Catalysis AI Agent Guides Discovering the Universal Design Principle of Cu‐Based Single‐Atom Alloy Catalysts for CO ₂ Electroreduction

Abstract

ABSTRACT Copper (Cu)‐based single‐atom alloys (SAAs) represent a promising strategy for optimizing the electroreduction of CO 2 (CO 2 R) to multi‐carbon products (C 2+ ). However, the diverse enhancement degrees of C 2+ selectivity brought about by various dopants have not yet been rationalized, which lead to the absence of guidelines for further designing desired Cu‐based SAAs. Herein, guided by the Catalysis AI Agent developed based on large‐scale data + large language model, as well as the Digital Catalysis Platform (the DigCat experimental database), we performed first‐principles calculations to evaluate C 2+ products selectivity trends through identifying the energy barrier of rate‐determining step (RDS) among diverse C‐C coupling pathways. With first‐principles results fed back, Catalysis AI Agent reveals that the element classification in the periodic table of guest metal dopant is essential for establishing robust structure‐selectivity correlations among Cu‐based SAAs. A structural descriptor (φ) is developed and helps to establish a strong correlation among the electronic‐scale structural features, the adsorption strength of C‐C coupling precursors, and the macroscopic C 2+ products selectivity. A universal design principle based on φ for Cu‐based SAAs enables the rapid and qualitative evaluation of C 2+ selectivity, which is fully supported by most of the experimental references and our experimental verification.