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

Hai Yang Yuan, Ningning Sun, Jianfu Chen, Hua Gui Yang, P Hu, Haifeng Wang

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
42 Downloads (Pure)

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 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.
Original languageEnglish
Pages (from-to)2352-2358
JournalJACS Au
Volume2
Issue number10
Early online date21 Sept 2022
DOIs
Publication statusPublished - 24 Oct 2022

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