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Reliability Analysis of HHV Prediction Models for Organic Materials Using Bond Dissociation Energies
The purpose of this study is to analyze the reliability of predictive models for higher heating values related to organic materials. A theoretical model was developed, which utilizes bond dissociation energies (BDEs) to establish correlations between elemental composition and calorific values. Our a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575004/ https://www.ncbi.nlm.nih.gov/pubmed/37835911 http://dx.doi.org/10.3390/polym15193862 |
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author | Tao, Junjun Pan, Longwei Yao, Jiajie Liu, Longfei Chen, Qiang |
author_facet | Tao, Junjun Pan, Longwei Yao, Jiajie Liu, Longfei Chen, Qiang |
author_sort | Tao, Junjun |
collection | PubMed |
description | The purpose of this study is to analyze the reliability of predictive models for higher heating values related to organic materials. A theoretical model was developed, which utilizes bond dissociation energies (BDEs) to establish correlations between elemental composition and calorific values. Our analysis indicates that the energy contribution of one mole of hydrogen atoms is approximately equal to −144.4 kJ mol(−1). Further investigation reveals significant variations in the bond dissociation energies of carbon atoms within organic compounds, resulting in a range of energy outputs from −414.30 to −275.34 kJ mol(−1) per mole of carbon atoms. The presence of oxygen atoms in organic compounds has a negative impact on the magnitude of combustion heat, with values ranging from 131.1 to 207.17 kJ mol(−1). The combustion mechanism imposes certain constraints, leading to the equation HHV(g) = −31.34·[C] − 144.44·[H] + 10.57·[O] for organic compounds. Based on the parameter sensitivity analysis, the coefficient associated with carbon mass fraction exhibits a significantly greater impact on result prediction accuracy, demonstrating a sensitivity value of 92.65%. The results of further analysis indicate that empirical correlations involving the mass fractions of the elements N and S in lignocellulosic materials may be prone to over-fitting, with sensitivity indices of 1.59% and 0.016%, respectively. |
format | Online Article Text |
id | pubmed-10575004 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105750042023-10-14 Reliability Analysis of HHV Prediction Models for Organic Materials Using Bond Dissociation Energies Tao, Junjun Pan, Longwei Yao, Jiajie Liu, Longfei Chen, Qiang Polymers (Basel) Article The purpose of this study is to analyze the reliability of predictive models for higher heating values related to organic materials. A theoretical model was developed, which utilizes bond dissociation energies (BDEs) to establish correlations between elemental composition and calorific values. Our analysis indicates that the energy contribution of one mole of hydrogen atoms is approximately equal to −144.4 kJ mol(−1). Further investigation reveals significant variations in the bond dissociation energies of carbon atoms within organic compounds, resulting in a range of energy outputs from −414.30 to −275.34 kJ mol(−1) per mole of carbon atoms. The presence of oxygen atoms in organic compounds has a negative impact on the magnitude of combustion heat, with values ranging from 131.1 to 207.17 kJ mol(−1). The combustion mechanism imposes certain constraints, leading to the equation HHV(g) = −31.34·[C] − 144.44·[H] + 10.57·[O] for organic compounds. Based on the parameter sensitivity analysis, the coefficient associated with carbon mass fraction exhibits a significantly greater impact on result prediction accuracy, demonstrating a sensitivity value of 92.65%. The results of further analysis indicate that empirical correlations involving the mass fractions of the elements N and S in lignocellulosic materials may be prone to over-fitting, with sensitivity indices of 1.59% and 0.016%, respectively. MDPI 2023-09-22 /pmc/articles/PMC10575004/ /pubmed/37835911 http://dx.doi.org/10.3390/polym15193862 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tao, Junjun Pan, Longwei Yao, Jiajie Liu, Longfei Chen, Qiang Reliability Analysis of HHV Prediction Models for Organic Materials Using Bond Dissociation Energies |
title | Reliability Analysis of HHV Prediction Models for Organic Materials Using Bond Dissociation Energies |
title_full | Reliability Analysis of HHV Prediction Models for Organic Materials Using Bond Dissociation Energies |
title_fullStr | Reliability Analysis of HHV Prediction Models for Organic Materials Using Bond Dissociation Energies |
title_full_unstemmed | Reliability Analysis of HHV Prediction Models for Organic Materials Using Bond Dissociation Energies |
title_short | Reliability Analysis of HHV Prediction Models for Organic Materials Using Bond Dissociation Energies |
title_sort | reliability analysis of hhv prediction models for organic materials using bond dissociation energies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575004/ https://www.ncbi.nlm.nih.gov/pubmed/37835911 http://dx.doi.org/10.3390/polym15193862 |
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