Artificial neural network approach for co-pyrolysis of Chlorella vulgaris and peanut shell binary mixtures using microalgae ash catalyst. (15th September 2020)
- Record Type:
- Journal Article
- Title:
- Artificial neural network approach for co-pyrolysis of Chlorella vulgaris and peanut shell binary mixtures using microalgae ash catalyst. (15th September 2020)
- Main Title:
- Artificial neural network approach for co-pyrolysis of Chlorella vulgaris and peanut shell binary mixtures using microalgae ash catalyst
- Authors:
- Bong, Jang Tyng
Loy, Adrian Chun Minh
Chin, Bridgid Lai Fui
Lam, Man Kee
Tang, Daniel Kuok Ho
Lim, Huei Yeong
Chai, Yee Ho
Yusup, Suzana - Abstract:
- Abstract: The catalytic pyrolysis of pure microalgae (M), peanut shell wastes (PS) and their binary mixtures were analysed by introducing the microalgae ash (MA) as a catalyst. The pyrolysis processes were conducted at different heating rates from 10 K/min-100 K/min to observe their thermal degradation behaviour. Additionally, Artificial Neural Network (ANN) was applied by feeding the heating rates and temperatures to predict the weight loss of the samples. The kinetic and thermodynamic parameters were also determined through three different iso-conversional kinetic models: Friedman (FR), Kissinger-Akahira-Sunose (KAS) and Flynn-Wall-Ozawa (FWO). Based on the kinetic results, FWO model achieved the lowest deviation between the activation energies ( E a ) from the experimental which aligned with the ANN predicted results. The finding also shows that the activation energy ( E a ) of the catalytic pyrolysis of binary mixtures was lower than the pure M and PS (Experimental: 142.56 kJ/mol; ANN forecast: 131.37 kJ/mol). Graphical abstract: Image 1 Highlights: The synergistic effect of co-pyrolysis of M and PS were studied using TGA. ANN modelling was applied to predict the weight loss of samples. LT transfer functions produce similar results as the experimental TG curves. The syngas composition has increased after the addition of MA as a catalyst. The E a of M/MA/PS mixture was reduced to 142.56 kJ/mol with MA as a catalyst.
- Is Part Of:
- Energy. Volume 207(2020)
- Journal:
- Energy
- Issue:
- Volume 207(2020)
- Issue Display:
- Volume 207, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 207
- Issue:
- 2020
- Issue Sort Value:
- 2020-0207-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09-15
- Subjects:
- Catalytic pyrolysis -- Microalgae -- Thermodynamic analysis -- Kinetic analysis -- Artificial neural network
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2020.118289 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13734.xml