Quantifying the Two-Dimensional Driving Patterns of Chemisorbed Oxygen and Particle Size on NO Reduction Activity and Mechanism

ACS Appl Mater Interfaces. 2023 Jul 26;15(29):34838-34851. doi: 10.1021/acsami.3c05162. Epub 2023 Jul 15.

Abstract

Quantification in the driving patterns of activity descriptors on structure-activity relationships and reaction mechanisms over heterogeneous catalysts is still a great challenge and needs to be addressed urgently. Herein, with the example of typical Mn-based catalysts, based on the activity regularity and many characterizations, the chemisorbed oxygen density (ρOβ) and particle size (dTEM) have been proposed as the two-dimensional descriptors for selective catalytic reduction of NO, whose role is in quantifying the contents of vacancy defects and the amounts of active sites located on terraces or interfaces, respectively. They can be utilized to construct and quantify the driving patterns for the structure-activity relationships and reaction mechanisms of NO reduction. As a consequence, a complementary modulation for Ea by ρOβ and dTEM is described quantitatively in terms of the fitted functions. Moreover, based on the structure-activity relationships and the quantification laws of in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), the reaction efficiency (RE) of the specific combined NOx-intermediate is identified as the trigger to drive the Langmuir-Hinshelwood mechanism and modulated by the descriptors complementally and collaboratively following the fitted quantification functions. Either of the two descriptors at its lower values plays a dominant role in regulating Ea and RE, and the dominant factor evolves progressively: dTEM ↔ coupling dTEM with ρOβ ↔ ρOβ, when the dependency of Ea and RE on the descriptors is adopted to identify the dominant factor and domains. Therefore, this work has quantitatively accounted for the essence of activity modulation and may provide insight into the quantitative driving patterns for reaction activity and mechanism.

Keywords: driving patterns; reaction mechanisms; selective catalytic reduction of NO; structure−activity relationships; two-dimensional descriptors.