Artificial intelligence-aided preparation of perovskite SrFexZr1-xO3-δ catalysts for ozonation degradation of organic pollutant concentrated water after membrane treatment.

Xu Wang, Yanan Zhang, Cheng Zhang, Huangzhao Wei, Haibo Jin, Zhao Mu, Xiaofei Chen, Xinru Chen, Pin Wang, Xiaoyan Guo, Fuchen Ding, Xiaowei Liu, Lei Ma

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Membrane technology has been widely used to treat wastewater from a variety of industries, but it also results in a large amount of concentrated wastewater containing organic pollutants after membrane treatment, which is challenging to decompose. Here in this work, a series of perovskite SrFexZr1-xO3-δ catalysts were prepared via a modified co-precipitation method and evaluated for catalytic ozone oxidative degradation of m-cresol. An artificial neural intelligence networks (ANN) model was employed to train the experimental data to optimize the preparation parameters of catalysts, with SrFe0.13Zr0.87O3-δ being the optimal catalysts. The resultant catalysts before and after reduction were then thoroughly characterized and tested for m-cresol degradation. It was found that the co-doping of Fe and Zr at the B-site and the improvement of oxygen vacancies and oxygen active species by reduction dramatically increased TOC removal rates up to 5 times compared with ozone alone, with the conversion rate of m-cresol reaching 100%. We also proposed a possible mechanism for m-cresol degradation via investigating the intermediates using GC-MS, and confirmed the good versatility of the reduced SrFe0.13Zr0.87O3-δ catalyst to remove other common organic pollutants in concentrated wastewater. This work demonstrates new prospects for the use of perovskite materials in wastewater treatment.
Original languageEnglish (US)
Pages (from-to)137825
JournalChemosphere
DOIs
StatePublished - Jan 19 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-01-26
Acknowledgements: This research was supported by National Natural Science Foundation of China (52100072, 52100213), the Fundamental Research Funds for the Central Universities (No. JZ2021HGTA0159 and No. JZ2021HGQA0212), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA21021101), the Scientific Research Common Program of Beijing Municipal Commission of Education (KM202010017006), the Beijing Natural Science Foundation (8214056), and the Undergraduates Research Training Program (2021X00142)..

ASJC Scopus subject areas

  • Environmental Chemistry
  • General Chemistry

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