The development of high-performance atomic catalysts for the carbon dioxide reduction reaction (CO₂RR) is a time-consuming process due to the complexity of the reaction mechanism and the uncertainty of the active site. Herein, we have proposed combining density functional theory (DFT) and machine learning (ML) to investigate the potential of topological graphene-based dual-atom catalysts (DACs) as CO₂RR electrocatalysts. By analyzing the ML results, we identify the number of d-orbital electrons in the active site as a key factor influencing the CO₂RR catalytic activity. Additionally, we propose a simple descriptor to measure the CO₂RR activity of these DACs. Our findings provide plausible explanations for the synergistic interactions between bimetallic atoms in CO₂RR and allow us to screen the homogeneous Ni-Ni pair as the most promising dual-atom catalysts. This work offers a fast ML approach based on limited DFT calculations to predict the most electroactive and stable DACs on carbon support for CO₂RR, facilitating rapid screening of high-performance dual-atom catalysts.

Designing high-performance electrocatalysts toward hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is essential to reduce the activation barrier and optimize free adsorption energy of reactive intermediates. Herein, we report that incorporating high-valence Cr into NiSe₂ (Cr_xNi_1−xSe₂) kinetically and thermodynamically expedites elementary steps of both HER and OER. The as-prepared Cr_0.05Ni_0.95Se₂ catalyst displays excellent HER and OER activities, with low overpotentials of 89 and 272 mV at the current density of 10 mA·cm⁻² (j₁₀), respectively, and remains stable during operation for 30 h. A low cell voltage of only 1.59 V is required to drive j₁₀ in alkaline media. In situ Raman spectroscopy reveals that Cr incorporation facilitates the formation of NiOOH active species during the OER process. Meanwhile, theoretical explorations demonstrate that high-valence Cr incorporation efficiently accelerates water dissociation kinetics and improves H* adsorption during HER process, lowering the activation barrier of OER and optimizing the adsorption energy of oxygen-based intermediate, thus kinetically and thermodynamically enhancing the intrinsic performance of NiSe₂ for over water splitting. This strategy provides a new horizon to design transition metal based electrocatalysts in the clean energy field.

Carbon monoxide electroreduction (COER) has been a key part of tandem electrolysis of carbon dioxide (CO₂), in which searching for high catalytic performance COER electrocatalysts remains a great challenge. Herein, by means of density functional theory (DFT) computations, we explored the potential of a series of transition metal atoms anchored on N-doped γ-graphyne (TM@N-GY, TM from Ti to Au) as the COER electrocatalysts. We found that the final product selectivity of these single-atom catalysts depended on the position of the metal atom in the periodic table, with metals in the front and middle of each periodic period exhibiting high selectivity for CH₄, while metals in the back producing CH₃OH. Machine learning (ML) found that metal atomic number was intrinsic to the difference in COER performance of these single-atom catalysts (SACs). The free energy changes showed that Mn@N-GY and Ni@N-GY exhibited outstanding COER catalytic performance for producing CH₄ and CH₃OH, respectively. Our results provide theoretical and experimental guidance for designing efficient COER catalysts to generate C₁ products.

Modulation of the surface electron distribution is a challenging problem that determines the adsorption ability of catalytic process. Here, we address this challenge by bridging the inner and outer layers of the core–shell structure through the bridge Br atom. Carbon shell wrapped copper bromide nanorods (CuBr@C) are constructed for the first time by chemical vapour deposition with hexabromobenzene (HBB). HBB pyrolysis provides both bridge Br atom and C shells. The C shell protects the stability of the internal halide structure, while the bridge Br atom triggers the rearrangement of the surface electrons and exhibits excellent electrocatalytic activity. Impressively, the hydrogen evolution reaction (HER) activity of CuBr@C is significantly better than that of commercial N-doped carbon nanotubes, surpassing commercial Pt/C at over 200 mA·cm⁻². Density functional theory (DFT) calculations reveal that bridge Br atoms inspire aggregation of delocalized electrons on C-shell surfaces, leading to optimization of hydrogen adsorption energy.

The development of highly efficient Pt-based alloy nanocatalysts is important but remains challenging for fuel cells commercialization. Here, a new class of zigzag-like platinum-zinc (Pt-Zn) alloy nanowires (NWs) with rough surface and controllable composition is reported. The merits of anisotropic one-dimensional nanostructure, stable high-index facets and coordinatively unsaturated Pt sites endow the composition-optimal Pt₉₄Zn₆ NWs with a mass activity of 7.2 and 6.2 times higher than that of commercial Pt black catalysts toward methanol/ethanol oxidation, respectively. Alloying-induced d-band electron modulation and lattice strain effects weaken the adsorption strength of poisoning species, which originally enhances the catalytic activity of Pt-Zn NWs. This study provides a new perspective of Pt-Zn electrocatalysts with intrinsic mechanism for enhanced catalytic performance.