Activity self-optimization steered by dynamically evolved Fe³+@Fe₂+ double-center on Fe₂O₃ catalyst for NH₃-SCR

Identification of the active centers dynamically stable under the reaction condition is of paramount importance but challenging because of the limited knowledge of steady-state chemistry on catalysts at the atomic level. Herein, focusing on the Fe O catalyst for the selective catalytic reduction of NO with NH (NH -SCR) as a model system, we reveal quantitatively the self-evolving Fe @Fe (∼1:1) double-centers under the in-situ condition by the first-principles microkinetic simulations, which enables the accurate prediction of the optimal industry operating temperature (590 K). The cooperation of this double-center achieves the self-optimization of catalytic activity and rationalizes the intrinsic origin of Fe O catalyzing NH -SCR at middle-high temperatures instead of high temperatures. Our findings demonstrate the atomic-level self-evolution of active sites and the dynamically adjusted activity variation of the catalyst under the in-situ condition during the reaction process and provide insights into the reaction mechanism and catalyst optimization.