دورية أكاديمية
Response Methodology Optimization and Artificial Neural Network Modeling for the Removal of Sulfamethoxazole Using an Ozone-Electrocoagulation Hybrid Process.
| العنوان: | Response Methodology Optimization and Artificial Neural Network Modeling for the Removal of Sulfamethoxazole Using an Ozone-Electrocoagulation Hybrid Process. |
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| المؤلفون: | Nghia NT; Faculty of Chemical and Environmental Technology, Hung Yen University of Technology and Education, Khoai Chau District, Hung Yen 17817, Vietnam., Tuyen BTK; Faculty of Chemistry, TNU-University of Sciences, Thai Nguyen City 25000, Vietnam., Quynh NT; Faculty of Chemistry, TNU-University of Sciences, Thai Nguyen City 25000, Vietnam., Thuy NTT; Faculty of Chemistry, TNU-University of Sciences, Thai Nguyen City 25000, Vietnam., Nguyen TN; Faculty of Chemical and Environmental Technology, Hung Yen University of Technology and Education, Khoai Chau District, Hung Yen 17817, Vietnam., Nguyen VD; Faculty of Chemistry, TNU-University of Sciences, Thai Nguyen City 25000, Vietnam., Tran TKN; Institute of Applied Technology and Sustainable Development, Nguyen Tat Thanh University, Ho Chi Minh City 70000, Vietnam. |
| المصدر: | Molecules (Basel, Switzerland) [Molecules] 2023 Jun 29; Vol. 28 (13). Date of Electronic Publication: 2023 Jun 29. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: MDPI Country of Publication: Switzerland NLM ID: 100964009 Publication Model: Electronic Cited Medium: Internet ISSN: 1420-3049 (Electronic) Linking ISSN: 14203049 NLM ISO Abbreviation: Molecules Subsets: PubMed not MEDLINE; MEDLINE |
| أسماء مطبوعة: | Original Publication: Basel, Switzerland : MDPI, c1995- |
| مواضيع طبية MeSH: | Ozone*/chemistry , Water Pollutants, Chemical*/chemistry, Sulfamethoxazole/chemistry ; Ecosystem ; Anti-Bacterial Agents ; Electrocoagulation ; Neural Networks, Computer ; Water |
| مستخلص: | Removing antibiotics from water is critical to prevent the emergence and spread of antibiotic resistance, protect ecosystems, and maintain the effectiveness of these vital medications. The combination of ozone and electrocoagulation in wastewater treatment provides enhanced removal of contaminants, improved disinfection efficiency, and increased overall treatment effectiveness. In this work, the removal of sulfamethoxazole (SMX) from an aqueous solution using an ozone-electrocoagulation (O-EC) system was optimized and modeled. The experiments were designed according to the central composite design. The parameters, including current density, reaction time, pH, and ozone dose affecting the SMX removal efficiency of the OEC system, were optimized using a response surface methodology. The results show that the removal process was accurately predicted by the quadric model. The numerical optimization results show that the optimum conditions were a current density of 33.2 A/m 2 , a time of 37.8 min, pH of 8.4, and an ozone dose of 0.7 g/h. Under these conditions, the removal efficiency reached 99.65%. A three-layer artificial neural network (ANN) with logsig-purelin transfer functions was used to model the removal process. The data predicted by the ANN model matched well to the experimental data. The calculation of the relative importance showed that pH was the most influential factor, followed by current density, ozone dose, and time. The kinetics of the SMX removal process followed the first-order kinetic model with a rate constant of 0.12 (min -1 ). The removal mechanism involves various processes such as oxidation and reduction on the surface of electrodes, the reaction between ozone and ferrous ions, degradation of SMX molecules, formation of flocs, and adsorption of species on the flocs. The results obtained in this work indicate that the O-EC system is a potential approach for the removal of antibiotics from water. |
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| معلومات مُعتمدة: | CS2021-TN06-14 TNU-University of Sciences, |
| فهرسة مساهمة: | Keywords: electrocoagulation; optimization; ozone; removal efficiency; sulfamethoxazole |
| المشرفين على المادة: | JE42381TNV (Sulfamethoxazole) 66H7ZZK23N (Ozone) 0 (Water Pollutants, Chemical) 0 (Anti-Bacterial Agents) 059QF0KO0R (Water) |
| تواريخ الأحداث: | Date Created: 20230714 Date Completed: 20230717 Latest Revision: 20230718 |
| رمز التحديث: | 20240628 |
| مُعرف محوري في PubMed: | PMC10343529 |
| DOI: | 10.3390/molecules28135119 |
| PMID: | 37446780 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1420-3049 |
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| DOI: | 10.3390/molecules28135119 |