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Statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto Rosa damascena leaves as a low-cost biosorbent
In this study, Rosa damascena leaf powder was evaluated as a biosorbent for the removal of copper from aqueous solutions. Process variables such as the biosorbent dose, pH, and initial copper concentration were optimized using response surface methodology. A quadratic model was established to relate...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9123003/ https://www.ncbi.nlm.nih.gov/pubmed/35595800 http://dx.doi.org/10.1038/s41598-022-12233-1 |
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author | Fawzy, Mustafa A. Al-Yasi, Hatim M. Galal, Tarek M. Hamza, Reham Z. Abdelkader, Tharwat G. Ali, Esmat F. Hassan, Sedky H. A. |
author_facet | Fawzy, Mustafa A. Al-Yasi, Hatim M. Galal, Tarek M. Hamza, Reham Z. Abdelkader, Tharwat G. Ali, Esmat F. Hassan, Sedky H. A. |
author_sort | Fawzy, Mustafa A. |
collection | PubMed |
description | In this study, Rosa damascena leaf powder was evaluated as a biosorbent for the removal of copper from aqueous solutions. Process variables such as the biosorbent dose, pH, and initial copper concentration were optimized using response surface methodology. A quadratic model was established to relate the factors to the response based on the Box–Behnken design. Analysis of variance (ANOVA) was used to assess the experimental data, and multiple regression analysis was used to fit it to a second-order polynomial equation. A biosorbent dose of 4.0 g/L, pH of 5.5, and initial copper concentration of 55 mg/L were determined to be the best conditions for copper removal. The removal of Cu(2+) ions was 88.7% under these optimal conditions, indicating that the experimental data and model predictions were in good agreement. The biosorption data were well fitted to the pseudo-second-order and Elovich kinetic models. The combination of film and intra-particle diffusion was found to influence Cu(2+) biosorption. The Langmuir and Dubinin–Radushkevich isotherm models best fit the experimental data, showing a monolayer isotherm with a q(max) value of 25.13 mg/g obtained under optimal conditions. The thermodynamic parameters showed the spontaneity, feasibility and endothermic nature of adsorption. Scanning electron microscopy, energy-dispersive X-ray spectroscopy, and Fourier transform infrared spectroscopy were used to characterize the biosorbent before and after Cu(2+) biosorption, revealing its outstanding structural characteristics and high surface functional group availability. In addition, immobilized R. damascena leaves adsorbed 90.7% of the copper from aqueous solution, which is more than the amount adsorbed by the free biosorbent (85.3%). The main mechanism of interaction between R. damascena biomass and Cu(2+) ions is controlled by both ion exchange and hydrogen bond formation. It can be concluded that R. damascena can be employed as a low-cost biosorbent to remove heavy metals from aqueous solutions. |
format | Online Article Text |
id | pubmed-9123003 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91230032022-05-22 Statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto Rosa damascena leaves as a low-cost biosorbent Fawzy, Mustafa A. Al-Yasi, Hatim M. Galal, Tarek M. Hamza, Reham Z. Abdelkader, Tharwat G. Ali, Esmat F. Hassan, Sedky H. A. Sci Rep Article In this study, Rosa damascena leaf powder was evaluated as a biosorbent for the removal of copper from aqueous solutions. Process variables such as the biosorbent dose, pH, and initial copper concentration were optimized using response surface methodology. A quadratic model was established to relate the factors to the response based on the Box–Behnken design. Analysis of variance (ANOVA) was used to assess the experimental data, and multiple regression analysis was used to fit it to a second-order polynomial equation. A biosorbent dose of 4.0 g/L, pH of 5.5, and initial copper concentration of 55 mg/L were determined to be the best conditions for copper removal. The removal of Cu(2+) ions was 88.7% under these optimal conditions, indicating that the experimental data and model predictions were in good agreement. The biosorption data were well fitted to the pseudo-second-order and Elovich kinetic models. The combination of film and intra-particle diffusion was found to influence Cu(2+) biosorption. The Langmuir and Dubinin–Radushkevich isotherm models best fit the experimental data, showing a monolayer isotherm with a q(max) value of 25.13 mg/g obtained under optimal conditions. The thermodynamic parameters showed the spontaneity, feasibility and endothermic nature of adsorption. Scanning electron microscopy, energy-dispersive X-ray spectroscopy, and Fourier transform infrared spectroscopy were used to characterize the biosorbent before and after Cu(2+) biosorption, revealing its outstanding structural characteristics and high surface functional group availability. In addition, immobilized R. damascena leaves adsorbed 90.7% of the copper from aqueous solution, which is more than the amount adsorbed by the free biosorbent (85.3%). The main mechanism of interaction between R. damascena biomass and Cu(2+) ions is controlled by both ion exchange and hydrogen bond formation. It can be concluded that R. damascena can be employed as a low-cost biosorbent to remove heavy metals from aqueous solutions. Nature Publishing Group UK 2022-05-20 /pmc/articles/PMC9123003/ /pubmed/35595800 http://dx.doi.org/10.1038/s41598-022-12233-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Fawzy, Mustafa A. Al-Yasi, Hatim M. Galal, Tarek M. Hamza, Reham Z. Abdelkader, Tharwat G. Ali, Esmat F. Hassan, Sedky H. A. Statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto Rosa damascena leaves as a low-cost biosorbent |
title | Statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto Rosa damascena leaves as a low-cost biosorbent |
title_full | Statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto Rosa damascena leaves as a low-cost biosorbent |
title_fullStr | Statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto Rosa damascena leaves as a low-cost biosorbent |
title_full_unstemmed | Statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto Rosa damascena leaves as a low-cost biosorbent |
title_short | Statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto Rosa damascena leaves as a low-cost biosorbent |
title_sort | statistical optimization, kinetic, equilibrium isotherm and thermodynamic studies of copper biosorption onto rosa damascena leaves as a low-cost biosorbent |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9123003/ https://www.ncbi.nlm.nih.gov/pubmed/35595800 http://dx.doi.org/10.1038/s41598-022-12233-1 |
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