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dc.contributor.authorYap, Tshun Li
dc.contributor.authorLoy, Adrian Chun Minh
dc.contributor.authorChin, Bridgid
dc.contributor.authorLim, Juin Yau
dc.contributor.authorAlhamzi, Hatem
dc.contributor.authorChai, Yee Ho
dc.contributor.authorYiin, Chung Loong
dc.contributor.authorCheah, Kin Wai
dc.contributor.authorWee, Melvin Xin Jie
dc.contributor.authorLam, Man Kee
dc.contributor.authorJawad, Zeinab Abbas
dc.contributor.authorYusup, Suzana
dc.contributor.authorSerene Sow Mun, Lock
dc.date.accessioned2022-02-16T02:41:46Z
dc.date.available2022-02-16T02:41:46Z
dc.date.issued2022
dc.identifier.citationYap, T.L. and Loy, A.C.M. and Chin, B.L.F. and Lim, J.Y. and Alhamzi, H. and Chai, Y.H. and Yiin, C.L. et al. 2022. Synergistic Effects of Catalytic Co-Pyrolysis Chlorella vulgaris and Polyethylene Mixtures using Artificial Neuron Network: Thermodynamic and Empirical Kinetic Analyses. Journal of Environmental Chemical Engineering. 10 (3): Article No. 107391.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/87766
dc.identifier.doi10.1016/j.jece.2022.107391
dc.description.abstract

The catalytic pyrolysis of Chlorella vulgaris, high-density polyethylene (Pure HDPE) and, their binary mixtures were conducted to analyse the kinetic and thermodynamic performances from 10 to 100 K/min. The kinetic parameters were computed by substituting the experimental and ANN predicted data into these iso-conversional equations and plotting linear plots. Among all the iso-conversional models, Flynn-Wall-Ozawa (FWO) model gave the best prediction for kinetic parameters with the lowest deviation error (2.28–12.76%). The bifunctional HZSM-5/LS catalysts were found out to be the best catalysts among HZSM-5 zeolite, natural limestone (LS), and bifunctional HZSM-5/LS catalyst in co-pyrolysis of binary mixture of Chlorella vulgaris and HDPE, in which the Ea of the whole system was reduced from range 144.93–225.84 kJ/mol (without catalysts) to 75.37–76.90 kJ/mol. With the aid of artificial neuron network and genetic algorithm, an empirical model with a mean absolute percentage error (MAPE) of 51.59% was developed for tri-solid state degradation system. The developed empirical model is comparable to the thermogravimetry analysis (TGA) experimental values alongside the other empirical model proposed in literature.

dc.publisherElsevier
dc.titleSynergistic Effects of Catalytic Co-Pyrolysis Chlorella vulgaris and Polyethylene Mixtures using Artificial Neuron Network: Thermodynamic and Empirical Kinetic Analyses
dc.typeJournal Article
dcterms.source.issn2213-2929
dcterms.source.titleJournal of Environmental Chemical Engineering
dc.date.updated2022-02-16T02:41:35Z
curtin.departmentCurtin International
curtin.accessStatusFulltext not available
curtin.facultyCurtin International
curtin.contributor.orcidChin, Bridgid [0000-0002-6544-664X]
curtin.contributor.scopusauthoridChin, Bridgid [56052383600]


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