The development of effective and inexpensive hydrogen evolution reaction (HER) electrocatalysts for future renewable energy systems is highly desired. Platinum-based materials are the most active electrocatalysts for catalyzing HER, but reducing the use of Pt is required because of the high price and scarcity of Pt. Here, we achieve pseudo-atomic-scale dispersion of Pt, i.e. individual atoms or subnanometer clusters, on the sidewalls of single-walled carbon nanotubes (SWNTs) with a simple and readily upscalable electroplating deposition method. These SWNTs activated with an ultralow amount of Pt exhibit activity similar to that of commercial Pt/C with a notably higher (∼66–333-fold) Pt loading for catalyzing the HER under the acidic conditions required in proton exchange membrane technology. These catalysts resemble pseudo-atomic-scale Pt systems which are mainly composed of a few to tens of Pt atoms dispersed on the sidewalls of the SWNTs. The Pt loading is only 0.19–0.75 atom % at the electrode surface, and characteristic peaks for Pt cyclic voltammograms are undetectable. The atomic dispersion increases the portion of the surface active-atom sites, and therefore, notably lower Pt loading is needed to attain a high catalytic activity. Density functional theory (DFT) calculations suggest higher ability for SWNTs, in comparison to graphene, as a catalyst support for immobilizing Pt atoms, thus providing an atomic dispersion. Moreover, a high HER activity for the SWNTs activated with Pt atoms, similar to that of bulk Pt, is predicted.

We report a comprehensive computational study of the intricate structure-property relationships governing the hydrogen adsorption trends on MoS 2 edges with varying S-and H-coverages, as well as provide insights into the role of individual adsorption sites. Additionally, the effect of singleand dual S-vacancies in the basal plane on the adsorption energetics is assessed, likewise with an emphasis on the H-coverage dependency. The employed edge/site-selective approach reveals significant variations in the adsorption free energies, ranging between ∼ ±1.0 eV for the different edges-types and S-saturations, including differences of even as much as ∼ 1.2 eV between sites on the same edge. The incrementally increasing hydrogen coverage is seen to mainly weaken the adsorption, but intriguingly for certain configurations a stabilizing effect is also observed. The strengthened binding is seen to be coupled with significant surface restructuring, most notably the splitting of terminal S 2 -dimers. Our work links the energetics of hydrogen adsorption on 2H-MoS 2 to both static and dynamic geometrical features and quantifies the observed trends as a function of H-coverage, thus illustrating the complex structure/activity relationships of the MoS 2 catalyst. The results of this systematical study aims to serve as guidance for experimentalists by suggesting feasible edge/S-coverage combinations, the synthesis of which would potentially yield the most optimally performing HER-catalysts.

The computational hydrogen evolution activity of Pt(111) remains controversial due to apparent discrepancies with experiments concerning rate-determining activation free energies and equilibrium hydrogen coverages. A fundamental source of error may lie within the static representations of the metal−water interface commonly employed in density functional theory (DFT)based kinetic models neglecting important entropic effects on reaction dynamics. In this work, we present a dynamic reassessment of the Volmer−Tafel hydrogen evolution pathway on Pt(111) through DFT-based constrained molecular dynamics simulations and thermodynamic integration. Hydrogen coverage effects are gauged at two distinct surface saturations, while the critical potential dependence and constant potential conditions are accounted for using a capacitive model of the electrified interface. The uncertainty in the highly nontrivial treatment of the electrode potential is carefully examined, and we provide a quantitative estimation of the error associated with dynamically simulated electrochemical barriers. The dynamic description of the electrochemical interface promotes a substantial decrease of the Tafel free energy barrier as the coverage is increased to a full monolayer. This follows from a decreased entropic barrier due to suppressed adlayer dynamics compared to the unsaturated surface, a detail easily missed by static calculations predicting notably higher barriers at the same coverage. Due to observed endergonic adsorption of active hydrogen intermediates, the Tafel step remains ratedetermining irrespective of the coverage as illustrated by composed Volmer−Tafel free energy landscapes. Importantly, our explicitly dynamic approach avoids the ambiguous choice of frozen solvent configuration, decreasing the reliance on error cancellation and paving the way for less biased electrochemical simulations.

This study presents the first direct simulation of the hydrogen evolution reaction using a fully explicit, dynamic DFT approach and highlights the importance of incorporating solvent dynamics in the rigorous description of electrochemical reactions.

Electrochemical devices for efficient production of hydrogen as energy carrier rely still largely on rare platinum group metal catalysts. Chemically and structurally modified metal dichalcogenide MoS2 is a promising substitute for these critical raw materials at the cathode side where the hydrogen evolution reaction takes place. For precise understanding of structure and hydrogen adsorption characteristics in chemically modified MoS2 nanostructures, we perform comprehensive density functional theory calculations on transition metal (Fe, Co, Ni, Cu) doping at the experimentally relevant MoS2 surfaces at substitutional Mo-sites. Clear benefits of doping the basal plane are found, whereas at the Mo- and S-edges complex modifications at the whole edge are observed. New insight into doping-enhanced activity is obtained and guidance is given for further experiments. We study a machine learning model to facilitate the screening of suitable structures and find a promising level of prediction accuracy with minimal structural input.