Growth rate-dependent lithium isotope fractionation derived from machine learning-enabled molecular simulation

Growth rate-dependent lithium isotope fractionation derived from machine learning-enabled molecular simulation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Physical Sciences - Article Growth rate-dependent lithium isotope fractionation derived from machine learning-enabled molecular simulation Xiancai Lu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8885037/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Lithium (Li) isotopes have emerged as a promising tracer for various geological processes and clay minerals serve as key Li carriers in Earth surface systems, but the underlying mechanism driving Li isotope fractionation remains poorly understood. Based on a deep potential (DP) trained with density functional theory (DFT) data, path integral molecular dynamic (PIMD) simulations reveal the equilibrium and kinetic Li fractionation factors of -11.5‰ and -23.5‰ during clay precipitation, respectively. Further modeling indicates that high clay growth rate intensifies Li isotope fractionation, which can be well described by the surface kinetic model. The unified mechanistic framework involving equilibrium and kinetic fractionation not only elucidates the intrinsic Li isotopic fractionation factors and pH dependencies observed in both natural and experimental contexts, but also highlights the critical roles of reactive kinetic fractionation during rapid clay precipitation, such as estuarine and hydrothermal systems. Earth and environmental sciences/Solid Earth sciences/Geochemistry Physical sciences/Chemistry/Theoretical chemistry/Computational chemistry Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryInformation.docx Supplementary Information Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8885037","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Physical Sciences - Article","associatedPublications":[],"authors":[{"id":592141056,"identity":"3ed1ad99-e465-4280-9d65-68cc574bbc69","order_by":0,"name":"Xiancai Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYFAC5gYDBgYbBsYGIJuHOC2MIC1pJGoBEochbKK0GBw/2FDMu+N8HvOMBMYHb9sY5M0JaZHsSWww5j1zu5hxRgKz4dw2BsOdDQS08EswArW03U5snJHAJs3bxpBgcICAFjaIlnMgLey/idICteUA2BZmorSA/AL0QnJiY8/DZsk55yQMNxDSYnD88DGDt212iRvbkw9+eFNmI0/QFpB3DECkYQM4giQIqwcC5gcgUp4otaNgFIyCUTAiAQAW/T3y58uLYwAAAABJRU5ErkJggg==","orcid":"","institution":"Nanjing University","correspondingAuthor":true,"prefix":"","firstName":"Xiancai","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2026-02-15 09:35:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8885037/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8885037/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104397589,"identity":"ddb1e16c-bcd8-4c6d-b9c9-6733b1870dfb","added_by":"auto","created_at":"2026-03-11 11:52:27","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":956272,"visible":true,"origin":"","legend":"","description":"","filename":"Mainmanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8885037/v1_covered_e07ba306-413e-4191-bcde-410727f19d2b.pdf"},{"id":103188906,"identity":"2fff97c3-0970-4c38-a5f7-917b2ccd7408","added_by":"auto","created_at":"2026-02-23 00:22:38","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1196827,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8885037/v1/89b6792f96c695f5686c79ad.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Growth rate-dependent lithium isotope fractionation derived from machine learning-enabled molecular simulation","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8885037/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8885037/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Lithium (Li) isotopes have emerged as a promising tracer for various geological processes and clay minerals serve as key Li carriers in Earth surface systems, but the underlying mechanism driving Li isotope fractionation remains poorly understood. Based on a deep potential (DP) trained with density functional theory (DFT) data, path integral molecular dynamic (PIMD) simulations reveal the equilibrium and kinetic Li fractionation factors of -11.5‰ and -23.5‰ during clay precipitation, respectively. Further modeling indicates that high clay growth rate intensifies Li isotope fractionation, which can be well described by the surface kinetic model. 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