Homonuclear dual-atom catalysts embedded on N-doped graphene for highly efficient nitrate reduction to ammonia: From theoretical prediction to experimental validation

Electrocatalytic reduction of nitrate (NO3−) to ammonia (NRA) is emerging as an attractive strategy to attain valuable NH3 synthesis and harmful NO3− removal, but developing efficient electrocatalysts remains challenging. Herein, taking homonuclear dual metal catalysts (DACs) embedded on N-doped graphene as the example, we proposed a three-step strategy to theoretically evaluate their NRA catalytic performance by means of density functional theory (DFT) computations, which enables us to rapidly identify Cu2@N3−6 as the most promising NRA catalyst with a low limiting potential (−0.14 V). More importantly, such theoretical prediction was further validated by our proof-of-concept experiment: the NH3 yield rate of ∼18.2 mg h−1 cm−2 at − 0.8 V vs RHE and the Faradaic efficiency of 97.4% were achieved. Our studies may offer a feasible avenue to rapidly and precisely achieve efficient NRA catalysts by using theoretical prediction as a guideline for experimentalists to avoid the traditional "trial and error method".