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 Lai Fui; 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; Lock, Serene Sow Mun

doi:10.1016/j.jece.2022.107391

Cited by 36 publications

(4 citation statements)

References 24 publications

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“…They showed that 15 wt% bottom ash had higher effect on catalytic activity compared to 15 wt% fly ash. Yap et al (2022) [ 19 ] used two different catalysts (HZSM-5 zeolite and natural limestone (LS)) for copyrolysis of HDPE and Chlorella vulgaris mixture. They concluded that the combined HZSM-5/LS catalyst had the best effect in the copyrolysis of the HDPE and Chlorella vulgaris mixture, with the activation energy decreasing from 144.93–225.84 to 75.37–76.90 kJ/mol.…”

Section: Introductionmentioning

confidence: 99%

Catalytic Pyrolysis of PET Polymer Using Nonisothermal Thermogravimetric Analysis Data: Kinetics and Artificial Neural Networks Studies

Dubdub

Alhulaybi

2022

Polymers

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This paper presents the catalytic pyrolysis of a constant-composition mixture of zeolite β and polyethylene terephthalate (PET) polymer by thermogravimetric analysis (TGA) at different heating rates (2, 5, 10, and 20 K/min). The thermograms showed only one main reaction and shifted to higher temperatures with increasing heating rate. In addition, at constant heating rate, they moved to lower temperatures of pure PET pyrolysis when a catalyst was added. Four isoconversional models, namely, Kissinger–Akahira–Sunose (KAS), Friedman, Flynn–Wall–Qzawa (FWO), and Starink, were applied to obtain the activation energy (Ea). Values of Ea acquired by these models were very close to each other with average value of Ea = 154.0 kJ/mol, which was much lower than that for pure PET pyrolysis. The Coats–Redfern and Criado methods were employed to set the most convenient solid-state reaction mechanism. These methods revealed that the experimental data matched those obtained by different mechanisms depending on the heating rate. Values of Ea obtained by these two models were within the average values of 157 kJ/mol. An artificial neural network (ANN) was utilized to predict the remaining weight fraction using two input variables (temperature and heating rate). The results proved that ANN could predict the experimental value very efficiently (R2 > 0.999) even with new data.

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Section: Introductionmentioning

confidence: 99%

Catalytic Pyrolysis of PET Polymer Using Nonisothermal Thermogravimetric Analysis Data: Kinetics and Artificial Neural Networks Studies

Dubdub

Alhulaybi

2022

Polymers

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“…ANNs have been used for the prediction of biomass heating values, thermal behaviors, kinetics, and product distributions considering biomass feedstock properties and process operating variables. Studies for the prediction of gross heating value, − pyrolysis kinetic parameters, − and thermal degradation rate , were predicted using neural networks. A few studies pertaining to the prediction of pyrolytic yields with limited datasets are reported.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Models for the Prediction of Biomass Pyrolysis Products from Preliminary Analysis

Balsora,

Joshi

et al. 2023

Ind. Eng. Chem. Res.

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“…In addition, compared with non-catalytic pyrolysis, the appropriate catalyst could further reduce energy input and time consumption and improve the quality of products [10][11][12]. For example, the catalytic co-pyrolysis behavior of chlorella and polyethylene was investigated by a thermogravimetric analyzer [13]. The results showed that the activation energy decreased dramatically, from 144.93-225.84 kJ/mol (without catalyst) to 75.37-76.90 kJ/mol with the use of HZSM-5/LS catalysts.…”

Section: Introductionmentioning

confidence: 99%

Catalytic Pyrolysis of Hydrochar by Calcined Eggshells for Bioenergy Production: Improved Thermo-Kinetic Studies and Reduced Pollutant Emissions

Yang,

Chen,

Wang

et al. 2023

Catalysts

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Bioenergy production from hydrochar via catalytic thermal conversion is of increasing importance to easing the energy shortage. The catalytic pyrolysis characteristics of hydrochar derived from sawdust (HSD) with calcined eggshell (CES) were investigated by the thermogravimetric–Fourier transform infrared spectroscopy–mass spectrometry (TG-FTIR-MS) method. Kinetic and thermodynamic parameters were determined by two iso-conversional model-free methods, namely, Kissinger–Akahira–Sunose (KAS) and Flynn–Wall–Ozawa (FWO). The results demonstrated that HSD exhibited a high fuel quality, with elevated carbon content (54.03%) and an increased high calorific value (21.65 MJ Kg−1). CES significantly enhanced the pyrolysis behavior of HSD by promoting the secondary cracking of organic vapors under the synergistic effect of CaO and mineral elements. Compared to non-catalytic pyrolysis, the residual mass and average activation energy of HSD-CES decreased by 29.61% and 14.10%, respectively, and the gaseous products of H2 and CO from HSD-CES increased by 26.14% and 22.94%, respectively. Furthermore, the participation of CES effectively suppressed the emission of pollutants in the HSD pyrolysis process, with a 27.13% reduction in CH4, a 22.76% reduction in HCN, and a 20.28% reduction in NH3. This study provides valuable guidance on the potential use of hydrochar for renewable energy production.

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Synergistic effects of catalytic co-pyrolysis Chlorella vulgaris and polyethylene mixtures using artificial neuron network: Thermodynamic and empirical kinetic analyses

Cited by 36 publications

References 24 publications

Catalytic Pyrolysis of PET Polymer Using Nonisothermal Thermogravimetric Analysis Data: Kinetics and Artificial Neural Networks Studies

Catalytic Pyrolysis of PET Polymer Using Nonisothermal Thermogravimetric Analysis Data: Kinetics and Artificial Neural Networks Studies

Artificial Neural Network-Based Models for the Prediction of Biomass Pyrolysis Products from Preliminary Analysis

Catalytic Pyrolysis of Hydrochar by Calcined Eggshells for Bioenergy Production: Improved Thermo-Kinetic Studies and Reduced Pollutant Emissions

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