Activity Self-Optimization Steered by Dynamically Evolved Fe3+@Fe2+ Double-Center on Fe2O3 Catalyst for NH3-SCR.

Abstract

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 Fe2O3 catalyst for the selective catalytic reduction of NO with NH3 (NH3-SCR) as a model system, we reveal quantitatively the self-evolving Fe3+@Fe2+ (∼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 Fe2O3 catalyzing NH3-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.