Volume 10, Issue 4 (3-2023)
2023, 10(4): 12-23 |
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Z G, M A A, M H S, F K. Elimination of antibiotics from aqueous solutions using graphitic adsorbent functionalized with ionic liquid and optimized through response surface methodology. Journal title 2023; 10 (4) :12-23
URL: http://jms.thums.ac.ir/article-1-1178-en.html
URL: http://jms.thums.ac.ir/article-1-1178-en.html
1- Islamic Azad University of Omidiyeh
2- yasouj university
2- yasouj university
Abstract: (1314 Views)
Background & Aim: Antibiotic contaminants observed in waters have become a significant concern in recent years. In this study, a new engineered nanosorbent was developed to remove fluoroquinolone antibiotic from water
Methods: Nanoabsorbent (IL@GCN@IL) was prepared by immobilizing a bi-cationic ionic liquid on a substrate of graphitic carbon nitride (GCN). The performance of this nanoabsorbent was evaluated under various parameters such as adsorbent dose, antibiotic concentration, time and temperature. Generalized regression neural network (GRNN) and response surface method (RSM) were used to model the removal.
Results: This nanoabsorbent showed a good absorption performance, so that the removal precentage of ciprofloxacin (CPF) was 96.23%. The adsorption process followed the Freundlich isothermal pseudo-second-order kinetic model, indicating a heterogeneous chemisorption process
Conclusion: This nanoabsorbent showed good reusability and can be an ideal and promising candidate for removing antibiotic pollutants from aqueous solutions. Overall, this study highlights the potential of engineered nanosorbents as effective adsorbents for the removal of antibiotic contaminants from water, which can have significant implications for water treatment and environmental protection.
Methods: Nanoabsorbent (IL@GCN@IL) was prepared by immobilizing a bi-cationic ionic liquid on a substrate of graphitic carbon nitride (GCN). The performance of this nanoabsorbent was evaluated under various parameters such as adsorbent dose, antibiotic concentration, time and temperature. Generalized regression neural network (GRNN) and response surface method (RSM) were used to model the removal.
Results: This nanoabsorbent showed a good absorption performance, so that the removal precentage of ciprofloxacin (CPF) was 96.23%. The adsorption process followed the Freundlich isothermal pseudo-second-order kinetic model, indicating a heterogeneous chemisorption process
Conclusion: This nanoabsorbent showed good reusability and can be an ideal and promising candidate for removing antibiotic pollutants from aqueous solutions. Overall, this study highlights the potential of engineered nanosorbents as effective adsorbents for the removal of antibiotic contaminants from water, which can have significant implications for water treatment and environmental protection.
Type of Study: Research |
Subject:
General
Received: 2023/05/21 | Accepted: 2023/06/19 | Published: 2023/07/3
Received: 2023/05/21 | Accepted: 2023/06/19 | Published: 2023/07/3
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