This research seeks to investigate extremely efficient catalysts for the nitrogen reduction process (NRR), utilizing machine learning (ML)-aided density functional theory (DFT) computations. Specifically, we investigate dual transition metal atoms anchored on hexagonal nitrogen-doped graphene (TM₁-TM₂@N₆G) as prospective high-activity catalysts for the NRR. The findings indicate that the synergistic effect of dual transition metal atoms in the TM₁-TM₂@N₆G catalyst overcomes the intrinsic constraints of the linear relationship among intermediates, facilitating the activation and adsorption of N₂, thereby exhibiting significant potential for ammonia synthesis through N₂ reduction. Particularly, four catalysts screened by ML and DFT exhibit good stability and excellent selectivity and activation towards N₂. Among them, the catalysts Ti-Cr@N₆G, Ti-Mo@N₆G, and Ti-Pd@N₆G possess two reaction pathways with minimum reaction energies of 0.55 eV, 0.50 eV, and 0.40 eV, respectively. Remarkably, Ti-Co@N₆G, which features a single reaction pathway, exhibits a reaction energy lower than 0.05 eV, allowing the NRR to proceed spontaneously. It is noteworthy that incorporating ML into DFT calculations facilitates the rapid screening of all transition metal combinations, significantly accelerating the research on catalytic performance and optimizing the selection of catalysts.

Ammonia is an ideal candidate for clean energy in the future, and its large-scale production has long relied on the Haber–Bosch process, which operates at a high temperature and pressure. However, this process faces significant challenges due to the growing demand for ammonia and the increasing need for environmental protection. The high energy consumption and substantial CO₂ emissions associated with the Haber–Bosch method have greatly limited its application. Consequently, increasing research efforts have been devoted to developing green ammonia synthesis technologies. Among these, the electrocatalytic nitrogen reduction reaction (NRR), which uses water and nitrogen as raw materials to synthesize NH₃ under mild conditions, has emerged as a promising alternative. This method offers the potential for carbon neutrality and decentralized production when coupled with renewable electricity. However, it is important to note that the current energy efficiency and ammonia production rates of NRR under ambient aqueous conditions generally lag behind those of modern Haber–Bosch processes integrated with green hydrogen (H₂). As the core of the NRR process, the performance of electrocatalysts directly impacts the efficiency, energy consumption, and product selectivity of the entire reaction. To date, significant efforts have been made to identify the most suitable electrocatalysts. In this paper, we focus on the current research status of metal catalysts—including both precious and non-precious metals—as well as non-metal catalysts. We systematically review important advances in performance optimization, innovative design strategies, and mechanistic analyses of various catalysts. We clarify innovative optimization strategies for different catalysts and summarize and compare the catalytic effects of various catalyst types. Finally, we discuss the challenges facing electrocatalysis research and propose possible future development directions. Through this paper, we aim to provide guidance for the preparation of high-efficiency NRR catalysts and the future industrial application of electrochemical ammonia synthesis.

CO₂ hydrogenation to methanol has attracted considerable attention as a promising catalytic route for both reducing CO₂ emissions and producing valuable chemical intermediates. Among various catalysts, Cu–ZnO-based systems are the most widely studied; however, their performance remains constrained by limited methanol selectivity and stability, highlighting the need for improved catalytic strategies. In this work, liquid metal gallium (Ga) was incorporated into Cu–ZnO catalysts as an additive for CO₂ hydrogenation to methanol. Owing to its high dispersibility and fluidity, Ga helps maintain long-term catalyst stability. We investigated different introduction methods for Ga promoters and found that the physical mixing approach generated the strongest alkaline sites, thereby enhancing CO₂ activation and increasing the CO₂ conversion to methanol. Moreover, this catalyst effectively suppressed carbon deposition, further improving its stability. These findings offer new insights into the use of liquid metal Ga in CO₂ hydrogenation and provide fresh perspectives for the rational design of efficient methanol synthesis catalysts.