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#explainable ai Review Open access

Dynamic Reconstruction of Atomically Dispersed Copper Catalysts for CO 2 Reduction: From In Situ Observations to Rational Design

Unknown authors
Sep 2026 · EcoEnergy · 0 citations · 76 references

Abstract

The electrocatalytic CO 2 reduction reaction (CO 2 RR) to useful multicarbon (C 2+ ) products offers a way to help achieve carbon neutrality. Copper‐based catalysts are uniquely capable of achieving this efficiently; however, when used as single atoms or dual‐atom pairs, their structures change significantly during reactions. This change makes it difficult to apply traditional models that link a catalyst's shape to its performance, which hinders the design of high‐performance catalysts. To bridge this gap, this review presents a comprehensive framework focused on the behaviors and mechanisms of such dynamically evolving copper‐based catalysts in CO 2 RR. First, it explains how C 2+ products are formed at the atomic level, describing three main ways in which carbon atoms bond: symmetric, asymmetric, and single‐site dynamic coupling. Second, it summarizes the primary features that affect the degree to which these catalysts form C 2+ products, especially the changing environment and oxidation state (Cu + /Cu 0 ratio) during the reaction. Next, the discussion elucidates how external factors, such as electrolyte and electrolysis conditions, influence their dynamic surface reconstruction. Finally, emphasis is placed on the shift from passive observation to active catalyst design, driven by multiscale theoretical simulations and automated AI chemists. This offers practical insights into developing efficient atomically dispersed Cu‐based catalysts suitable for industrial use.

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