Browsing by Author "Striugas, Nerijus"

Now showing 1 - 4 of 4

Pyrolysis behaviour of ultrafiltration polymer composite membranes (PSF/ PET): Kinetic, thermodynamic, prediction modelling using artificial neural network and volatile product analysis
(Elsevier B.V, 2024-04) Yousef, Samy; Eimontas, Justas; Striugas, Nerijus; Mohamed, Alaa; Abdelnaby, Mohammed Ali
This study aims to explore the feasibility of managing ultrafiltration polymer composite membranes (UPCM) waste and converting it into valuable chemicals and energy products using a pyrolysis process. The thermal decomposition experiments were performed on polysulfone (PSF)/polyethylene terephthalate (PET) membranes using thermogravimetric analysis (TG). The vapors generated during the thermochemical process were analyzed under different heating rate conditions using TG-FTIR and GC/MS. In addition, the kinetic and thermodynamic parameters of the pyrolysis process were determined using conventional modeling methods and artificial neural network (ANN) method. The results demonstrated that the PSF/PET feedstock exhibits ahigh volatile matter content (77 % wt.%), which can be completely decomposed up to 600 °C by 79 wt%. While TG-FTIR analysis showed that the released vapors contained aromatic groups and benzoic acid (89.21 wt% at 15˚C/min) as the main GC/MS compound. Moreover, the kinetic analysis demonstrated complete decomposition of the membranes at a lower activation energy (151 kJ/mol). Meanwhile, the ANN model exhibited high performance in predicting the degradation stages of PSF/PET membranes under unknown heating conditions. This approach shows potential for modeling the thermal decomposition of ultrafiltration composite membranes more broadly.
Pyrolysis Kinetic Behavior and Thermodynamic Analysis of PET Nonwoven Fabric
(MDPI AG, 2023-09) Yousef, Samy; Eimontas, Justas; Striugas, Nerijus; Mohamed, Alaa; Abdelnaby, Mohammed Ali
This research aims to maximize polyethylene terephthalate (PET) nonwoven fabric waste and make it as a new source for benzoic acid extraction using a pyrolysis process. The treatment was performed using a thermogravimetric analyzer (TGA) and released products were characterized using FTIR spectroscopy and gas chromatography–mass spectrometry (GC–MS). The pyrolysis kinetic and thermodynamic behavior of PET fabric was also studied and simulated using different linear and nonlinear models. The results show that the PET fabric is very rich in volatile matter (80 wt.%) and can completely degrade under 490 ◦C with a weight loss of 84%. Meanwhile, the generated vapor was rich in the carbonylic C=O functional group (FTIR), and the GC–MS analysis concluded that benzoic acid was the major compound with an abundance of 75% that was achieved at the lowest heating rate (5 ◦C/min). The linear kinetic results showed that PET samples had an activation energy in the ranges of 193–256 kJ/mol (linear models) and ~161 kJ/mol (nonlinear models). The thermodynamic parameters, including enthalpy, Gibbs free energy, and entropy, were estimated in the ranges of 149–250 kJ/mol, 153–232 kJ/mol, and 256–356 J/mol K, respectively. Accordingly, pyrolysis treatment can be used to extract benzoic acid from PET fabric waste with a 134% increase in the benzoic acid abundance that can be recovered from PET bottle plastic waste.
Synthesis of benzoic acid from catalytic co-pyrolysis of waste wind turbine blades and biomass and their kinetic analysis
(Elsevier B.V., 2024-08) Yousef, Samy; Eimontas, Justas; Striugas, Nerijus; Abdelnaby, Mohammed Ali
This work aims to study the catalytic co-pyrolysis of waste wind turbine blades (WTB: consists of fiberglass/unsaturated polyester resin) and woody biomass (WB) over ZSM-5 and Y-type zeolite catalysts for the production of benzoic acid. The experiments were performed on an equal combination of WTB and WB (WTB/WB) and a fixed amount of catalyst (50 wt%) using a thermogravimetric (TG) analyser at 10, 20 and 30 °C/min. The evolved products from the catalytic co-pyrolysis process were recognized using TG-FTIR and GC/MS. The kinetic and thermodynamic characteristics of catalytic co-pyrolysis was studied using various linear and nonlinear approaches. Also, the decomposition curves were predicted mathematically using an artificial neural network algorithm. The results revealed that the mixture was decomposed in the presence of both catalysts in the form of dual decomposition peaks at 361–374 °C and 428–443 °C, respectively. Based on TG-FTIR results, the C[dbnd]O stretching and carbon dioxide clusters were their main functional groups. While the GC-MS analysis revealed that the released vapours were completely free of toxic styrene (the main compound of resin) and the catalytic co-pyrolysis treatment succeeded in converting it into highly abundant benzoic acid, especially at 10 °C/ min, with an estimated 71.4 % (ZSM-5) and 64 % (Y-type). Whereas the activation energy was estimated at 262–295 kJ/mol (ZSM-5) and 319–357 kJ/mol (Y-type) with almost similar reaction complexity when compared to the case of absence of catalysts. Finally, the developed ANN algorithm showed high efficiency in predicting TG decomposition zones for both WTB/WB mixtures over zeolite catalysts with R2 more than 0.99. These results demonstrate that WB and zeolite catalysts can be used for upgrading the pyrolysis oil of WTB and eliminate its toxic styrene and convert it into benzoic acid and other aromatic hydrocarbons compounds (such as benzene, alanine, and 2-Propanamine).
Synthesis of value-added aromatic chemicals from catalytic pyrolysis of waste wind turbine blades and their kinetic analysis using artificial neural network
(Elsevier, 2024-01) Yousef, Samy; Eimontas, Justas; Striugas, Nerijus; Abdelnaby, Mohammed Ali
This research aims to convert the resin fraction of waste wind turbine blades (WTB) into value-added aromatic chemicals using catalytic pyrolysis. The catalytic study on WTB made of glass fibre/unsaturated polyester resin (UPR) was performed on two different types of zeolite catalysts (ZSM-5 and Y-type) using a thermogravimetric (TG) analyser. The effect of catalyst and heating rate on the abundance and composition of the synthesised aromatic chemicals was observed using TG-FTIR and GC/MS. The kinetics and thermodynamic behaviour of catalytic pyrolysis of WTB was also studied using traditional modelling techniques (KAS, FWO, Friedman, Vyazovkin, and Cai) and an artificial neural network (ANN). TG-FTIR results showed that the gases released from the catalytic process were very rich in aromatic groups, while GC/MS analysis revealed that benzene, toluene, and ethylbenzene (BTE) were the main constituents of the synthesised aromatic chemicals with abundance estimated at 36% (ZSM-5 at 10◦C/min) and 64% (Y-type at 15◦C/min) accompanied by a significant reduction in styrene formation up to 16.2% (main toxic element in the UPR). Besides, it contributed to reduction of the activation energy of the reaction up to 126 KJ/mol (ZSM-5) and 100 KJ/mol (Y-type). The trained ANN model also showed high performance in predicting the thermal decomposition zones of WTB at unknown heating rates with R2 close to 1. Accordingly, the use of catalytic pyrolysis of WTB over a Y-type zeolite catalyst is highly recommended for decomposition of UPR to aromatic chemicals BTE and reduction of styrene in the produced fuel.