Synergistic Effects of Catalytic Co-Pyrolysis Chlorella vulgaris and Polyethylene Mixtures using Artificial Neuron Network: Thermodynamic and Empirical Kinetic Analyses - Yap, Tshun Li; Loy, Adrian Chun Minh; Chin, Bridgid; Lim, Juin Yau; Alhamzi, Hatem; Chai, Yee Ho; Yiin, Chung Loong; Cheah, Kin Wai; Wee, Melvin Xin Jie; Lam, Man Kee; Jawad, Zeinab Abbas; Yusup, Suzana; et al. (Elsevier, 2022)
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.