Understanding Polyol Decomposition on Bimetallic Pt–Mo Catalysts—A DFT Study of Glycerol

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better understanding of electro/photocatalytic processes are essential for improving catalyst effectiveness. Recent advances in data science and artificial intelligence have great potential to accelerate electrocatalysis and photocatalysis research, particularly the rapid exploration of large materials chemistry spaces through machine learning. Here a comprehensive introduction to, and critical review of, machine learning techniques used in electrocatalysis and photocatalysis research are provided. Sources of electro/photocatalyst data and current approaches to representing these materials by mathematical features are described, the most commonly used machine learning methods summarized, and the quality and utility of electro/photocatalyst models evaluated. Illustrations of how machine learning models are applied to novel electro/photocatalyst discovery and used to elucidate electrocatalytic or photocatalytic reaction mechanisms are provided. The review offers a guide for materials scientists on the selection of machine learning methods for electrocatalysis and photocatalysis research. The application of machine learning to catalysis science represents a paradigm shift in the way advanced, next-generation catalysts will be designed and synthesized.

Mo single atoms in the Cu(111) surface as improved catalytic active centers for deoxygenation reactions

The surface Mo-doped Cu(111) catalyst feature improved performance towards deoxygenation reactions, acting as a single-atom alloy capable of breaking Brønsted–Evans–Polanyi relations for carbonyl bond scissions.

Recent advances in the electrooxidation of biomass-based organic molecules for energy, chemicals and hydrogen production

The recent developments in biomass-derivative fuelled electrochemical converters for electricity or hydrogen production together with chemical electrosynthesis have been reviewed.

Elucidating Molecular Interactions in Glycerol Adsorption at the Metal-Water Interface with Density Functional Theory

Glycerol is an extremely versatile platform molecule for chemical and fuel production, as evidenced by successful demonstrations in electrochemical and thermochemical processes, where key catalytic chemistries occur at the solid-liquid interface. Despite the remarkable progress made in enriching the first-principles-based computational tool set to reveal and characterize solvent structures in the past decade, techniques for realistic and efficient molecular-level modeling to study aqueous-phase glycerol chemistry are still far from mature. Many aqueous-phase catalytic systems are deemed too complex for routine modeling because of their highly correlated structures at the heterogeneous solid-liquid interface. This invited feature article merges recent developments in quantum mechanical solvation models and oxygenated hydrocarbon conversion chemistry by revisiting the molecular interactions of adsorbed glycerol and its dehydrogenation intermediates at the water-metal interface. Explicit participation of water through the establishment of water-adsorbate, water-water, and water-metal interactions on Pt(111) was investigated using density functional theory. In periodic models, the adsorption favors networklike structures with adsorbates as nodal points linked by coadsorbed water molecules. We also showed that these adsorption patterns actually preserve the original bond-order-based scaling relationship framework established without the consideration of solvent. This behavior can be exploited to improve computational efficiency for future analysis of catalytic polyol conversions in the aqueous-phase environment.

Catalytic Transfer Hydrogenation of Biomass-Derived Substrates to Value-Added Chemicals on Dual-Function Catalysts: Opportunities and Challenges

Aqueous-phase hydrodeoxygenation (APH) of bioderived feedstocks into useful chemical building blocks is one the most important processes for biomass conversion. However, several technological challenges, such as elevated reaction temperature (220-280 °C), high H₂ pressure (4-10 MPa), uncontrollable side reactions, and intensive capital investment, have resulted in a bottleneck for the further development of existing APH processes. Catalytic transfer hydrogenation (CTH) under much milder conditions with non-fossil-based H₂ has attracted extensive interest as a result of several advantageous features, including high atom efficiency (≈100 %), low energy intensity, and green H₂ obtained from renewable sources. Typically, CTH can be categorized as internal H₂ transfer (sacrificing small amounts of feedstocks for H₂ generation) and external H₂ transfer from H₂ donors (e.g., alcohols, formic acid). Although the last decade has witnessed a few successful applications of conventional APH technologies, CTH is still relatively new for biomass conversion. Very limited attempts have been made in both academia and industry. Understanding the fundamentals for precise control of catalyst structures is key for tunable dual functionality to combine simultaneous H₂ generation and hydrogenation. Therefore, this Review focuses on the rational design of dual-functionalized catalysts for synchronous H₂ generation and hydrogenation of bio-feedstocks into value-added chemicals through CTH technologies. Most recent studies, published from 2015 to 2018, on the transformation of selected model compounds, including glycerol, xylitol, sorbitol, levulinic acid, hydroxymethylfurfural, furfural, cresol, phenol, and guaiacol, are critically reviewed herein. The relationship between the nanostructures of heterogeneous catalysts and the catalytic activity and selectivity for C-O, C-H, C-C, and O-H bond cleavage are discussed to provide insights into future designs for the atom-economical conversion of biomass into fuels and chemicals.

Insights into the roles of water on the aqueous phase reforming of glycerol

Microkinetic modeling using energies from DFT and scaling relations to reveal roles of water in aqueous phase reforming of glycerol.

Mo@Pt overlayers as efficient catalysts for hydrodeoxygenation of guaiacol and anisole

Silica alumina supported Mo@Pt overlayer catalysts were prepared via the directed deposition technique and evaluated for hydrodeoxygenation (HDO) of guaiacol and anisole.

Theoretical Heterogeneous Catalysis: Scaling Relationships and Computational Catalyst Design

Scaling relationships are theoretical constructs that relate the binding energies of a wide variety of catalytic intermediates across a range of catalyst surfaces. Such relationships are ultimately derived from bond order conservation principles that were first introduced several decades ago. Through the growing power of computational surface science and catalysis, these concepts and their applications have recently begun to have a major impact in studies of catalytic reactivity and heterogeneous catalyst design. In this review, the detailed theory behind scaling relationships is discussed, and the existence of these relationships for catalytic materials ranging from pure metal to oxide surfaces, for numerous classes of molecules, and for a variety of catalytic surface structures is described. The use of the relationships to understand and elucidate reactivity trends across wide classes of catalytic surfaces and, in some cases, to predict optimal catalysts for certain chemical reactions, is explored. Finally, the observation that, in spite of the tremendous power of scaling relationships, their very existence places limits on the maximum rates that may be obtained for the catalyst classes in question is discussed, and promising strategies are explored to overcome these limitations to usher in a new era of theory-driven catalyst design.

The effects of the Mo–Sn contact interface on the oxidation reaction of dimethyl ether to methyl formate at a low reaction temperature

With increasing degrees of Mo–Sn interface contact, the molar ratio of methyl formate (MF) to methanol (MeOH) and formaldehyde (FA) was found to linearly increase simultaneously.