Machine-learning-guided design of Co-Cu bimetallic single-atom sites for electrochemical nitrate-to-ammonia conversion

Xinyu Zou

doi:10.1016/j.jcat.2026.117118

Machine-learning-guided design of Co-Cu bimetallic single-atom sites for electrochemical nitrate-to-ammonia conversion

2026-08-09

0

PRE

AI

X

Xinyu Zou

W

Wensheng Liu

M

Meng Ji

S

Songze Li

M

Maocong Hu *

M

Mao Peng *

Z

Zhenhua Yao *

K

Kwan San Hui *

T

Tao Ye *

DOI：10.1016/j.jcat.2026.117118

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• ML screening identifies Co–Cu diatomic sites for NO3RR. • CoCuN4/CNT achieves 92.9% Faradaic efficiency for NH3. • Diatomic Co–Cu motif balances nitrate activation and hydrogenation. • In situ Raman and DFT reveal synergistic NO3RR mechanism. • Zn–NO3− battery demonstrates coupled energy–environment application.

Machine-learning-guided design of Co-Cu bimetallic single-atom sites for electrochemical nitrate-to-ammonia conversion

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