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Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases

Sensitivity analyses of rate constants for chemical kinetics of the pyrolysis reaction are essential for the efficient valorization of plastic waste into combustible liquids and gases. Finding the role of individual rate constants can provide important information on the process conditions, quality,...

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Autores principales: Irfan, Muhammad, Un Nabi, Rao Adeel, Hussain, Hammad, Naz, Muhammad Yasin, Shukrullah, Shazia, Khawaja, Hassan Abbas, Rahman, Saifur, Farid, Muhammad Usman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10192758/
https://www.ncbi.nlm.nih.gov/pubmed/37215830
http://dx.doi.org/10.1016/j.heliyon.2023.e16049
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author Irfan, Muhammad
Un Nabi, Rao Adeel
Hussain, Hammad
Naz, Muhammad Yasin
Shukrullah, Shazia
Khawaja, Hassan Abbas
Rahman, Saifur
Farid, Muhammad Usman
author_facet Irfan, Muhammad
Un Nabi, Rao Adeel
Hussain, Hammad
Naz, Muhammad Yasin
Shukrullah, Shazia
Khawaja, Hassan Abbas
Rahman, Saifur
Farid, Muhammad Usman
author_sort Irfan, Muhammad
collection PubMed
description Sensitivity analyses of rate constants for chemical kinetics of the pyrolysis reaction are essential for the efficient valorization of plastic waste into combustible liquids and gases. Finding the role of individual rate constants can provide important information on the process conditions, quality, and quantity of the pyrolysis products. The reaction temperature and time can also be reduced through these analyses. For sensitivity analysis, one possible approach is to estimate the kinetic parameters using MLRM (multiple linear regression model) in SPSS. To date, no research reports on this research gap are documented in the published literature. In this study, MLRM is applied to kinetic rate constants, which slightly differ from experimental data. The experimental and statistically predicted rate constants varied up to 200% from their original values to perform sensitivity analysis using MATLAB software. The product yield was examined after 60 min of thermal pyrolysis at a fixed temperature of 420 °C. The predicted rate constant “k(8)” with a slight difference of 0.02 and 0.04 from the experiment revealed 85% oil yield and 40% light wax after 60 min of operation. The heavy wax was missing from the products under these conditions. This rate constant can be utilized to maximize the commercial-scale extraction of liquids and light waxes from thermal pyrolysis of plastics.
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spelling pubmed-101927582023-05-19 Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases Irfan, Muhammad Un Nabi, Rao Adeel Hussain, Hammad Naz, Muhammad Yasin Shukrullah, Shazia Khawaja, Hassan Abbas Rahman, Saifur Farid, Muhammad Usman Heliyon Research Article Sensitivity analyses of rate constants for chemical kinetics of the pyrolysis reaction are essential for the efficient valorization of plastic waste into combustible liquids and gases. Finding the role of individual rate constants can provide important information on the process conditions, quality, and quantity of the pyrolysis products. The reaction temperature and time can also be reduced through these analyses. For sensitivity analysis, one possible approach is to estimate the kinetic parameters using MLRM (multiple linear regression model) in SPSS. To date, no research reports on this research gap are documented in the published literature. In this study, MLRM is applied to kinetic rate constants, which slightly differ from experimental data. The experimental and statistically predicted rate constants varied up to 200% from their original values to perform sensitivity analysis using MATLAB software. The product yield was examined after 60 min of thermal pyrolysis at a fixed temperature of 420 °C. The predicted rate constant “k(8)” with a slight difference of 0.02 and 0.04 from the experiment revealed 85% oil yield and 40% light wax after 60 min of operation. The heavy wax was missing from the products under these conditions. This rate constant can be utilized to maximize the commercial-scale extraction of liquids and light waxes from thermal pyrolysis of plastics. Elsevier 2023-05-06 /pmc/articles/PMC10192758/ /pubmed/37215830 http://dx.doi.org/10.1016/j.heliyon.2023.e16049 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Irfan, Muhammad
Un Nabi, Rao Adeel
Hussain, Hammad
Naz, Muhammad Yasin
Shukrullah, Shazia
Khawaja, Hassan Abbas
Rahman, Saifur
Farid, Muhammad Usman
Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases
title Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases
title_full Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases
title_fullStr Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases
title_full_unstemmed Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases
title_short Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases
title_sort statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10192758/
https://www.ncbi.nlm.nih.gov/pubmed/37215830
http://dx.doi.org/10.1016/j.heliyon.2023.e16049
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