ABSTRACT The electrochemical nitrate reduction reaction (eNO 3 RR) to ammonia (NH 3 ) is a key for producing fuels during interstellar travel and an alternative to Haber−Bosch process. However, the complicated multi‐electron/proton transfer electrode process of eNO 3 RR makes affordable electrocatalyst discovery and its mechanistic understanding challenging. Herein, we established a human–machine collaboration framework by employing dimensionally reduced reaction descriptors which enables an accelerated data‐driven discovery‐to‐unveiling of unconventional and high‐performance eNO 3 RR electrocatalysts with desirable element choice. Using the current density difference between nitrite (NO 2 − ) reduction and hydrogen evolution as a descriptor, the optimal FeCoNiCuGa electrocatalyst was identified in a drastically short timeframe. Even compared with Pt or Rh, the FeCoNiCuGa exhibits a higher NH 3 production rate of 9.8 mmol mg cat −1 at −0.3 V versus a reversible hydrogen electrode. Furthermore, together with a mechanistic study using rotating ring‐disk electrode combined with a new kinetic model, in situ infrared spectroscopy unveiled that the adsorbed NO 2 − (*NO 2 − ) plays a crucial role in the efficient electrode process: a moderate *NO 2 − binding accelerates NH 3 formation whereas a weak binding leads to unfavorable reactions. Our work demonstrates that a comprehensive human–machine collaboration approach enables an accelerated discovery‐to‐unveiling of promising electrode processes, providing a feasible way to promote game‐changing electrochemical technologies.
Cheng et al. (Fri,) studied this question.
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