A modified DAEM: To study the bioenergy potential of invasive Staghorn Sumac through pyrolysis, ANN, TGA, kinetic modeling, FTIR and GC–MS analysis. (1st October 2020)
- Record Type:
- Journal Article
- Title:
- A modified DAEM: To study the bioenergy potential of invasive Staghorn Sumac through pyrolysis, ANN, TGA, kinetic modeling, FTIR and GC–MS analysis. (1st October 2020)
- Main Title:
- A modified DAEM: To study the bioenergy potential of invasive Staghorn Sumac through pyrolysis, ANN, TGA, kinetic modeling, FTIR and GC–MS analysis
- Authors:
- Sajjad Ahmad, Muhammad
Liu, Hui
Alhumade, Hesham
Hussain Tahir, Muddasar
Çakman, Gülce
Yıldız, Ağah
Ceylan, Selim
Elkamel, Ali
Shen, Boxiong - Abstract:
- Graphical abstract: Highlights: Bioenergy potential of Staghorn Sumac was explored using kinetics, FTIR and GCMS. Experimental and Predicted results were compared with DAEM model. Artificial Neural Network was used to validate the results obtained from DAEM. FTIR and GCMS results confirmed the bioenergy potential of invasive Staghorn Sumac. 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 bioenergyGraphical abstract: Highlights: Bioenergy potential of Staghorn Sumac was explored using kinetics, FTIR and GCMS. Experimental and Predicted results were compared with DAEM model. Artificial Neural Network was used to validate the results obtained from DAEM. FTIR and GCMS results confirmed the bioenergy potential of invasive Staghorn Sumac. 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. … (more)
- Is Part Of:
- Energy conversion and management. Volume 221(2020)
- Journal:
- Energy conversion and management
- Issue:
- Volume 221(2020)
- Issue Display:
- Volume 221, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 221
- Issue:
- 2020
- Issue Sort Value:
- 2020-0221-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10-01
- Subjects:
- Pyrolysis -- Thermodynamics parameters -- Bioenergy -- Bio-oil -- Artificial Neural Network -- Gas Chromatography–Mass Spectrometry
Direct energy conversion -- Periodicals
Energy storage -- Periodicals
Energy transfer -- Periodicals
Énergie -- Conversion directe -- Périodiques
Direct energy conversion
Periodicals
621.3105 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01968904 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.enconman.2020.113173 ↗
- Languages:
- English
- ISSNs:
- 0196-8904
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.547000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14266.xml