Recent advancements in the use of plastics as a carbon source for carbon nanotubes synthesis - A review

Modekwe, Helen U.; Daramola, Michael O.; Mamo, Messai A.; Moothi, Kapil

doi:10.1016/j.heliyon.2024.e24679

Heliyon

2024

DOI: 10.1016/j.heliyon.2024.e24679

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Recent advancements in the use of plastics as a carbon source for carbon nanotubes synthesis - A review

Helen U. Modekwe,

Michael O. Daramola,

Messai A. Mamo

et al.

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2024

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Cited by 4 publications

References 167 publications

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Artificial neural network for predicting the performance of waste polypropylene plastic-derived carbon nanotubes

Modekwe,

Akintola,

Ayeleru

et al. 2024

Int. J. Environ. Sci. Technol.

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In this study, an artificial neural network model using function fitting neural networks was developed to describe the yield and quality of multi-walled carbon nanotubes deposited over NiMo/CaTiO3 catalyst using waste polypropylene plastics as cheap hydrocarbon feedstock using a single-stage chemical vapour deposition technique. The experimental dataset was developed using a user-specific design with four numeric factors (input variable): synthesis temperature, furnace heating rate, residence time, and carrier gas (nitrogen) flow rate to control the performance (yield and quality) of produced carbon nanotubes. Levenberg–Marquardt algorithm was utilized in training, validating, and testing the experimental dataset. The predicted model gave a considerable correlation coefficient (R) value close to 1. The presented model would be of remarkable benefit to successfully describe and predict the performance of polypropylene-derived carbon nanotubes and show how the predictive variables could affect the response variables (quality and yield) of carbon nanotubes.

show abstract

Artificial neural network for predicting the performance of waste polypropylene plastic-derived carbon nanotubes

Modekwe,

Akintola,

Ayeleru

et al. 2024

Int. J. Environ. Sci. Technol.

View full text Add to dashboard Cite

show abstract

Multifactorial evaluation of an ultra-fast process for electrospinning of recycled expanded polystyrene to manufacture high-efficiency membranes for nanoparticle air filtration

Lima,

Chagas,

Honorato

et al. 2024

Journal of Environmental Management

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Heavy metals removal from mine wastewater using polysulfone membrane infused with waste plastic-derived carbon nanotubes as filler

Modekwe,

Ramatsa,

Mamo

et al. 2024

Waste Management Bulletin

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Recent advancements in the use of plastics as a carbon source for carbon nanotubes synthesis - A review

Cited by 4 publications

References 167 publications

Artificial neural network for predicting the performance of waste polypropylene plastic-derived carbon nanotubes

Artificial neural network for predicting the performance of waste polypropylene plastic-derived carbon nanotubes

Multifactorial evaluation of an ultra-fast process for electrospinning of recycled expanded polystyrene to manufacture high-efficiency membranes for nanoparticle air filtration

Heavy metals removal from mine wastewater using polysulfone membrane infused with waste plastic-derived carbon nanotubes as filler

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