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High-resolution absorption isotopic spectrometry as a tool for aging studies of Li-ion batteries

  • Lithium (Li) is the key element in the manufacturing of batteries. Isotopic study of Li may help to identify the causes of battery aging due to isotopic fractionation during charge/discharge cycles. Isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←22S electronic transition around 670.788 nm. In this work, we propose improvements to our previous work [1] by using a higher-resolution double echelle modular spectrometer (HR-DEMON II) coupled to a continuum source graphite furnace atomic absorption spectrometer (HR-CS-GF-AAS) for the isotopic analysis of Li. The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm (XGBoost). A set of samples with 6Li isotope amount fractions ranging from 0.0004 to 0.99 mol mol-1 was used for the algorithm's training. Subsequently, the procedure was validated by a set of stock chemicalsLithium (Li) is the key element in the manufacturing of batteries. Isotopic study of Li may help to identify the causes of battery aging due to isotopic fractionation during charge/discharge cycles. Isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←22S electronic transition around 670.788 nm. In this work, we propose improvements to our previous work [1] by using a higher-resolution double echelle modular spectrometer (HR-DEMON II) coupled to a continuum source graphite furnace atomic absorption spectrometer (HR-CS-GF-AAS) for the isotopic analysis of Li. The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm (XGBoost). A set of samples with 6Li isotope amount fractions ranging from 0.0004 to 0.99 mol mol-1 was used for the algorithm's training. Subsequently, the procedure was validated by a set of stock chemicals (Li2CO3, LiNO3, LiCl, and LiOH) and a BAM candidate reference material, a cathode material (NMC111). Finally, the ML model was applied to determine the isotope ratio of geological samples, including anorthosite, granite, soil, rhyolite, nepheline syenite, and basalt and battery samples. These samples were measured as digested without any further purification step. Improvements in the optical resolution resolve the lithium isotopic components of the atomic spectra. In the studied geological samples, were found δ7Li values between -0.5 and 4.5 ‰ with a precision range of 1 to 2 ‰. In addition, the proposed method was validated with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), and these results are comparable and compatible.zeige mehrzeige weniger

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Metadaten
Autor*innen:Dalia Morcillo
Koautor*innen:Alexander Winckelmann, Silke Richter, Sebastian Recknagel, Lars Jacobsen, Daniel Frick, Anita Schmidt, Robert Leonhardt, Ulrich Panne, Carlos Enrique Abad Andrade
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2022
Organisationseinheit der BAM:1 Analytische Chemie; Referenzmaterialien
1 Analytische Chemie; Referenzmaterialien / 1.6 Anorganische Referenzmaterialien
3 Gefahrgutumschließungen; Energiespeicher
3 Gefahrgutumschließungen; Energiespeicher / 3.1 Sicherheit von Gefahrgutverpackungen und Batterien
P Präsident
P Präsident / P.0 Präsident und andere
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Angewandte Physik
Freie Schlagwörter:Battery; High-resolution absorption isotopic spectrometry; Lithium isotope; Machine learning
Themenfelder/Aktivitätsfelder der BAM:Chemie und Prozesstechnik
Chemie und Prozesstechnik / Chemische Charakterisierung und Spurenanalytik
Energie
Energie / Elektrische Energiespeicher und -umwandlung
Veranstaltung:Caltech-BAM Meeting
Veranstaltungsort:Online meeting
Beginndatum der Veranstaltung:10.08.2022
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:29.11.2022
Referierte Publikation:Nein
Eingeladener Vortrag:Nein
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