Degradation of Bisphenol A Using Self-Excited Oscillating Jets in Synergy with Fenton and Periodate Oxidation: Experimental and Artificial Neural Network Modeling Study DOI Open Access

Jian Wang,

Bingsheng Li,

Shiwei Xie

et al.

Water, Journal Year: 2024, Volume and Issue: 16(16), P. 2326 - 2326

Published: Aug. 18, 2024

Bisphenol A (BPA) is an environmental endocrine-disrupting compound that resistant to conventional biological treatment, making it crucial develop oxidation process. This study introduces a novel hydrodynamic cavitation (HC) coupled with Fenton + periodate (PI) system for the efficient degradation of BPA. By systematically examining key parameters such as inlet pressure, Fe (II), H2O2, and PI concentration, was found HC performed optimally at pressure 0.5 MPa. conversion 98.14% achieved within 60 min when molar ratio BPA, approximately 1:1:5:1. Further analysis revealed gray correlation between H2O2 concentrations on efficiency 0.833 0.843, respectively, indicating both them had significant effects The free radical quenching assay confirmed hydroxyl (•OH) main active substance. Additionally, toxicity intermediates evaluated using Toxicity Estimation Software Tool (TEST). An artificial neural network (ANN)-based model constructed predict BPA-degradation process, facilitating precise reagent dosing providing robust support intelligent application water-treatment technologies.

Language: Английский

Targeted Comparative Analysis of Gas Injection Strategies to Enhance Hydrodynamic Cavitation for Effective Wastewater Treatment DOI Creative Commons

Esmail Noshadi,

Maziar Changizian, Morteza Behbahani-Nejad

et al.

Water Air & Soil Pollution, Journal Year: 2025, Volume and Issue: 236(2)

Published: Jan. 20, 2025

Language: Английский

Citations

1
Synergistic Enhancement in Hydrodynamic Cavitation combined with Peroxymonosulfate Fenton-like Process for BPA Degradation: New Insights into the Role of Cavitation Bubbles in Regulation Reaction Pathway DOI

Hongkun Han,

Mengfan Chen,

Congting Sun

et al.

Water Research, Journal Year: 2024, Volume and Issue: 268, P. 122666 - 122666

Published: Oct. 19, 2024

Language: Английский

Citations

6
Design of new CoFe2O4/MXene/NaTaO3 double heterostructures for efficient photodegradation of antibiotic DOI
Wenying Shi,

Xiaofeng Sun,

Minghui Xu

et al.

Journal of Water Process Engineering, Journal Year: 2024, Volume and Issue: 67, P. 106229 - 106229

Published: Sept. 28, 2024

Language: Английский

Citations

5
Catalytic behaviour of iron-based nanomaterials for the remediation of hazardous chemicals from wastewater: A Review DOI
Guddappa Halligudra,

S. Chetana,

Seema Singh

et al.

Journal of Physics and Chemistry of Solids, Journal Year: 2025, Volume and Issue: unknown, P. 112735 - 112735

Published: March 1, 2025

Language: Английский

Citations

0
Electrostatic Field Modification Enhances the Electrocatalytic Oxygen Evolution Reaction Stability of CoFe2O4 Catalysts DOI Creative Commons

Liwen Liang,

Jiatong Miao,

Xiyuan Feng

et al.

Micromachines, Journal Year: 2025, Volume and Issue: 16(5), P. 491 - 491

Published: April 22, 2025

Enhancing the stability of oxygen evolution reaction (OER) catalysts is a critical challenge for realizing efficient water splitting. In this work, we introduce an innovative approach by applying electric field during annealing CoFe2O4/C catalyst. By controlling strength (100 mV) and treatment duration (1 h), achieved dual optimization catalyst’s microstructure electronic environment, resulting in significant improvement catalytic stability. The experimental results demonstrate that field-treated catalyst exhibits reduced overpotential decay (only 0.8 enhanced (retaining 89.1% its initial activity after 24 h) extended OER testing. This performance significantly surpasses untreated sample, which showed 1.5 mV retained only 72.5% h. X-ray photoelectron spectroscopy (XPS) analysis confirmed promoted formation vacancies, substantially improved electron transfer efficiency, optimized local environment Co2+/Co3+ Fe2+/Fe3+, leading to decrease charge resistance (Rct) from 58.2 Ω 42.9 Ω. study not presents novel strategy modulating via fields but also broadens design concepts materials establishing structure–activity relationship between strength, microstructure, performance, ultimately providing theoretical foundation guidance development highly stable splitting catalysts.

Language: Английский

Citations

0
Photocatalytic activation of peroxymonosulfate by Bi2WO6/Fe3O4/ZrO2 magnetic composite for degradation of cloxacillin, moxifloxacin, and azithromycin antibiotics under visible LED light irradiation DOI

Neda Ravankhah,

Mohammad Reza Rezaei, Meghdad Pirsaheb

et al.

Journal of Water Process Engineering, Journal Year: 2025, Volume and Issue: 74, P. 107791 - 107791

Published: April 24, 2025

Language: Английский

Citations

0
Degradation of Bisphenol A Using Self-Excited Oscillating Jets in Synergy with Fenton and Periodate Oxidation: Experimental and Artificial Neural Network Modeling Study DOI Open Access

Jian Wang,

Bingsheng Li,

Shiwei Xie

et al.

Water, Journal Year: 2024, Volume and Issue: 16(16), P. 2326 - 2326

Published: Aug. 18, 2024

Bisphenol A (BPA) is an environmental endocrine-disrupting compound that resistant to conventional biological treatment, making it crucial develop oxidation process. This study introduces a novel hydrodynamic cavitation (HC) coupled with Fenton + periodate (PI) system for the efficient degradation of BPA. By systematically examining key parameters such as inlet pressure, Fe (II), H2O2, and PI concentration, was found HC performed optimally at pressure 0.5 MPa. conversion 98.14% achieved within 60 min when molar ratio BPA, approximately 1:1:5:1. Further analysis revealed gray correlation between H2O2 concentrations on efficiency 0.833 0.843, respectively, indicating both them had significant effects The free radical quenching assay confirmed hydroxyl (•OH) main active substance. Additionally, toxicity intermediates evaluated using Toxicity Estimation Software Tool (TEST). An artificial neural network (ANN)-based model constructed predict BPA-degradation process, facilitating precise reagent dosing providing robust support intelligent application water-treatment technologies.

Language: Английский

Citations

0