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Author Jenkinson, K.; Spadaro, M.C.; Golovanova, V.; Andreu, T.; Morante, J.R.; Arbiol, J.; Bals, S. url  doi
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  Title Direct operando visualization of metal support interactions induced by hydrogen spillover during CO₂ hydrogenation Type A1 Journal article
  Year (down) 2023 Publication Advanced materials Abbreviated Journal  
  Volume 35 Issue 51 Pages 2306447-10  
  Keywords A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)  
  Abstract The understanding of catalyst active sites is a fundamental challenge for the future rational design of optimized and bespoke catalysts. For instance, the partial reduction of Ce4+ surface sites to Ce3+ and the formation of oxygen vacancies are critical for CO2 hydrogenation, CO oxidation, and the water gas shift reaction. Furthermore, metal nanoparticles, the reducible support, and metal support interactions are prone to evolve under reaction conditions; therefore a catalyst structure must be characterized under operando conditions to identify active states and deduce structure-activity relationships. In the present work, temperature-induced morphological and chemical changes in Ni nanoparticle-decorated mesoporous CeO2 by means of in situ quantitative multimode electron tomography and in situ heating electron energy loss spectroscopy, respectively, are investigated. Moreover, operando electron energy loss spectroscopy is employed using a windowed gas cell and reveals the role of Ni-induced hydrogen spillover on active Ce3+ site formation and enhancement of the overall catalytic performance.  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos 001106139400001 Publication Date 2023-10-22  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0935-9648 ISBN Additional Links UA library record; WoS full record  
  Impact Factor 29.4 Times cited Open Access OpenAccess  
  Notes This work was supported by the funding received by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement no. 818776 – DYNAPOL, no. 770887 PICOMETRICS and no. 815128 REALNANO). The authors also acknowledge the computational resources provided by the Swiss National Supercomputing Center (CSCS), by CINECA, and the Research Foundation Flanders (FWO, Belgium) G.0346.21N.; Sygma_SB Approved Most recent IF: 29.4; 2023 IF: 19.791  
  Call Number UA @ admin @ c:irua:201143 Serial 9022  
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