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Comprehensive investigation of almond shells pyrolysis using advance predictive models
National University of Sciences & Technology, Pakistan.
NFC Institute of Engineering & Technology, Pakistan.
National University of Sciences & Technology, Pakistan.
National University of Sciences & Technology, Pakistan.
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2024 (English)In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 227, article id 120568Article in journal (Refereed) Published
Abstract [en]

This research focused on comprehensive characterization and assessment of almond shells pyrolysis for bioenergy potential through thermogravimetric analysis from ambient temperature to 900 °C at different heating rates of 10, 15, and 20 °C/min in inert environment. Iso-conversional model-free methods like Friedman, Ozawa-Flynn-Wall (OFW), and Kissinger-Akahira-Sunose (KAS) were used for kinetic analysis. Average activation energies (Ea) evaluated using Friedman, OFW, and KAS methods were 198.45 kJ mol−1, 204.43 kJ mol−1, and 204.97 kJ mol−1, respectively. The evaluation of thermodynamic parameters, including ΔH‡, ΔG‡, and ΔS‡, was also assessed. The average values of ΔH‡, ΔG‡, and ΔS‡, were found to be 199.4 kJ mol−1, 172.17 kJ mol−1 and 42.60 kJ mol−1 respectively. The reaction mechanism was obtained from combined kinetics. A high R2 value of 0.9933 demonstrates strong agreement between the combined kinetic analysis results and the experimental data. The distribution activation energy model was assessed employing four pseudo elements identified as PC1, PC2, PC3, and PC4. Artificial Neural Network (ANN) and Boosting regression trees (BRT) were used for the prediction of Ea of almond shells pyrolysis. The detailed understanding of thermokinetics and creating customized predictive and innovative modelling techniques like ANN and BRT sets a new benchmark for developing customized models for thermochemical conversion of varieties of almond shells. 

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 227, article id 120568
Keywords [en]
Almond shells, Pyrokinetics, DAEM, ANN, BRT
National Category
Energy Engineering
Research subject
Chemical Engineering
Identifiers
URN: urn:nbn:se:kau:diva-100102DOI: 10.1016/j.renene.2024.120568ISI: 001237170500001Scopus ID: 2-s2.0-85191658947OAI: oai:DiVA.org:kau-100102DiVA, id: diva2:1869810
Available from: 2024-06-13 Created: 2024-06-13 Last updated: 2024-06-25Bibliographically approved

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Naqvi, Salman Raza

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