Atomic catalysts (AC) are emerging as a highly attractive research topic, especially in sustainable energy fields. Lack of a full picture of the hydrogen evolution reaction (HER) impedes the future development of potential electrocatalysts. In this work, the systematic investigation of the HER process in graphdyine (GDY) based AC is presented in terms of the adsorption energies, adsorption trend, electronic structures, reaction pathway, and active sites. This comprehensive work innovatively reveals GDY based AC for HER covering all the transition metals (TM) and lanthanide (Ln) metals, enabling the screening of potential catalysts. The density functional theory (DFT) calculations carefully explore the HER performance beyond the comparison of sole H adsorption. Therefore, the screened catalysts candidates not only match with experimental results but also provide significant references for novel catalysts. Moreover, the machine learning (ML) technique bag‐tree approach is innovatively utilized based on the fuzzy model for data separation and converse prediction of the HER performance, which indicates a similar result to the theoretical calculations. From two independent theoretical perspectives (DFT and ML), this work proposes pivotal guidelines for experimental catalyst design and synthesis. The proposed advanced research strategy shows great potential as a general approach in other energy‐related areas.

Although the atomic catalyst has attracted intensive attention in the past few years, the current progress of this field is still limited to a single atomic catalyst (SAC). With very few successful cases of dual atomic catalysts (DACs), the most challenging part of experimental synthesis still lies in two main directions: the thermodynamic stability of the synthesis and the optimal combination of metals. To address such challenges, comprehensive theoretical investigations on graphdiyne (GDY)‐based DAC are proposed by considering both, the formation stability and the d‐band center modifications. Unexpectedly, it is proven that the introduction of selected lanthanide metals to the transition metals contributes to the optimized stability and electroactivity. With further verification by machine learning, the potential f–d orbital coupling is unraveled as the pivotal factor in modulating the d‐band center with enhanced stability by less orbital repulsive forces. These findings supply the delicate explanations of the atomic interactions and screen out the most promising DAC to surpass the limitations of conventional trial and error synthesis. This work has supplied an insightful understanding of DAC, which opens up a brand new direction to advance the research in atomic catalysts for broad applications.

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In recent years, investigations into atomic catalysts has accelerated significantly. Although different atomic catalysts have been developed, the introduction of main group elements is rarely considered. In this work, the possibility of introducing alkaline/alkaline earth metals (AAEM), post‐transition metal (Post‐TM), and metalloids to form stable graphdiyne‐based dual atomic catalysts (GDY‐DAC) is revealed. The main group elements not only act as a promising separator to improve the loading of DACs but also activate the alkyl chains to facilitate the electroactivity of GDY‐DAC. Most importantly, the main group elements in the GDY‐DAC do not affect the electroactivity of transition or lanthanide metals and even enable subtle modulations on the electronic structures. The p band center is a significant descriptor to modulate the electroactivity in oxides while their applications in the atomic catalysts are unclear. With the further evaluations of machine learning, it is found that the involvements of s‐orbitals and p‐orbitals perturb the prediction accuracies of both formation energies and p‐band center, especially for the AAEM. This work supplies insights that are expected to aid progress in designing main group elements‐based atomic catalysts, which opens a new avenue in designing advanced electrocatalysts.

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