Abstract
Biomass is deemed to be an important contributor to satisfy our energy, chemicals and material requirements throughout the world. The present study aimed to study the bioenergy potential of Staghorn Sumac (SS) through modified distributed activation energy model (DAEM), kinetic models, thermogravimetric analyzer, elemental analyzer, Fourier transform infrared spectrometry (FTIR) and gas chromatography-mass spectrometry (GC–MS). Pyrolysis experiments were carried out at the different heating rates of 10, 20, 30 and 40 °C min−1 to study kinetics. The average activation energy values achieved through DAEM, KAS, FWO and Starink models were 160, 167, 169, and 168 kJ mol−1, respectively. Additionally, an Artificial Neural Network (ANN) model was equated with modified DAEM. Moreover, The composition of evolved gas compound measured by a gas chromatography coupled with mass spectroscopy showed that bio-oil mainly consisted of 82.33% acid, 6.37% aldehyde and ketone, 4.96% amid, 2.76% ester, 2.07% aromatic and alcohols, and 1.52% other groups. This study has revealed the remarkable potentials of Staghorn Sumac for clean bioenergy production.
Original language | English |
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Article number | 113173 |
Journal | Energy Conversion and Management |
Volume | 221 |
DOIs | |
State | Published - 1 Oct 2020 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 Elsevier Ltd
Keywords
- Artificial Neural Network
- Bio-oil
- Bioenergy
- Gas Chromatography–Mass Spectrometry
- Pyrolysis
- Thermodynamics parameters
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Nuclear Energy and Engineering
- Fuel Technology
- Energy Engineering and Power Technology