journal article·2023-12

An ultrafast carrier dynamics system from oxygen vacancies modified SnO2 QDs and Zn2SnO4 heterojunction for deeply photocatalytic oxidation of NO

Yuhan Li, Min Zhang, Bangfu Chen, Ping Ouyang, Youyu Duan, Kangle Lv, Fan Dong

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Abstract

Deeply photocatalytic oxidation of NO-to-NO3– holds great promise for alleviating NOx pollution. The major challenge of NO photo-oxidation is the highly in-situ generated NO2 concentration, and the formation of unstable nitrate species causes desorption to release NO2. In this study, SnO2 quantum dots and oxygen vacancies co-modified Zn2SnO4 (ZSO-SnO2-OVs) were prepared by a one-step hydrothermal procedure, the NO photo-oxidation was investigated by a combination of solid experimental and theoretical support. Impressively, spectroscopic measurements indicate that fast carrier dynamics can be achieved due to the electron transfer efficiency of ZSO-SnO2-OVs reaching 99.99%, far outperforming the counterpart and previously reported photocatalysts. During NO oxidation, molecular NO/O2 and H2O are efficiently adsorbed/activated around OVs and SnO2 QDs, respectively. In-situ infrared measurements and calculated electron localized function disclose two main findings: (1) richly electrons enable NO promptly form NO– instead of toxic NO2 or NO+; (2) the generation of stable and undecomposed bidentate NO3– rather than bridging or monodentate one benefits the deep oxidation of NO via shifting reaction sites from O terminals for original ZSO to Sn ones for ZSO-SnO2-OVs. The synergistic action of SnO2 QDs and OVs positively contributes to the NO oxidation performance enhancement (60.6%, 0.1 g of sample) and high selectivity of NO to NO3– (99.2%). Results from this study advance the mechanistic understanding of NO photo-oxidation and its selectivity to NO3– over photocatalysts.
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Research context

OpenAlex topics: Catalytic Processes in Materials Science · Advanced Photocatalysis Techniques · Gas Sensing Nanomaterials and Sensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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