Cost-effective and dynamic carbon dioxide conversion into methane using a CaTiO3@Ni-Pt catalyst in a photo-thermal hybrid system

Fabrication of Heterostructural FeNi3-Loaded Perovskite Catalysts by Rapid Plasma for Highly Efficient Photothermal Reverse Water Gas Shift Reaction

Metal-semiconductor heterostructured catalysts have attracted great attention because of their unique interfacial characteristics and superior catalytic performance. Exsolution of nanoparticles is one of the effective and simple ways for in-situ growth of metal nanoparticles embedded in oxide surfaces and their favorable dispersion and stability. However, both high-temperature and a reducing atmosphere are required simultaneously in conventional exsolution, which is time-consuming and costly, and particles often agglomerate during the process. In this work, Ca0.9Ti0.8Ni0.1Fe0.1O3-δ (CTNF) is exposed to dielectric blocking discharge (DBD) plasma at room temperature to fabricate alloying FeNi3 nanoparticles from CTNF perovskite. FeNi3-CTNF has outstanding catalytic activity for photothermal reverse water gas shift reaction (RWGS). At 350 °C under full-spectrum irradiation, the carbon monoxide (CO) yield of FeNi3-CTNF (10.78 mmol g-1 h-1) is 11 times that of pure CaTiO3(CTO), and the CO selectivity is 98.9%. This superior catalytic activity is attributed to the narrow band gap, photogenerated electron migration to alloy particles, and abundant surface oxygen vacancies. The carbene pathway reaction is also investigated through in-situ Raman spectroscopy. The present work presents a straightforward method for the exsolution of nanoalloys in metal-semiconductor heterostructures for photothermal CO2 reduction.

Engineering the Electronic Structure towards Visible Lights Photocatalysis of CaTiO3 Perovskites by Cation (La/Ce)-Anion (N/S) Co-Doping: A First-Principles Study

Cation-anion co-doping has proven to be an effective method of improving the photocatalytic performances of CaTiO3 perovskites. In this regard, (La/Ce-N/S) co-doped CaTiO3 models were investigated for the first time using first-principles calculations based on a supercell of 2 × 2 × 2 with La/Ce concentrations of 0.125, 0.25, and 0.375. The energy band structure, density of states, charge differential density, electron-hole effective masses, optical properties, and the water redox potential were calculated for various models. According to our results, (La-S)-doped CaTiO3 with a doping ratio of 0.25 (LCOS1-0.25) has superior photocatalytic hydrolysis properties due to the synergistic performances of its narrow band gap, fast carrier mobility, and superb ability to absorb visible light. Apart from the reduction of the band gap, the introduction of intermediate energy levels by La and Ce within the band gap also facilitates the transition of excited electrons from valence to the conduction band. Our calculations and findings provide theoretical insights and solid predictions for discovering CaTiO3 perovskites with excellent photocatalysis performances.

Artificial-intelligence-driven discovery of catalyst genes with application to CO2 activation on semiconductor oxides

Catalytic-materials design requires predictive modeling of the interaction between catalyst and reactants. This is challenging due to the complexity and diversity of structure-property relationships across the chemical space. Here, we report a strategy for a rational design of catalytic materials using the artificial intelligence approach (AI) subgroup discovery. We identify catalyst genes (features) that correlate with mechanisms that trigger, facilitate, or hinder the activation of carbon dioxide (CO2) towards a chemical conversion. The AI model is trained on first-principles data for a broad family of oxides. We demonstrate that surfaces of experimentally identified good catalysts consistently exhibit combinations of genes resulting in a strong elongation of a C-O bond. The same combinations of genes also minimize the OCO-angle, the previously proposed indicator of activation, albeit under the constraint that the Sabatier principle is satisfied. Based on these findings, we propose a set of new promising catalyst materials for CO2 conversion.

Fundamentals and applications of photo-thermal catalysis

Photo-thermal catalysis has recently emerged as an alternative route to drive chemical reactions using light as an energy source.

Effect of Cobalt Oxide Content on the Activity of NiO-Co2O3/γ-Al2O3 Catalyst in the Reaction of Dry Reforming of Methane to Synthesis Gas

The effect of cobalt oxide content on the activity of NiO-Co2O3/γ-Al2O3 catalyst was investigated in process of dry reforming of methane (DRM) to synthesis gas. It was found that among the studied catalysts the highest activity is shown by the NiO-Co2O3/ γ-Al2O3, where methane conversion is 89%. It was determined by the scanning electron microscopy (SEM) and X-ray diffraction analysis (XRD) there are oxides of Ni and Co in the form of nanosized particles on active NiO-Co2O3/γ-Al2O3 catalyst and Co-Ni alloys, formed after the reaction of DRM, the size of 17‒23 nm. Thermogravimetric Analysis (TGA)/ Differential Thermal Analysis (DTA)/ Differential Scanning Calorimetry (DSC) of catalyst showed that the highest weight loss (2.7%) is observed at a degree from 30 to 260 °C after DRM. After heating above 300 °C there is a slight increase in weight, accompanied by an exothermic effect on the DSC curve due to the gas adsorption used to purge the unit. The data indicate the absence of coke formation on NiO-Co2O3/γ-Al2O3 surface. According to TPR-H2 there are peaks at relatively low temperatures of Т1mах = 205 °C and Т2mах = 497 °C on thermally programmed reduction (TPR) TPR-Н2 spectrum of NiO-Со2О3/γ-Al2O3, which are associated with the formation of easily reducible cobalt and nickel oxides, indicating the presence of active and mobile oxygen in the catalyst. These results confirm that the activity of NiO-Co2O3/γ-Al2O3 is due to the formation of nanophases, the presence of active oxygen, and the absence of coke on the catalyst surface.