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Two-dimensional transition metal dichalcogenides (TMDs) have gained attention as potent catalysts for the hydrogen evolution reaction (HER). The traditional trial-and-error methodology for catalyst development has proven inefficient due to its costly and time-intensive nature. To accelerate the catalyst development process, the Gibbs free energy of hydrogen adsorption (Δ G H ∗ ), computed using the density functional theory (DFT), is widely used as the paramount descriptor for evaluating and predicting HER catalyst performance. However, DFT calculations for Δ G H ∗ are time-consuming and thus pose a challenge for high-throughput screening. Herein, we devise a predictive model for Δ G H ∗ within transition metal-doped TMD systems using a machine learning (ML) framework. We calculate DFT Δ G H ∗ values for 150 TM-doped MX2 (CrS2, MoS2, WS2, MoSe2, and MoTe2) and apply various ML algorithms. We validate the universality of our model by constructing 15 new external test sets. The prediction results show a high correlation coefficient of R 2 = 0.92. Based on feature analysis, the three most important parameters are the number of valence electrons of the doped transition metal, the distance of the valence electrons of the doped transition metal, and the electronegativity of the doped transition metal. Our DFT-based ML model provides a useful guideline for the material development process through Δ G H ∗ prediction and facilitates the efficient design of transition metal dichalcogenide catalysts that exhibit superior HER activity. [ABSTRACT FROM AUTHOR]

Hydrodesulfurization catalysis ensures upgrading and purification of fossil fuels to comply with increasingly strict regulations on S emissions. The future shift toward more diverse and lower-quality crude oil supplies, high in S content, requires attention to improvements of the complex sulfided CoMo catalyst based on a fundamental understanding of its working principles. In this study, we use scanning tunneling microscopy to directly visualize and quantify how reducing conditions transforms both cluster shapes and edge terminations in MoS2 and promoted CoMoS-type hydrodesulfurization catalysts. The reduced catalyst clusters are shown to be terminated with a fractional coverage of sulfur, representative of the catalyst in its active state. By adsorption of a proton-accepting molecular marker, we can furthermore directly evidence the presence of catalytically relevant S–H groups on the Co-promoted edge. The experimentally observed cluster structure is predicted by theory to be identical to the structure present under catalytic working conditions. [ABSTRACT FROM AUTHOR]

The article discusses the carbon dioxide emissions which are largely driven by fossil fuel combustion and thus there is significant interest in developing alternative carbon-neutral fuels. Also discussed is the molecular hydrogen which is a highly promising fuel that received a great deal of attention since the proposition of a hydrogen economy by John Bockris in 1970.

Recently, transition metal dichalcogenides (TMDs), represented by MoS2, have been proven to be a fascinating new class of electrocatalysts in hydrogen evolution reaction (HER). The rich chemical activities, combined with several strategies to regulate its morphologies and electronic properties, make MoS2 very attractive for understanding the fundamentals of electrocatalysis. In this review, recent developments in using MoS2 as electrocatalysts for the HER with high activity are presented. The effects of edges on HER activities of MoS2 are briefly discussed. Then we demonstrate strategies to further enhance the catalytic performance of MoS2 by improving its conductivity or engineering its structure. Finally, the key challenges to the industrial application of MoS2 in electrocatalytic hydrogen evolution are also pointed out. [ABSTRACT FROM AUTHOR]