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X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons
The X-ray absorption (XRA) method using digital image processing techniques is a reliable technique to determine the exhaustion degree of granular activated carbons (GACs). Using an innovative digital image processing technique, the identification of individual adsorbed molecules or ions in a GAC wa...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795858/ https://www.ncbi.nlm.nih.gov/pubmed/33379219 http://dx.doi.org/10.3390/ma14010091 |
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author | Puente Torres, Jeamichel Crespo Sariol, Harold Mariño Peacok, Thayset Yperman, Jan Adriaensens, Peter Carleer, Robert Brito Sauvanell, Ángel |
author_facet | Puente Torres, Jeamichel Crespo Sariol, Harold Mariño Peacok, Thayset Yperman, Jan Adriaensens, Peter Carleer, Robert Brito Sauvanell, Ángel |
author_sort | Puente Torres, Jeamichel |
collection | PubMed |
description | The X-ray absorption (XRA) method using digital image processing techniques is a reliable technique to determine the exhaustion degree of granular activated carbons (GACs). Using an innovative digital image processing technique, the identification of individual adsorbed molecules or ions in a GAC was possible. Adsorption isotherm models (Langmuir and Freundlich) were used to simulate the adsorption equilibrium data of Methylene Blue (MB), nickel, cobalt and iodine. Freundlich equation was found to have the highest value of R(2) compared with Langmuir. The identification of distinctive patterns applying XRA for different adsorbed ions and molecules onto GAC was explored. It is demonstrated that unique XRA configurations for each adsorbed ion or molecule are found, as well as a proportional relationship between its incident energy (needed to achieve maximum photon attenuation) and the (effective) atomic number, the adsorbate mass and the molar or atomic mass of adsorbed molecule or ion. XRA method in combination with image histogram modifications was used to obtain a digital signature of adsorbed ions/molecules, giving distinct GSI values for each one in the used energy range. Probabilistic models prove that XRA results are within relationships between effective atomic number and photonic interaction probability, reinforcing the potentialities of XRA for monitoring (multi-)ion and/or molecule combinations on GAC using advanced digital image processing techniques. It was proved that the proposed approach could assess different adsorbed ions/molecules onto GACs in water purification systems. |
format | Online Article Text |
id | pubmed-7795858 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77958582021-01-10 X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons Puente Torres, Jeamichel Crespo Sariol, Harold Mariño Peacok, Thayset Yperman, Jan Adriaensens, Peter Carleer, Robert Brito Sauvanell, Ángel Materials (Basel) Article The X-ray absorption (XRA) method using digital image processing techniques is a reliable technique to determine the exhaustion degree of granular activated carbons (GACs). Using an innovative digital image processing technique, the identification of individual adsorbed molecules or ions in a GAC was possible. Adsorption isotherm models (Langmuir and Freundlich) were used to simulate the adsorption equilibrium data of Methylene Blue (MB), nickel, cobalt and iodine. Freundlich equation was found to have the highest value of R(2) compared with Langmuir. The identification of distinctive patterns applying XRA for different adsorbed ions and molecules onto GAC was explored. It is demonstrated that unique XRA configurations for each adsorbed ion or molecule are found, as well as a proportional relationship between its incident energy (needed to achieve maximum photon attenuation) and the (effective) atomic number, the adsorbate mass and the molar or atomic mass of adsorbed molecule or ion. XRA method in combination with image histogram modifications was used to obtain a digital signature of adsorbed ions/molecules, giving distinct GSI values for each one in the used energy range. Probabilistic models prove that XRA results are within relationships between effective atomic number and photonic interaction probability, reinforcing the potentialities of XRA for monitoring (multi-)ion and/or molecule combinations on GAC using advanced digital image processing techniques. It was proved that the proposed approach could assess different adsorbed ions/molecules onto GACs in water purification systems. MDPI 2020-12-28 /pmc/articles/PMC7795858/ /pubmed/33379219 http://dx.doi.org/10.3390/ma14010091 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Puente Torres, Jeamichel Crespo Sariol, Harold Mariño Peacok, Thayset Yperman, Jan Adriaensens, Peter Carleer, Robert Brito Sauvanell, Ángel X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons |
title | X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons |
title_full | X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons |
title_fullStr | X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons |
title_full_unstemmed | X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons |
title_short | X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons |
title_sort | x-ray absorption (xra): a new technique for the characterization of granular activated carbons |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795858/ https://www.ncbi.nlm.nih.gov/pubmed/33379219 http://dx.doi.org/10.3390/ma14010091 |
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