Co-production of carbon nanotubes and hydrogen from waste plastic gasification in a two-stage fluidized catalytic bed

Yang, Ren-Xuan; Wu, Shan-Luo; Chuang, Kui-Hao; Wey, Ming‐Yen

doi:10.1016/j.renene.2020.05.141

Cited by 69 publications

(29 citation statements)

References 53 publications

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“…In comparison with recent work on CNTs from plastic waste, Yang et al [49] [42] obtained a carbon yield of 86.4 % from 1.5 g feedstock of PP (equivalent to 0.23 g g with Ni-La oxides. Aboul-Enein and Awadallah [15] investigated the effect of Fe/Mo ratio on a MgO supported bimetallic Fe-Mo catalyst for production of carbon nanomaterials from LDPE, and the optimal yield reached 976% of catalyst mass (0.325 g g -1 LDPE) at a Fe:Mo weight ratio of 30:20.…”

Section: Carbon Nanomaterials From Pyrolysis-catalysis Of Waste Plasticsmentioning

confidence: 91%

Carbon nanotubes from post-consumer waste plastics: Investigations into catalyst metal and support material characteristics

Yao

Yang

et al. 2021

Applied Catalysis B: Environmental

131

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Section: Carbon Nanomaterials From Pyrolysis-catalysis Of Waste Plasticsmentioning

confidence: 91%

Carbon nanotubes from post-consumer waste plastics: Investigations into catalyst metal and support material characteristics

Yao

Yang

et al. 2021

Applied Catalysis B: Environmental

131

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“…This type of practice includes three basic types: incineration, gasification, and pyrolysis process [2]. The products resulting from treating plastic waste vary between thermal energy used in heating systems during winter time, and char in the form of carbon black that can be used as a solid fuel, biogas, oil, wax, etc., [3][4][5]. When compared with all these energy products, pyrolysis oil product has a higher calorific value and better economic performance [6,7].…”

Section: Introductionmentioning

confidence: 99%

Catalytic Pyrolysis Kinetic Behavior and TG-FTIR-GC–MS Analysis of Metallized Food Packaging Plastics with Different Concentrations of ZSM-5 Zeolite Catalyst

et al. 2021

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Recently, the pyrolysis process has been adapted as a sustainable strategy to convert metallized food packaging plastics waste (MFPW) into energy products (paraffin wax, biogas, and carbon black particles) and to recover aluminum. Usually, catalysts are used in pyrolysis treatment to refine pyrolysis products and to increase their yield. In order to study the effect of a catalyst on the formulated volatile products, this work aims to study the pyrolysis behavior of MFPW in presence of catalyst, using TG-FTIR-GC–MS system. The pyrolysis experiments were conducted with ZSM-5 Zeolite catalyst with different concentrations (10, 30, and 50 wt.%) at different heating rates (5, 10, 15, 20, 25, and 30 °C/min). In addition, TG-FTIR system and GC-MS unit were used to observe and analyze the thermal and chemical degradation of the obtained volatile compounds at maximum decomposition peaks. In addition, the kinetic results of catalytic pyrolysis of ZSM-5/MFPW samples matched when model-free methods, a distributed activation energy model (DAEM), and an independent parallel reaction kinetic model (IPR) were used. The TGA-DTG results showed that addition of a catalyst did not have a significant effect on the features of the TGA-DTG curves with similar weight loss of 87–90 wt.% (without taking the weight of the catalyst into account). Meanwhile, FTIR results manifested strong presence of methane and high-intensity functional group of carboxylic acid residues, especially at high concentration of ZSM-5 and high heating rates. Likewise, GC-MS measurements showed that Benzene, Toluene, Hexane, p-Xylene, etc. compounds (main flammable liquid compounds in petroleum oil) generated catalysts exceeding 50%. Finally, pyrolysis kinetics showed that the whole activation energies of catalytic pyrolysis process of MFPW were estimated at 289 kJ/mol and 110, 350, and 174 kJ/mol for ZSM-5/MFPW samples (10, 30, and 50 wt.%, respectively), whereas DAEM and IPR approaches succeeded to simulate TGA and DTG profiles with deviations below <1.

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“…3 Innovative technologies such as pyrolysis and gasification have been proposed as a means of utilizing plastic wastes for the production of fuel and value-added chemicals. [4][5][6][7][8][9][10] Both the pyrolysis and gasification processes employ thermal energy to convert waste plastic materials to liquid fuel and hydrogen-rich syngas without combustion. 3,5 The amount of gasifying agent (oxygen or steam) during the gasification process is often controlled.…”

Section: Introductionmentioning

confidence: 99%

“…Various experimental studies have shown that factors such as feed composition, catalyst type, particle size, amount of plastic waste in a mixture significantly influence the conversion of waste plastic to value-added fuel products. 6,7 Friengfung et al investigated the catalytic steam gasification of a mixture of HDPE and low-density polyethylene (LDPE) for hydrogen production. Using a gasifying temperature of 850 C and steam to O 2 ratio of 1:1, the waste plastic gasification resulted in the evolution of 35% H 2 .…”

Section: Introductionmentioning

confidence: 99%

“…Rather than promoting the policy of outright banning waste plastics, researchers have agitated for sustainable utilization of waste plastics for the production of green fuel and chemicals 3 . Innovative technologies such as pyrolysis and gasification have been proposed as a means of utilizing plastic wastes for the production of fuel and value‐added chemicals 4‐10 . Both the pyrolysis and gasification processes employ thermal energy to convert waste plastic materials to liquid fuel and hydrogen‐rich syngas without combustion 3,5 .…”

Section: Introductionmentioning

confidence: 99%

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Modeling the prediction of hydrogen production by co‐gasification of plastic and rubber wastes using machine learning algorithms

et al. 2021

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This study aimed to investigate the application of radial basis function (RBF) and multilayer perceptron (MLP) artificial neural networks for modeling hydrogen production by co-gasification of rubber and plastic wastes. Both the RBF and MLP neural networks were configured by determining the besthidden neurons that could offer optimized performance. Based on the besthidden neurons, a model architecture of 4-16-1, 4-20-1, 4-17-1, and 4-3-1 was obtained for RBF (with standard activation function), RBF (with ordinary activation function), one-layer MLP, and two-layer MLP, respectively, indicating the number of input nodes, the hidden neurons, and the output nodes. The predicted hydrogen production from the co-gasification closely agrees with the observed values. The 1-layer MLP with R 2 of .990 displayed the best performance with all the input parameters having a significant influence on 9 the model output. The neural network algorithm obtained in this study could be implemented in the eventuality of making a vital decision in the process operation of the co-gasification process for hydrogen production.

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Co-production of carbon nanotubes and hydrogen from waste plastic gasification in a two-stage fluidized catalytic bed

Cited by 69 publications

References 53 publications

Carbon nanotubes from post-consumer waste plastics: Investigations into catalyst metal and support material characteristics

Carbon nanotubes from post-consumer waste plastics: Investigations into catalyst metal and support material characteristics

Catalytic Pyrolysis Kinetic Behavior and TG-FTIR-GC–MS Analysis of Metallized Food Packaging Plastics with Different Concentrations of ZSM-5 Zeolite Catalyst

Modeling the prediction of hydrogen production by co‐gasification of plastic and rubber wastes using machine learning algorithms

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