Bipolaronic Motifs Induced Spatially Separated Catalytic Sites for Tunable Syngas Photosynthesis From CO2

Photocatalytic reduction of CO2 into syngas is a promising way to tackle the energy and environmental challenges; however, it remains a challenge to achieve reaction decoupling of CO2 reduction and water splitting. Therefore, efficient production of syngas with a suitable CO/H2 ratio for Fischer-Tropsch synthesis can hardly be achieved. Herein, bipolaronic motifs including Co(II)-pyridine N motifs and Co(II)-imine N motifs are rationally designed into a crystalline imine-linked 1,10-phenanthroline-5,6-dione-based covalent organic framework (bp-Co-COF) with a triazine core. These featured structures with spatially separated active sites exhibit efficient photocatalytic performance toward CO2-to-syngas conversion with a suitable CO/H2 ratio (1:1-1:3). The bipolaronic motifs enable a highly separated electron-hole state, whereby the Co(II)-pyridine N motifs tend to be the active sites for CO2 activation and accelerate the hydrogenation to form *COOH intermediates; whilst, the Co(II)-imine N motifs increase surface hydrophilicity for H2 evolution. The photocatalytic reductions of CO2 and H2O thus decouple and proceed via a concerted way on the bipolaronic motifs of bp-Co-COF. The optimal bp-Co-COF photocatalyst achieves a high syngas evolution rate of 15.8 mmol g-1 h-1 with CO/H2 ratio of 1:2, outperforming previously reported COF-based photocatalysts.

Multiobjective Bayesian Optimization Framework for the Synthesis of Methanol from Syngas Using Interpretable Gaussian Process Models

Methanol production has gained considerable interest on the laboratory and industrial scale as it is a renewable fuel and an excellent hydrogen energy storehouse. The formation of synthesis gas (CO/H₂) and the conversion of synthesis gas to methanol are the two basic catalytic processes used in methanol production. Machine learning (ML) approaches have recently emerged as powerful tools in reaction informatics. Inspired by these, we employ Gaussian process regression (GPR) to the model conversion of carbon monoxide (CO) and selectivity of the methanol product using data sets obtained from experimental investigations to capture uncertainty in prediction values. The results indicate that the proposed GPR model can accurately predict CO conversion and methanol selectivity as compared to other ML models. Further, the factors that influence the predictions are identified from the best GPR model employing "Shapley Additive exPlanations" (SHAP). After interpretation, the essential input features are found to be the inlet mole fraction of CO (Y(CO, in)) and the net inlet flow rate (Fin(nL/min)) for our best prediction GPR models, irrespective of our data sets. These interpretable models are employed for Bayesian optimization in a weighted multiobjective framework to obtain the optimal operating points, namely, maximization of both selectivity and conversion.

LaCo1-x-yCuxTiyO3/KIT-6 perovskites: synthesis and catalytic behavior in syngas conversion to higher alcohols

Highly dispersed LaCo_1-x-yCu_xTi_yO₃/KIT-6 perovskites were synthesized by the citrate method with inert mesoporous KIT-6 addition. The KIT-6 matrix was removed by dissolution in 7% NaOH aqueous solution. The dispersity of perovskites probably varies depending on the largest cation and its content at the B position of the perovskite ABO3 structure. The Co_S=2³⁺/Co_S=0³⁺ ratio increases with the increase in copper content and in the presence of Ti⁴⁺. It may be explained by the compensation of the distortion of the perovskite structure. The maximum syngas conversion is achieved at n_Co/n_Cu = 7/3. At a higher copper content, the activity of the samples decreases due to the formation of large copper particles (up to 40 nm) in the course of the reduction. The selectivity for alcohols increases with an increase in the proportion of copper and reaches maximum values at a ratio of n_Co/n_Cu close to 1. The distribution of alcohols is the same for all samples, except for LaCo_0.35Cu_0.35Ti_0.3O₃/KIT-6. It can be assumed that the synthesis of alcohols proceeds on bimetallic CoCu particles 3 nm in size and cobalt particles 4-6 nm in size, most likely enriched with copper on the surface.

Catlas: an automated framework for catalyst discovery demonstrated for direct syngas conversion

Catlas may be used with off-the-shelf pretrained models to explore large design spaces for catalyst discovery and has been used here to identify promising materials for the direct conversion of syngas to multi-carbon oxygenates.