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Author: Kondratenko, Evgenii V. × End date: 2019 × Start date: 2010 × Publisher: [London] : Nature Publishing Group UK × WGL Institute: LIKAT ×

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    Control of coordinatively unsaturated Zr sites in ZrO2 for efficient C–H bond activation
    ([London] : Nature Publishing Group UK, 2018) Zhang, Yaoyuan; Zhao, Yun; Otroshchenko, Tatiana; Lund, Henrik; Pohl, Marga-Martina; Rodemerck, Uwe; Linke, David; Jiao, Haijun; Jiang, Guiyuan; Kondratenko, Evgenii V.
    Due to the complexity of heterogeneous catalysts, identification of active sites and the ways for their experimental design are not inherently straightforward but important for tailored catalyst preparation. The present study reveals the active sites for efficient C–H bond activation in C1–C4 alkanes over ZrO2 free of any metals or metal oxides usually catalysing this reaction. Quantum chemical calculations suggest that two Zr cations located at an oxygen vacancy are responsible for the homolytic C–H bond dissociation. This pathway differs from that reported for other metal oxides used for alkane activation, where metal cation and neighbouring lattice oxygen form the active site. The concentration of anion vacancies in ZrO2 can be controlled through adjusting the crystallite size. Accordingly designed ZrO2 shows industrially relevant activity and durability in non-oxidative propane dehydrogenation and performs superior to state-of-the-art catalysts possessing Pt, CrOx, GaOx or VOx species.
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    A meta-analysis of catalytic literature data reveals property-performance correlations for the OCM reaction
    ([London] : Nature Publishing Group UK, 2019) Schmack, Roman; Friedrich, Alexandra; Kondratenko, Evgenii V.; Polte, Jörg; Werwatz, Axel; Kraehnert, Ralph
    Decades of catalysis research have created vast amounts of experimental data. Within these data, new insights into property-performance correlations are hidden. However, the incomplete nature and undefined structure of the data has so far prevented comprehensive knowledge extraction. We propose a meta-analysis method that identifies correlations between a catalyst’s physico-chemical properties and its performance in a particular reaction. The method unites literature data with textbook knowledge and statistical tools. Starting from a researcher’s chemical intuition, a hypothesis is formulated and tested against the data for statistical significance. Iterative hypothesis refinement yields simple, robust and interpretable chemical models. The derived insights can guide new fundamental research and the discovery of improved catalysts. We demonstrate and validate the method for the oxidative coupling of methane (OCM). The final model indicates that only well-performing catalysts provide under reaction conditions two independent functionalities, i.e. a thermodynamically stable carbonate and a thermally stable oxide support.