Breaking adsorption-energy scaling limitations of electrocatalytic nitrate reduction on intermetallic CuPd nanocubes by machine-learned insights

• Published in: Nature communications Vol. 13; no. 1; pp. 2338 - 12
• Main Authors: Gao, Qiang, Pillai, Hemanth Somarajan, Huang, Yang, Liu, Shikai, Mu, Qingmin, Han, Xue, Yan, Zihao, Zhou, Hua, He, Qian, Xin, Hongliang, Zhu, Huiyuan
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 29.04.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 119/118; 140/131; 140/146; 147/137; 639/301/299/886; 639/638/161/886; 639/638/563; Active sites; Adsorbates; Adsorption; Ammonia; Chemical reduction; Electrocatalysts; Electrochemistry; Energy; Humanities and Social Sciences; INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Intermetallic compounds; Learning algorithms; Machine learning; multidisciplinary; Nanocrystals; Nitrate reduction; Nitrates; Nitrogen; Nitrogen cycle; Scaling; Science; Science (multidisciplinary)

The electrochemical nitrate reduction reaction (NO 3 RR) to ammonia is an essential step toward restoring the globally disrupted nitrogen cycle. In search of highly efficient electrocatalysts, tailoring catalytic sites with ligand and strain effects in random alloys is a common approach but remains...