TY - JOUR VL - 207 JF - Energy A1 - Bong, J.T. A1 - Loy, A.C.M. A1 - Chin, B.L.F. A1 - Lam, M.K. A1 - Tang, D.K.H. A1 - Lim, H.Y. A1 - Chai, Y.H. A1 - Yusup, S. UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087697379&doi=10.1016%2fj.energy.2020.118289&partnerID=40&md5=fcf1b892dbc7e22e8ad7748a6fa11ca0 PB - Elsevier Ltd SN - 03605442 Y1 - 2020/// TI - Artificial neural network approach for co-pyrolysis of Chlorella vulgaris and peanut shell binary mixtures using microalgae ash catalyst ID - scholars12745 KW - Activation energy; Algae; Catalysts; Heating rate; Kinetics; Microorganisms; Neural networks; Oilseeds; Polymer blends; Pyrolysis KW - Activation energies (Ea); Artificial neural network approach; Catalytic pyrolysis; Chlorella vulgaris; Degradation behaviours; Flynn-Wall-Ozawa; Kinetic and thermodynamic parameters; Pyrolysis process KW - Binary mixtures KW - activation energy; artificial neural network; ash; catalyst; crop residue; green alga; heating; microalga; pyrolysis; reaction kinetics; thermodynamics KW - Arachis hypogaea; Chlorella vulgaris N2 - 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 N1 - cited By 64 AV - none ER -