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Multivariate data analysis for laser-induced XUV spectroscopy (LIXS)

  • The application of multivariate data analysis is essential in extracting the full potential of laser-induced XUV spectroscopy (LIXS) for high-precision elemental mapping. LIXS offers significant advantages over traditional laser-induced breakdown spectroscopy in UV-vis (LIBS), including higher precision and a wider dynamic range,[1,2] while making it possible to determine light elements like lithium and fluorine. However, it is challenged by the presence of unresolved transition arrays (UTAs) for heavier elements. These UTAs add considerable complexity to the spectral data, often concealing crucial information. In this study, we employ well-established multivariate data analysis techniques and intensive data preprocessing to unravel this contained information. The refined analysis reveals a high level of detail, enabling the precise identification of inhomogeneities within material samples. Our approach has particular relevance for studying aging processes in lithium-ion batteriesThe application of multivariate data analysis is essential in extracting the full potential of laser-induced XUV spectroscopy (LIXS) for high-precision elemental mapping. LIXS offers significant advantages over traditional laser-induced breakdown spectroscopy in UV-vis (LIBS), including higher precision and a wider dynamic range,[1,2] while making it possible to determine light elements like lithium and fluorine. However, it is challenged by the presence of unresolved transition arrays (UTAs) for heavier elements. These UTAs add considerable complexity to the spectral data, often concealing crucial information. In this study, we employ well-established multivariate data analysis techniques and intensive data preprocessing to unravel this contained information. The refined analysis reveals a high level of detail, enabling the precise identification of inhomogeneities within material samples. Our approach has particular relevance for studying aging processes in lithium-ion batteries (LIBs), specifically in relation to varying cathode materials and fluorine-containing polymer binder content. By combining elemental distribution with structural information, this improved method can offer a more comprehensive understanding of sample inhomogeneities and aging processes in LIBs, contributing to the development of more reliable and sustainable battery technologies.zeige mehrzeige weniger

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Metadaten
Autor*innen:Alexander WinckelmannORCiD
Koautor*innen:A. Wichser, Carlos Enrique Abad Andrade, D. Bleiner
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2023
Organisationseinheit der BAM:1 Analytische Chemie; Referenzmaterialien
1 Analytische Chemie; Referenzmaterialien / 1.6 Anorganische Referenzmaterialien
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Freie Schlagwörter:Laser-induced XUV spectroscopy; Lithium Ion Batteries; Multivariate data analysis
Themenfelder/Aktivitätsfelder der BAM:Chemie und Prozesstechnik
Chemie und Prozesstechnik / Chemische Charakterisierung und Spurenanalytik
Veranstaltung:Berliner Chemie in Praxis Symposium - BCPS 2023
Veranstaltungsort:Berlin, Germany
Beginndatum der Veranstaltung:06.10.2023
Enddatum der Veranstaltung:06.10.2023
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:17.10.2023
Referierte Publikation:Nein
Eingeladener Vortrag:Nein
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