computational Chemistry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jcc.70246","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T19:47:48Z","timestamp":1760557668000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/jcc.70246"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,14]]},"references-count":22,"journal-issue":{"issue":"27","published-print":{"date-parts":[[2025,10,15]]}},"alternative-id":["10.1002\/jcc.70246"],"URL":"https:\/\/doi.org\/10.1002\/jcc.70246","archive":["Portico"],"relation":{},"ISSN":["0192-8651","1096-987X"],"issn-type":[{"value":"0192-8651","type":"print"},{"value":"1096-987X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,14]]},"assertion":[{"value":"2025-07-02","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-09-22","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70246"}}