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المؤلفYap, Tshun Li
المؤلفLoy, Adrian Chun Minh
المؤلفChin, Bridgid Lai Fui
المؤلفLim, Juin Yau
المؤلفAlhamzi, Hatem
المؤلفChai, Yee Ho
المؤلفYiin, Chung Loong
المؤلفCheah, Kin Wai
المؤلفWee, Melvin Xin Jie
المؤلفLam, Man Kee
المؤلفJawad, Zeinab Abbas
المؤلفYusup, Suzana
المؤلفLock, Serene Sow Mun
تاريخ الإتاحة2024-04-22T04:57:06Z
تاريخ النشر2022
اسم المنشورJournal of Environmental Chemical Engineering
المصدرScopus
الرقم المعياري الدولي للكتاب22133437
معرّف المصادر الموحدhttp://dx.doi.org/10.1016/j.jece.2022.107391
معرّف المصادر الموحدhttp://hdl.handle.net/10576/53993
الملخصThe 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
راعي المشروعThe authors would like to express their sincere gratitude to the Curtin University Malaysia and the Centre of Biofuel and Biochemical (CBBR) of Universiti Teknologi PETRONAS (UTP) for the technical support. Also, Loy A. C. M. would like to thank the Australian Government , Australia for providing financial (Research Training Program) support to this project.
اللغةen
الناشرElsevier
الموضوعArtificial neural network
Catalytic pyrolysis
Empirical modelling
Genetic algorithm
Kinetic analysis
Microalgae Chlorella vulgaris
العنوانSynergistic effects of catalytic co-pyrolysis Chlorella vulgaris and polyethylene mixtures using artificial neuron network: Thermodynamic and empirical kinetic analyses
النوعArticle
رقم العدد3
رقم المجلد10
dc.accessType Abstract Only


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