Machine learning predict the degradation efficiency of aqueous refractory organic pollutants by ultrasound-based advanced oxidation processes-Reference-Cited by-同舟云学术

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Machine learning predict the degradation efficiency of aqueous refractory organic pollutants by ultrasound-based advanced oxidation processes

Published:2024-09 Issue: Volume:66 Page:106022
ISSN:2214-7144
Container-title:Journal of Water Process Engineering
language:en
Short-container-title:Journal of Water Process Engineering

Author:

Liu Shiqi,Long Zeqing,Liu Huize,Zhang Jie,Zhang Guangming,Liang Jinsong

Funder

Hebei Provincial Natural Science Foundation

Publisher

Elsevier BV

Reference48 articles.

1. Degradation of antibiotic amoxicillin from pharmaceutical industry wastewater into a continuous flow reactor using supercritical water gasification;Dias;Water Res.,2023

2. Nano zero-valent iron-based fiber electrode for efficient electro-Fenton treatment of pharmaceutical wastewater: mechanism of degradation and sterilization;Ma;Chem. Eng. J.,2023

3. Photocatalytic activation of PMS over magnetic heterojunction photocatalyst SrTiO3/BaFe12O19 for tetracycline ultrafast degradation;Feng;Chem. Eng. J.,2023

4. Enhanced H2O2 activation and sulfamethoxazole degradation by Fe-impregnated biochar;Zhang;Chem. Eng. J.,2020

5. A review of bioelectrochemical systems for antibiotic removal: efficient antibiotic removal and dissemination of antibiotic resistance genes;Zhang;J. Water Process Eng.,2020

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