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

Abstract 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 limited due to the ubiquitous energy-scaling relations. With interpretable machine learning, we unravel a mechanism of breaking adsorption-energy scaling relations through the site-specific Pauli repulsion interactions of the metal d -states with adsorbate frontier orbitals. The non-scaling behavior can be realized on (100)-type sites of ordered B2 intermetallics, in which the orbital overlap between the…

• NS
  National Science Foundation

  Awards: CBET-1845531, CAREER, 1845531, 2102363, CHE-2102363
• VP
  Virginia Polytechnic Institute and State University
• NR
  National Research Foundation
• DF
  Directorate for Engineering

  Awards: CBET- 2143710, CBET-1845531
• DO
  Division of Chemical, Bioengineering, Environmental, and Transport Systems

  Awards: 1845531, CBET-1845531
• DO
  Division of Chemistry

  Awards: CAREER, CHE-2102363