relation: https://khub.utp.edu.my/scholars/12745/
title: Artificial neural network approach for co-pyrolysis of Chlorella vulgaris and peanut shell binary mixtures using microalgae ash catalyst
creator: Bong, J.T.
creator: Loy, A.C.M.
creator: Chin, B.L.F.
creator: Lam, M.K.
creator: Tang, D.K.H.
creator: Lim, H.Y.
creator: Chai, Y.H.
creator: Yusup, S.
description: 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 (Ea) from the experimental which aligned with the ANN predicted results. The finding also shows that the activation energy (Ea) 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). © 2020 Elsevier Ltd
publisher: Elsevier Ltd
date: 2020
type: Article
type: PeerReviewed
identifier:   Bong, J.T. and Loy, A.C.M. and Chin, B.L.F. and Lam, M.K. and Tang, D.K.H. and Lim, H.Y. and Chai, Y.H. and Yusup, S.  (2020) Artificial neural network approach for co-pyrolysis of Chlorella vulgaris and peanut shell binary mixtures using microalgae ash catalyst.  Energy, 207.   ISSN 03605442     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087697379&doi=10.1016%2fj.energy.2020.118289&partnerID=40&md5=fcf1b892dbc7e22e8ad7748a6fa11ca0
relation: 10.1016/j.energy.2020.118289
identifier: 10.1016/j.energy.2020.118289