A combined theoretical and experimental investigation on the photocatalytic hydrogenation of CO2 on Cu/ZnO polar surface

The photocatalytic hydrogenation of CO₂ by Cu-deposited ZnO (Cu/ZnO) polar surfaces is investigated through density functional theory (DFT) calculations combined with experimental work. The DFT results demonstrate that, without Cu-loading, CO₂ and H₂ present weak physisorption on the clean ZnO polar surface, except that H₂ undergoes strong chemisorption on the ZnO(0001̄) surface. Cu deposition on the ZnO polar surface could remarkably enhance the CO₂ chemisorption ability, due to the induced charge redistribution on the interface of the Cu/ZnO polar surface systems. Additionally, a Cu-nanoisland, which was simulated using a Cu(111) slab model, exhibited strong ability to chemically adsorb H₂. Thus, H₂ may act as an adsorption competitor to CO₂ on the Cu/ZnO(0001̄), while, in contrast, CO₂ and H₂ (syngas) may have more opportunity to simultaneously adsorb on Cu/ZnO(0001) to promote the CO₂ hydrogenation. These facet-dependent properties lead us to assume that Cu/ZnO(0001) should be a favorable photocatalyst for CO₂ hydrogenation. This assumption is further verified by our photocatalysis experiment based on a ZnO single crystal. According to the theoretical and experimental results, the optimal HCOO* reaction pathway for the photocatalytic hydrogenation of CO₂ on Cu/ZnO(0001) is proposed. In this optimal HCOO* path, the hydrogenation of CO₂* step and hydrogenation of HCOO* step could be promoted by the coupling of a photo-generated spillover proton and a photoelectron on the interface of Cu/ZnO(0001). This research demonstrates the feasibility of the photocatalytic reduction of CO₂ on Cu/ZnO(0001), and will help to develop related high-efficiency catalysts.

In Situ Spectroscopic Characterization and Theoretical Calculations Identify Partially Reduced ZnO1-x /Cu Interfaces for Methanol Synthesis from CO2

The active site of the industrial Cu/ZnO/Al₂ O₃ catalyst used in CO₂ hydrogenation to methanol has been debated for decades. Grand challenges remain in the characterization of structure, composition, and chemical state, both microscopically and spectroscopically, and complete theoretical calculations are limited when it comes to describing the intrinsic activity of the catalyst over the diverse range of structures that emerge under realistic conditions. Here a series of inverse model catalysts of ZnO on copper hydroxide were prepared where the size of ZnO was precisely tuned from atomically dispersed species to nanoparticles using atomic layer deposition. ZnO decoration boosted methanol formation to a rate of 877 g_MeOH  kg_cat ^-1  h^-1 with ≈80 % selectivity at 493 K. High pressure in situ X-ray absorption spectroscopy demonstrated that the atomically dispersed ZnO species are prone to aggregate at oxygen-deficient ZnO ensembles instead of forming CuZn metal alloys. By modeling various potential active structures, density functional theory calculations and microkinetic simulations revealed that ZnO/Cu interfaces with oxygen vacancies, rather than stoichiometric interfaces, Cu and CuZn alloys were essential to catalytic activation.

Computational Methods in Heterogeneous Catalysis

The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. We finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.

Trends and Outlook of Computational Chemistry and Microkinetic Modeling for Catalytic Synthesis of Methanol and DME

The first-principle modeling of heterogeneous catalysts is a revolutionarily approach, as the electronic structure of a catalyst is closely related to its reactivity on the surface with reactant molecules. In the past, detailed reaction mechanisms could not be understood, however, computational chemistry has made it possible to analyze a specific elementary reaction of a reaction system. Microkinetic modeling is a powerful tool for investigating elementary reactions and reaction mechanisms for kinetics. Using a microkinetic model, the dominant pathways and rate-determining steps can be elucidated among the competitive reactions, and the effects of operating conditions on the reaction mechanisms can be determined. Therefore, the combination of computational chemistry and microkinetic modeling can significantly improve computational catalysis research. In this study, we reviewed the trends and outlook of this combination technique as applied to the catalytic synthesis of methanol (MeOH) and dimethyl ether (DME), whose detailed mechanisms are still controversial. Although the scope is limited to the catalytic synthesis of limited species, this study is expected to provide a foundation for future works in the field of catalysis research based on computational catalysis.

Unravelling the mechanisms of CO2 hydrogenation to methanol on Cu-based catalysts using first-principles multiscale modelling and experiments

Multi-scale modelling of various copper-based catalysts showed how and why different catalysts perform in methanol synthesis via carbon dioxide hydrogenation.

Surface energies of elemental crystals

The surface energy is a fundamental property of the different facets of a crystal that is crucial to the understanding of various phenomena like surface segregation, roughening, catalytic activity, and the crystal's equilibrium shape. Such surface phenomena are especially important at the nanoscale, where the large surface area to volume ratios lead to properties that are significantly different from the bulk. In this work, we present the largest database of calculated surface energies for elemental crystals to date. This database contains the surface energies of more than 100 polymorphs of about 70 elements, up to a maximum Miller index of two and three for non-cubic and cubic crystals, respectively. Well-known reconstruction schemes are also accounted for. The database is systematically improvable and has been rigorously validated against previous experimental and computational data where available. We will describe the methodology used in constructing the database, and how it can be accessed for further studies and design of materials.