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Probing active sites in Cux Pdy cluster catalysts by machine-learning-assisted X-ray absorption spectroscopy
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SYSNO ASEP 0544599 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Probing active sites in Cux Pdy cluster catalysts by machine-learning-assisted X-ray absorption spectroscopy Author(s) Liu, Y. (US)
Halder, A. (US)
Seifert, S. (US)
Marcella, N. (US)
Vajda, Štefan (UFCH-W) RID, ORCID
Frenkel, A. I. (US)Source Title ACS Applied Materials and Interfaces. - : American Chemical Society - ISSN 1944-8244
Roč. 13, č. 45 (2021), s. 53363-53374Number of pages 12 s. Language eng - English Country US - United States Keywords deep learning ; machine learning ; nanocatalysts ; nanoclusters ; size-selected clusters ; xanes Subject RIV CF - Physical ; Theoretical Chemistry OECD category Physical chemistry Method of publishing Limited access Institutional support UFCH-W - RVO:61388955 UT WOS 000752870800007 EID SCOPUS 85111204787 DOI 10.1021/acsami.1c06714 Annotation Size-selected clusters are important model catalysts because of their narrow size and compositional distributions, as well as enhanced activity and selectivity in many reactions. Still, their structure-activity relationships are, in general, elusive. The main reason is the difficulty in identifying and quantitatively characterizing the catalytic active site in the clusters when it is confined within subnanometric dimensions and under the continuous structural changes the clusters can undergo in reaction conditions. Using machine learning approaches for analysis of the operando X-ray absorption near-edge structure spectra, we obtained accurate speciation of the CuxPdy cluster types during the propane oxidation reaction and the structural information about each type. As a result, we elucidated the information about active species and relative roles of Cu and Pd in the clusters. Workplace J. Heyrovsky Institute of Physical Chemistry Contact Michaela Knapová, michaela.knapova@jh-inst.cas.cz, Tel.: 266 053 196 Year of Publishing 2022 Electronic address http://hdl.handle.net/11104/0321438
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