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    Dual Experimental and Computational Approach to Elucidate the Effect of Ga on Cu/Ceo2–Zro2 Catalyst for Co2 Hydrogenation

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    SSRN-id4162690.pdf
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    Type
    Preprint
    Authors
    Attada, Yerrayya cc
    Velisoju, Vijay Kumar
    Mohamed, Hend Omar
    Ramirez, Adrian
    Castaño, Pedro cc
    KAUST Department
    Multiscale Reaction Engineering, KAUST Catalysis Center (KCC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
    KAUST Catalysis Center (KCC)
    Physical Science and Engineering (PSE) Division
    Chemical Engineering Program
    Date
    2022-07-14
    Permanent link to this record
    http://hdl.handle.net/10754/679782
    
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    Abstract
    Intermetallic Cu–Ga catalysts are potential candidates for activating the selective and stable hydrogenation of carbon dioxide to methanol and dimethyl ether. This work explores the structure–function relationship in specific Cu–Ga/CeO 2 –ZrO 2 catalysts with different Ga loadings. Combining experiments with density functional theory calculations, we find the most well-balanced intermetallic Cu–Ga interphase (structure) and promote specific mechanistic pathways of the reaction (function). The experiments yielded the highest selectivity of the desired products when the Cu and Ga amounts were equal. The experimental work and density functional theory calculations demonstrated that methanol is formed through the carboxyl pathway on the Cu catalyst, while Ga promotes the formate pathway. Consequently, the productivities of both methanol and dimethyl ether are enhanced. The experimental results match well with the theoretical calculations. Comparing our results with other Ga-promoting systems, we also prove that Cu achieves better balance than Ni and Co.
    Citation
    Attada, Y., Velisoju, V. K., Mohamed, H. O., Ramirez, A., & Castano, P. (2022). Dual Experimental and Computational Approach to Elucidate the Effect of Ga on Cu/Ceo2–Zro2 Catalyst for Co2 Hydrogenation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4162690
    Sponsors
    King Abdullah University of Science and Technology (KAUST) provided funding for this work. The authors acknowledge the KAUST Supercomputing Laboratory for providing high-performance computational resources and support from the KAUST Core Labs.
    Publisher
    Elsevier BV
    DOI
    10.2139/ssrn.4162690
    Additional Links
    https://www.ssrn.com/abstract=4162690
    ae974a485f413a2113503eed53cd6c53
    10.2139/ssrn.4162690
    Scopus Count
    Collections
    Preprints; Physical Science and Engineering (PSE) Division; Chemical Engineering Program; KAUST Catalysis Center (KCC)

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