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Pyrolysis behavior of low value biomass (Sesbania bispinosa) to elucidate its bioenergy potential: Kinetic, thermodynamic and prediction modelling using artificial neural network

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  • Nawaz, Ahmad
  • Kumar, Pradeep

Abstract

Energy needs are dynamic, and the increasing demand for energy prompted the completion of this study to explore the thermal degradation characteristics of Sesbania bispinosa (SB) biomass in order to assess its pyrolytic performance for biofuel generation. The physicochemical analysis revealed lower moisture (6.30%), higher volatile (79.35%), and lower ash (3.95%). The results of the TG investigation indicated that the maximum devolatilization temperature range during the thermal deterioration of SB was 297–650 °C. The model-free approaches of Ozawa Flynn Wall (OFW), Kissinger Akahira Sunose (KAS), Tang (TG), Starink (SK), and Vyazovkin (VZK) were used to predict kinetic parameters. The average activation energy obtained was 181.37, 180.63, 180.91, 180.90, and 161.31 kJ/mol using the OFW, KAS, TG, SK, and VZK methods, respectively. The comprehensive pyrolysis index (CPI) showed a greater value at higher heating rates (50 °C/min), indicating the appropriateness of SB pyrolysis at higher heating rates. Further, artificial neural network (ANN) was employed for the prediction of thermal degradation data. Results revealed a strong correlation between actual and predicted values, which are much nearer to one. The investigation demonstrated the importance of ANN model and suitability of SB biomass as a potential feedstock for bioenergy production via pyrolysis.

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  • Nawaz, Ahmad & Kumar, Pradeep, 2022. "Pyrolysis behavior of low value biomass (Sesbania bispinosa) to elucidate its bioenergy potential: Kinetic, thermodynamic and prediction modelling using artificial neural network," Renewable Energy, Elsevier, vol. 200(C), pages 257-270.
  • Handle: RePEc:eee:renene:v:200:y:2022:i:c:p:257-270
    DOI: 10.1016/j.renene.2022.09.110
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    References listed on IDEAS

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    1. Sahoo, Abhisek & Saini, Komal & Negi, Shweta & Kumar, Jitendra & Pant, Kamal K. & Bhaskar, Thallada, 2022. "Inspecting the bioenergy potential of noxious Vachellia nilotica weed via pyrolysis: Thermo-kinetic study, neural network modeling and response surface optimization," Renewable Energy, Elsevier, vol. 185(C), pages 386-402.
    2. Nawaz, Ahmad & Kumar, Pradeep, 2022. "Elucidating the bioenergy potential of raw, hydrothermally carbonized and torrefied waste Arundo donax biomass in terms of physicochemical characterization, kinetic and thermodynamic parameters," Renewable Energy, Elsevier, vol. 187(C), pages 844-856.
    3. Sahoo, Abhisek & Kumar, Sachin & Mohanty, Kaustubha, 2021. "Kinetic and thermodynamic analysis of Putranjiva roxburghii (putranjiva) and Cassia fistula (amaltas) non-edible oilseeds using thermogravimetric analyzer," Renewable Energy, Elsevier, vol. 165(P1), pages 261-277.
    4. Yuan, Xinsong & He, Tao & Cao, Hongliang & Yuan, Qiaoxia, 2017. "Cattle manure pyrolysis process: Kinetic and thermodynamic analysis with isoconversional methods," Renewable Energy, Elsevier, vol. 107(C), pages 489-496.
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    1. Nishu, & Tang, Songbiao & Mei, Wenjie & Yang, Juntao & Wang, Zhongming & Yang, Gaixiu, 2024. "Effect of anaerobic digestion pretreatment on pyrolysis of distillers’ grain: Product distribution, kinetics and thermodynamics analysis," Renewable Energy, Elsevier, vol. 221(C).
    2. Ahmed, Gaffer & Kishore, Nanda, 2023. "Fuel phase extraction from pyrolytic liquid of Azadirachta indica biomass followed by subsequent characterization of pyrolysis products," Renewable Energy, Elsevier, vol. 219(P1).

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