A Rapid in-situ Method to Identify the Cathode Type of End-of-Life Lithium-Ion Batteries by X-ray Fluorescence Spectroscopy for Optimizing Battery Recycling

A Rapid in-situ Method to Identify the Cathode Type of End-of-Life Lithium-Ion Batteries by X-ray Fluorescence Spectroscopy for Optimizing Battery Recycling | 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 Article A Rapid in-situ Method to Identify the Cathode Type of End-of-Life Lithium-Ion Batteries by X-ray Fluorescence Spectroscopy for Optimizing Battery Recycling Feihong Ren, Vladimir Vidal, Andrea Campos, Florence Vacandio, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6355085/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Mar, 2026 Read the published version in Communications Engineering → Version 1 posted You are reading this latest preprint version Abstract Lithium-ion batteries (LIBs) are extensively used for diverse applications including electric vehicles, hence resulting in an increasing number of end-of-life (EOL) LIBs that require efficient disposal and recycling. Although there are some established recycling processes for cathode materials, which are the most expensive and chemically complex components of LIBs, a rapid identification technology for the cathode chemical type is still needed to optimize recycling. We developed a rapid method that combines X-ray fluorescence (XRF) spectroscopy and multivariate analysis to classify and identify the chemical information for whole EOL LIBs. After disassembling the batteries, the chemical composition of the cathode materials was analyzed by XRF, scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS), and inductively coupled plasma optical emission spectrometry (ICP-OES). We demonstrate it is possible to use XRF technology to directly identify the types of cathode materials in EOL LIBs without disassembling in the optic of sorting metal before extraction. Earth and environmental sciences/Environmental sciences/Environmental chemistry/Pollution remediation Physical sciences/Energy science and technology/Energy storage/Batteries Physical sciences/Chemistry/Analytical chemistry Physical sciences/Materials science/Materials for energy and catalysis/Batteries Physical sciences/Engineering/Chemical engineering battery sorting categorization classification cathode materials characterization multivariate analysis Full Text Additional Declarations There is NO Competing Interest. Supplementary Files supportinginformation.pdf Supporting information Cite Share Download PDF Status: Published Journal Publication published 02 Mar, 2026 Read the published version in Communications Engineering → 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. 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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-6355085","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":437421403,"identity":"e5fb9615-f9c0-49db-84c5-0462df355898","order_by":0,"name":"Feihong 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