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Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process
In this work, an original mathematical model for metals leaching from electronic waste in a dark fermentation process is proposed. The kinetic model consists of a system of non-linear ordinary differential equations, accounting for the main biological, chemical, and physical processes occurring in t...
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/PMC8917181/ https://www.ncbi.nlm.nih.gov/pubmed/35277534 http://dx.doi.org/10.1038/s41598-022-08106-2 |
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author | Russo, Fabiana Luongo, Vincenzo Mattei, Maria Rosaria Frunzo, Luigi |
author_facet | Russo, Fabiana Luongo, Vincenzo Mattei, Maria Rosaria Frunzo, Luigi |
author_sort | Russo, Fabiana |
collection | PubMed |
description | In this work, an original mathematical model for metals leaching from electronic waste in a dark fermentation process is proposed. The kinetic model consists of a system of non-linear ordinary differential equations, accounting for the main biological, chemical, and physical processes occurring in the fermentation of soluble biodegradable substrates and in the dissolution process of metals. Ad-hoc experimental activities were carried out for model calibration purposes, and all experimental data were derived from specific lab-scale tests. The calibration was achieved by varying kinetic and stoichiometric parameters to match the simulation results to experimental data. Cumulative hydrogen production, glucose, organic acids, and leached metal concentrations were obtained from analytical procedures and used for the calibration. The results confirmed the high accuracy of the model in describing biohydrogen production, organic acids accumulation, and metals leaching during the biological degradation process. Thus, the mathematical model represents a useful and reliable tool for the design of strategies for valuable metals recovery from waste or mineral materials. Moreover, further numerical simulations were carried out to analyze the interactions between the fermentation and the leaching processes and to maximize the efficiency of metals recovery due to the fermentation by-products. |
format | Online Article Text |
id | pubmed-8917181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89171812022-03-14 Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process Russo, Fabiana Luongo, Vincenzo Mattei, Maria Rosaria Frunzo, Luigi Sci Rep Article In this work, an original mathematical model for metals leaching from electronic waste in a dark fermentation process is proposed. The kinetic model consists of a system of non-linear ordinary differential equations, accounting for the main biological, chemical, and physical processes occurring in the fermentation of soluble biodegradable substrates and in the dissolution process of metals. Ad-hoc experimental activities were carried out for model calibration purposes, and all experimental data were derived from specific lab-scale tests. The calibration was achieved by varying kinetic and stoichiometric parameters to match the simulation results to experimental data. Cumulative hydrogen production, glucose, organic acids, and leached metal concentrations were obtained from analytical procedures and used for the calibration. The results confirmed the high accuracy of the model in describing biohydrogen production, organic acids accumulation, and metals leaching during the biological degradation process. Thus, the mathematical model represents a useful and reliable tool for the design of strategies for valuable metals recovery from waste or mineral materials. Moreover, further numerical simulations were carried out to analyze the interactions between the fermentation and the leaching processes and to maximize the efficiency of metals recovery due to the fermentation by-products. Nature Publishing Group UK 2022-03-11 /pmc/articles/PMC8917181/ /pubmed/35277534 http://dx.doi.org/10.1038/s41598-022-08106-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Russo, Fabiana Luongo, Vincenzo Mattei, Maria Rosaria Frunzo, Luigi Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process |
title | Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process |
title_full | Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process |
title_fullStr | Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process |
title_full_unstemmed | Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process |
title_short | Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process |
title_sort | mathematical modeling of metal recovery from e-waste using a dark-fermentation-leaching process |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917181/ https://www.ncbi.nlm.nih.gov/pubmed/35277534 http://dx.doi.org/10.1038/s41598-022-08106-2 |
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