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Thermocatalytic CO 2 hydrogenation to methanol is an attractive defossilization technology to combat climate change while producing a valuable platform chemical and energy carrier. However, predicting the performance of catalytic systems for this process remains a challenge. Herein, we present a machine learning framework to predict catalyst performance from experimental descriptors. A database of Cu-, Pd-, In 2 O 3 -, and ZnO-ZrO 2 -based catalysts with 1425 datapoints is compiled from literature and subjected to data mining. Accurate ensemble-tree models (R 2 > 0.85) are developed to predict the methanol space-time yield (STY) from 12 descriptors, where the significance of space velocity, pressure, and metal content is revealed. The model prediction and its insights are experimentally validated, with a root mean squared error of 0.11 g MeOH h−1 g cat −1 between the actual and predicted methanol STY. The framework is purely data-driven, interpretable, cross-deployable to other catalytic processes, and serves as an invaluable tool for guided experiments and optimization. [Display omitted] • Machine learning framework for CO 2 hydrogenation to methanol devised. • Database for Cu-, Pd-, In 2 O 3 - and ZnO-ZrO 2 -based catalysts compiled. • Generalized model to predict methanol space-time yield (STY) developed. • Efficacy and fidelity of the model experimentally validated. • Model enhancements to aid the discovery of novel catalysts required. [ABSTRACT FROM AUTHOR]

5-Methylfurfural (MF) is a critical commodity chemical used as food additive and synthetic intermediate. Opening a sustainable route towards highly selective synthesis of MF from 5-hydroxymethylfurfural (HMF) is of great significance, but has demonstrated extremely challenging. Herein, we report an efficient process for the selective production of MF from HMF over an anatase-supported gold catalyst (Au/a-TiO 2). During the hydrogenolysis of HMF, the desired C O bond is maintained and MF can be obtained in a high yield of 83.1 %, exhibiting excellent stability both in batch and flow operation. A combination of experimental and theoretical analyses attribute the superior performance of Au/a-TiO 2 to the synergistic effect of limited H access, low adsorption of reactants, and avoiding condensation, driven by the high concentration of oxygen vacancies in the support. This study highlights a novel approach of tailoring the coverage of active species for the selective transformation of renewable compounds into high-value-added chemicals. [Display omitted] • Selective production of MF from HMF via direct hydrogenolysis of the hydroxyl group using the Au/a-TiO 2 catalyst. • The C=O functional group was preserved under reductive conditions and MF can be obtained in a high yield of 83.1%. • The Au/a-TiO 2 catalyst shows high activity, remarkable selectivity, and excellent stability both in batch and flow operation. • The synergistic effect of limited H access, low adsorption of reactants, high concentration of oxygen vacancies. • This study paves the way for the design of new bifunctional catalysts toward selective hydrogenolysis of biomass. [ABSTRACT FROM AUTHOR]

The development of efficient CO 2 conversion catalysts is a long-lasting desire. Herein, we introduce an atomic Pd-promoted ZnZrO x solid solution catalyst (Pd-ZnZrO x), which shows markedly enhanced rate of methanol production compared to bare ZnZrO x , as well as excellent stability over 100 h on stream. Up to 0.8 at% (i. e. 0.6 wt%), Pd can be atomically dispersed in ZnZrO x , leading to more oxygen vacancies on the mixed oxide that foster methanol production. Kinetic analysis and in situ DRIFTS reveal that hydrogen activation is limited on ZnZrO x , but Pd doping facilitates H 2 dissociation as well as the consequent formation of HCOO*, thus boosting CO 2 conversion to methanol. DFT analyses suggest that the presence of atomic Pd enables a more exothermic H 2 dissociation, which increases the availability of surface H and facilitates CO 2 hydrogenation on adjacent Zn sites, providing rationale on the high activity and robustness of Pd-ZnZrO x in CO 2 hydrogenation. [Display omitted] • Coprecipitation of Zn, Zr, and Pd precursors forms atomically dispersed Pd on ZnZrO x. • Atomic Pd-doping leads to higher concentration of surface oxygen vacancies. • Atomic Pd-promoted ZnZrO x shows excellent CO 2 hydrogenation activity and lifetime. • Pd promotes H 2 splitting and the stabilization of key intermediates for CH 3 OH. [ABSTRACT FROM AUTHOR]