Iranmanesh, Reza ; Pourahmad, Afham ; Faress, Fardad ; Tutunchian, Sevil ; Ariana, Mohammad Amin ; Sadeqi, Hamed ; Hosseini, Saleh ; Alobaid, Falah ; Aghel, Babak (2022)
Introducing a Linear Empirical Correlation for Predicting the Mass Heat Capacity of Biomaterials.
In: Molecules, 27 (19)
doi: 10.3390/molecules27196540
Artikel, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
This study correlated biomass heat capacity (Cp) with the chemistry (sulfur and ash content), crystallinity index, and temperature of various samples. A five-parameter linear correlation predicted 576 biomass Cp samples from four different origins with the absolute average relative deviation (AARD%) of ~1.1%. The proportional reduction in error (REE) approved that ash and sulfur contents only enlarge the correlation and have little effect on the accuracy. Furthermore, the REE showed that the temperature effect on biomass heat capacity was stronger than on the crystallinity index. Consequently, a new three-parameter correlation utilizing crystallinity index and temperature was developed. This model was more straightforward than the five-parameter correlation and provided better predictions (AARD = 0.98%). The proposed three-parameter correlation predicted the heat capacity of four different biomass classes with residual errors between −0.02 to 0.02 J/g∙K. The literature related biomass Cp to temperature using quadratic and linear correlations, and ignored the effect of the chemistry of the samples. These quadratic and linear correlations predicted the biomass Cp of the available database with an AARD of 39.19% and 1.29%, respectively. Our proposed model was the first work incorporating sample chemistry in biomass Cp estimation.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Iranmanesh, Reza ; Pourahmad, Afham ; Faress, Fardad ; Tutunchian, Sevil ; Ariana, Mohammad Amin ; Sadeqi, Hamed ; Hosseini, Saleh ; Alobaid, Falah ; Aghel, Babak |
| Art des Eintrags: | Bibliographie |
| Titel: | Introducing a Linear Empirical Correlation for Predicting the Mass Heat Capacity of Biomaterials |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Ort: | Darmstadt |
| Verlag: | MDPI |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Molecules |
| Jahrgang/Volume einer Zeitschrift: | 27 |
| (Heft-)Nummer: | 19 |
| Kollation: | 12 Seiten |
| DOI: | 10.3390/molecules27196540 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | This study correlated biomass heat capacity (Cp) with the chemistry (sulfur and ash content), crystallinity index, and temperature of various samples. A five-parameter linear correlation predicted 576 biomass Cp samples from four different origins with the absolute average relative deviation (AARD%) of ~1.1%. The proportional reduction in error (REE) approved that ash and sulfur contents only enlarge the correlation and have little effect on the accuracy. Furthermore, the REE showed that the temperature effect on biomass heat capacity was stronger than on the crystallinity index. Consequently, a new three-parameter correlation utilizing crystallinity index and temperature was developed. This model was more straightforward than the five-parameter correlation and provided better predictions (AARD = 0.98%). The proposed three-parameter correlation predicted the heat capacity of four different biomass classes with residual errors between −0.02 to 0.02 J/g∙K. The literature related biomass Cp to temperature using quadratic and linear correlations, and ignored the effect of the chemistry of the samples. These quadratic and linear correlations predicted the biomass Cp of the available database with an AARD of 39.19% and 1.29%, respectively. Our proposed model was the first work incorporating sample chemistry in biomass Cp estimation. |
| Freie Schlagworte: | biomass sample, heat capacity, empirical correlation, biomass crystallinity, feature reduction |
| Zusätzliche Informationen: | This article belongs to the Special Issue Sustainable Development and Application of Renewable Chemicals from Biomass and Waste |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 500 Naturwissenschaften und Mathematik > 540 Chemie 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Energiesysteme und Energietechnik (EST) |
| Hinterlegungsdatum: | 02 Aug 2024 12:44 |
| Letzte Änderung: | 02 Aug 2024 12:44 |
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Introducing a Linear Empirical Correlation for Predicting the Mass Heat Capacity of Biomaterials. (deposited 07 Nov 2022 12:29)
- Introducing a Linear Empirical Correlation for Predicting the Mass Heat Capacity of Biomaterials. (deposited 02 Aug 2024 12:44) [Gegenwärtig angezeigt]
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