RefXAS : an open access database of X-ray absorption spectra – improvements and outlook
Paripsa, S. ; Gaur, A. 1; Förste, F.; Doronkin, D. E.
1,2; Malzer, W.; Schlesiger, C.; Kanngießer, B.; Welter, E.; Grunwaldt, J-D.
1,2; Lützenkirchen-Hecht, D.
1 Institut für Technische Chemie und Polymerchemie (ITCP), Karlsruher Institut für Technologie (KIT)
2 Institut für Katalyseforschung und -technologie (IKFT), Karlsruher Institut für Technologie (KIT)
1,2; Malzer, W.; Schlesiger, C.; Kanngießer, B.; Welter, E.; Grunwaldt, J-D.
1,2; Lützenkirchen-Hecht, D.1 Institut für Technische Chemie und Polymerchemie (ITCP), Karlsruher Institut für Technologie (KIT)
2 Institut für Katalyseforschung und -technologie (IKFT), Karlsruher Institut für Technologie (KIT)
Abstract:
Under the DAPHNE4NFDI consortium, RefXAS has evolved as a
comprehensive open-access database for X-ray absorption spectroscopy (XAS).
We have implemented a platform that allows users to submit raw datasets and
associated metadata via a web interface. The database supports automated
metadata handling and quality control, ensuring that uploaded data adheres to
predefined standards. Recent developments include the integration of a
standardised download package, improved filtering systems, and the transition to
institutional data storage at DESY, alongside future plans to incorporate the NeXus
format, enhancing machine learning applications. This paper provides an
overview of these advancements and their implications for the XAS community.
comprehensive open-access database for X-ray absorption spectroscopy (XAS).
We have implemented a platform that allows users to submit raw datasets and
associated metadata via a web interface. The database supports automated
metadata handling and quality control, ensuring that uploaded data adheres to
predefined standards. Recent developments include the integration of a
standardised download package, improved filtering systems, and the transition to
institutional data storage at DESY, alongside future plans to incorporate the NeXus
format, enhancing machine learning applications. This paper provides an
overview of these advancements and their implications for the XAS community.
| Zugehörige Institution(en) am KIT | Institut für Katalyseforschung und -technologie (IKFT) Institut für Technische Chemie und Polymerchemie (ITCP) |
| Publikationstyp | Zeitschriftenaufsatz |
| Publikationsdatum | 01.05.2025 |
| Sprache | Englisch |
| Identifikator | ISSN: 1742-6588, 1742-6596 KITopen-ID: 1000183788 |
| HGF-Programm | 38.03.02 (POF IV, LK 01) Power-based Fuels and Chemicals |
| Erschienen in | Journal of Physics: Conference Series |
| Verlag | Institute of Physics Publishing Ltd (IOP Publishing Ltd) |
| Band | 3010 |
| Heft | 1 |
| Seiten | 012124 |
| Nachgewiesen in | Dimensions OpenAlex Scopus |