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State-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes
In this research, molecular dynamics (MD) simulation is used to investigate the efficiency of carbon nanotubes (CNT) and boron nitride nanotubes (BNNT) in removing lead ions from contaminated waters. Then the effect of functionalizing nanotubes with –COO– and COOH– functional groups and the nanotube...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349052/ https://www.ncbi.nlm.nih.gov/pubmed/37452035 http://dx.doi.org/10.1038/s41598-023-38442-w |
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author | Ghasemi, Zeinab Farzad, Farzaneh Zaboli, Ameneh Zeraatkar Moghaddam, Ali |
author_facet | Ghasemi, Zeinab Farzad, Farzaneh Zaboli, Ameneh Zeraatkar Moghaddam, Ali |
author_sort | Ghasemi, Zeinab |
collection | PubMed |
description | In this research, molecular dynamics (MD) simulation is used to investigate the efficiency of carbon nanotubes (CNT) and boron nitride nanotubes (BNNT) in removing lead ions from contaminated waters. Then the effect of functionalizing nanotubes with –COO– and COOH– functional groups and the nanotubes’ absorption performance of two different concentrations of lead ions are studied. To better evaluate adsorption process, the set of descriptors, such as interaction energies, radial distribution function, etc., are calculated. The MD results show that the absorption performance is significantly improved by modifying the surface of CNT and BNNT with functional groups. In addition, the adsorption capacity increases in higher concentrations of Pb ions at BNNTCOO– and CNTCOOH systems. The interaction energy of BNNTCOO– with a concentration of 50 lead ions is − 2879.28 kJ/mol, which is about 106 kJ/mol more negative than BNNTCOO– at a concentration of 20 lead ions. Also, it is observed that the functionalization of both nanotubes with –COO– increases their absorption capacity. The obtained results from this study provide significant information about the mechanisms of lead adsorption on the surface of nanotubes. |
format | Online Article Text |
id | pubmed-10349052 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103490522023-07-16 State-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes Ghasemi, Zeinab Farzad, Farzaneh Zaboli, Ameneh Zeraatkar Moghaddam, Ali Sci Rep Article In this research, molecular dynamics (MD) simulation is used to investigate the efficiency of carbon nanotubes (CNT) and boron nitride nanotubes (BNNT) in removing lead ions from contaminated waters. Then the effect of functionalizing nanotubes with –COO– and COOH– functional groups and the nanotubes’ absorption performance of two different concentrations of lead ions are studied. To better evaluate adsorption process, the set of descriptors, such as interaction energies, radial distribution function, etc., are calculated. The MD results show that the absorption performance is significantly improved by modifying the surface of CNT and BNNT with functional groups. In addition, the adsorption capacity increases in higher concentrations of Pb ions at BNNTCOO– and CNTCOOH systems. The interaction energy of BNNTCOO– with a concentration of 50 lead ions is − 2879.28 kJ/mol, which is about 106 kJ/mol more negative than BNNTCOO– at a concentration of 20 lead ions. Also, it is observed that the functionalization of both nanotubes with –COO– increases their absorption capacity. The obtained results from this study provide significant information about the mechanisms of lead adsorption on the surface of nanotubes. Nature Publishing Group UK 2023-07-14 /pmc/articles/PMC10349052/ /pubmed/37452035 http://dx.doi.org/10.1038/s41598-023-38442-w Text en © The Author(s) 2023 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 Ghasemi, Zeinab Farzad, Farzaneh Zaboli, Ameneh Zeraatkar Moghaddam, Ali State-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes |
title | State-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes |
title_full | State-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes |
title_fullStr | State-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes |
title_full_unstemmed | State-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes |
title_short | State-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes |
title_sort | state-of-the-art predictive modeling of heavy metal ions removal from the water environment using nanotubes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349052/ https://www.ncbi.nlm.nih.gov/pubmed/37452035 http://dx.doi.org/10.1038/s41598-023-38442-w |
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