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Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization
Nowadays, wearing a 3-layered face mask (3LFM) to protect against coronavirus illness (COVID-19) has become commonplace, resulting in massive, hazardous solid waste. Since most of them are infected with viruses, a secure way of disposal is necessary to prevent further virus spread. Pyrolysis treatme...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taiwan Institute of Chemical Engineers. Published by Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518071/ https://www.ncbi.nlm.nih.gov/pubmed/36193262 http://dx.doi.org/10.1016/j.jtice.2022.104538 |
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author | Nawaz, Ahmad Kumar, Pradeep |
author_facet | Nawaz, Ahmad Kumar, Pradeep |
author_sort | Nawaz, Ahmad |
collection | PubMed |
description | Nowadays, wearing a 3-layered face mask (3LFM) to protect against coronavirus illness (COVID-19) has become commonplace, resulting in massive, hazardous solid waste. Since most of them are infected with viruses, a secure way of disposal is necessary to prevent further virus spread. Pyrolysis treatment has recently developed as an effective method for disposing of such hazardous waste and consequently converting them into energy products. In this regard, the goal of the present study is to physicochemically characterize the 3LFM followed by pyrolysis in a TGA to evaluate the pyrolysis performance, kinetic, and thermodynamic parameters and in a semi-batch reactor to characterize the volatile product. Furthermore, an artificial neural network (ANN) was used to forecast thermal deterioration data. The results demonstrated a strong correlation between real and anticipated values. The study proved the relevance of the ANN model and the applicability of pyrolysis for disposing of 3LFM while simultaneously producing energy products. |
format | Online Article Text |
id | pubmed-9518071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95180712022-09-29 Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization Nawaz, Ahmad Kumar, Pradeep J Taiwan Inst Chem Eng Article Nowadays, wearing a 3-layered face mask (3LFM) to protect against coronavirus illness (COVID-19) has become commonplace, resulting in massive, hazardous solid waste. Since most of them are infected with viruses, a secure way of disposal is necessary to prevent further virus spread. Pyrolysis treatment has recently developed as an effective method for disposing of such hazardous waste and consequently converting them into energy products. In this regard, the goal of the present study is to physicochemically characterize the 3LFM followed by pyrolysis in a TGA to evaluate the pyrolysis performance, kinetic, and thermodynamic parameters and in a semi-batch reactor to characterize the volatile product. Furthermore, an artificial neural network (ANN) was used to forecast thermal deterioration data. The results demonstrated a strong correlation between real and anticipated values. The study proved the relevance of the ANN model and the applicability of pyrolysis for disposing of 3LFM while simultaneously producing energy products. Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. 2022-10 2022-09-28 /pmc/articles/PMC9518071/ /pubmed/36193262 http://dx.doi.org/10.1016/j.jtice.2022.104538 Text en © 2022 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Nawaz, Ahmad Kumar, Pradeep Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization |
title | Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization |
title_full | Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization |
title_fullStr | Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization |
title_full_unstemmed | Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization |
title_short | Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization |
title_sort | thermal degradation of hazardous 3-layered covid-19 face mask through pyrolysis: kinetic, thermodynamic, prediction modelling using ann and volatile product characterization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518071/ https://www.ncbi.nlm.nih.gov/pubmed/36193262 http://dx.doi.org/10.1016/j.jtice.2022.104538 |
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