Selectivity descriptors for the direct hydrogenation of CO2 to hydrocarbons during zeolite-mediated bifunctional catalysis

Adrian Ramirez, Xuan Gong, Mustafa Caglayan, Stefan-Adrian F. Nastase, Edy Abou-Hamad, Lieven Gevers, Luigi Cavallo, Abhishek Dutta Chowdhury () and Jorge Gascon ()
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Adrian Ramirez: King Abdullah University of Science and Technology (KAUST)
Xuan Gong: Wuhan University
Mustafa Caglayan: King Abdullah University of Science and Technology (KAUST)
Stefan-Adrian F. Nastase: King Abdullah University of Science and Technology (KAUST)
Edy Abou-Hamad: King Abdullah University of Science and Technology (KAUST)
Lieven Gevers: King Abdullah University of Science and Technology (KAUST)
Luigi Cavallo: King Abdullah University of Science and Technology (KAUST)
Abhishek Dutta Chowdhury: Wuhan University
Jorge Gascon: King Abdullah University of Science and Technology (KAUST)

Nature Communications, 2021, vol. 12, issue 1, 1-13

Abstract: Abstract Cascade processes are gaining momentum in heterogeneous catalysis. The combination of several catalytic solids within one reactor has shown great promise for the one-step valorization of C1-feedstocks. The combination of metal-based catalysts and zeolites in the gas phase hydrogenation of CO2 leads to a large degree of product selectivity control, defined mainly by zeolites. However, a great deal of mechanistic understanding remains unclear: metal-based catalysts usually lead to complex product compositions that may result in unexpected zeolite reactivity. Here we present an in-depth multivariate analysis of the chemistry involved in eight different zeolite topologies when combined with a highly active Fe-based catalyst in the hydrogenation of CO2 to olefins, aromatics, and paraffins. Solid-state NMR spectroscopy and computational analysis demonstrate that the hybrid nature of the active zeolite catalyst and its preferred CO2-derived reaction intermediates (CO/ester/ketone/hydrocarbons, i.e., inorganic-organic supramolecular reactive centers), along with 10 MR-zeolite topology, act as descriptors governing the ultimate product selectivity.

Date: 2021
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DOI: 10.1038/s41467-021-26090-5

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