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Thermogravimetric analysis of textile waste: kinetic parameters and pyrolytic decomposition mechanisms
Summary
This study uses thermogravimetric analysis (TGA) to characterize how textile waste, including synthetic fibers like polyester and nylon, decomposes under heat. By measuring weight loss at different temperatures, the researchers determine kinetic parameters that describe the pyrolysis process. These findings are useful for designing thermal recycling or waste-to-energy systems for mixed textile waste streams.
• Optimizes pyrolysis recycling by analyzing textile thermal decomposition. • Determines activation energy using model-free and Coats-Redfern methods. • Identifies fiber-specific decomposition temperatures and reaction mechanisms. • Quantifies gaseous emissions, aiding pollution control in textile recycling. Thermogravimetric analysis (TGA) is a powerful technique to elucidate the thermal decomposition behavior of textile materials, a critical step in designing efficient pyrolysis processes. In this study, new insights into the kinetic behavior and activation energies of various textile fibers, 100 % cotton, 100 % polyester, and cotton/polyester blends, using model-free kinetic methods (Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Friedman (FR)) and the Coast-Redfern (CR) method were provided. Thermogravimetric analysis (TGA) was performed at multiple heating rates (5, 10, 15, and 20 °C/min) under an N 2 atmosphere to simulate pyrolysis conditions. Results revealed a clear relationship between fiber composition and decomposition behavior. Therefore, while 100 % cotton decomposes at 371 °C and 100 % polyester at 431 °C, blended fibers exhibit two distinct decomposition steps, a feature not previously reported in detail. The model-free methods indicated that the activation energy (E a ) increases with conversion (α), highlighting the complex multi-step decomposition of these fibers. For example, in 100 % cotton, E a increases from 96.9 kJ/mol (α = 0.1) to 195.6 kJ/mol (α = 0.9), indicating a close dependence on the stages of decomposition. Furthermore, the CR method revealed that the most appropriate reaction models differ by fiber type, identifying the nucleation (F1) model as one of the most suitable, offering a predictive tool for optimizing pyrolysis conditions in industrial textile waste management.