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Co-pyrolysis of Chlorella vulgaris with plastic wastes: Thermal degradation, kinetics and Progressive Depth Swarm-Evolution (PDSE) neural network-based optimization.

Authors :
Isabel Jia Yen Tan
Adrian Chun Minh Loy
Bridgid Lai Fui Chin
Kin Wai Cheah
Sin Yong Teng
Bing Shen How
Hatem Alhazmi
Wei Dong Leong
Huei Yeong Lim
Man Kee Lam
Su Shiung Lam
Source :
Green Technologies & Sustainability. May2024, Vol. 2 Issue 2, p1-23. 23p.
Publication Year :
2024

Abstract

The search of sustainable route for biofuel production from renewable biomass have garnered wide interest to seek for various routes without compromising the environment. Co-pyrolysis emerges as a promising thermochemical route that can improve the pyrolysis output from simultaneously processing more than two feedstocks in an inert atmosphere. This paper focuses on the kinetic modeling and neuro-evolution optimization in the application of catalytic co-pyrolysis of microalgae and plastic waste using HZSM-5 supported on limestone (HZSM-5/LS), in which co-pyrolysis of binary mixture of microalgae and plastic wastes (i.e. High-Density Polyethylene and Low-Density Polyethylene) was investigated over different heating rates. The results have shown a positive synergistic effect between the microalgae and polyethylene in which the apparent activation energies values have reduced significantly (-20 kJ/mol) compared to that obtained by pyrolysis of individual microalgae component. The kinetic models reflect that the mixture of microalgae and Low-Density Polyethylene for use as co-pyrolysis feedstock requires activation energy that is 23% and 13% lower compared to that required by pure microalgae and the mixture of microalgae and High-Density Polyethylene, respectively. The Progressive Depth Swarm-Evolution (PDSE) was used for neural architecture search, which subsequently provided optimal reaction condition at 873 K can achieve 99.6 % of degradation rate using a tri-combination of LDPE (0.13 %) + HDPE (0.77 %) + MA (0.11 %) in the presence of HZSM-5/LS catalyst. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
29497361
Volume :
2
Issue :
2
Database :
Academic Search Index
Journal :
Green Technologies & Sustainability
Publication Type :
Academic Journal
Accession number :
177099493
Full Text :
https://doi.org/10.1016/j.grets.2024.100077