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The accuracy of multiple methods for estimating the reaction order of representative thermoplastic polymers waste for energy utilization

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  • Zhang, Wenlong
  • Zhang, Juan
  • Ding, Yanming
  • Zhou, Ru
  • Mao, Shaohua

Abstract

Thermoplastic polymers are versatile for different fields, and their waste is produced largely. Among the waste treatment methods, pyrolysis is an important method to dispose of thermoplastic polymers waste because of potential energy utilization. Furthermore, accurate pyrolysis kinetic parameters can reflect the pyrolysis process. Therein, reaction order n is an essential factor to characterize reaction kinetics, while the difference between different n values is very small, so the accuracy of n should be paid more attention. To obtain the accurate n value of thermoplastic polymers waste in nitrogen, one representative material called extruded polystyrene (XPS) was studied by using thermogravimetric analysis at five heating rates. The kinetic parameters and thermodynamic parameters were calculated simultaneously, and n was estimated by multiple methods (master plots, model-free, Shuffled Complex Evolution (SCE) and model reconstruction) at heating rates of 10, 30 and 40 K/min. The results showed that XPS waste had important energy potentials, and the n was 2, 2.08, 1.99 and 1.64 for four methods, respectively. Moreover, based on fixed kinetic parameters, the accuracy of n obtained by multiple methods was compared at 3 and 80 K/min not used to estimate kinetic parameters. The accuracy of these methods was: SCE > model reconstruction > model-free > master plots.

Suggested Citation

  • Zhang, Wenlong & Zhang, Juan & Ding, Yanming & Zhou, Ru & Mao, Shaohua, 2022. "The accuracy of multiple methods for estimating the reaction order of representative thermoplastic polymers waste for energy utilization," Energy, Elsevier, vol. 239(PB).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pb:s0360544221023604
    DOI: 10.1016/j.energy.2021.122112
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    References listed on IDEAS

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    2. Xu, Li & Chen, Yu & Zhang, Yuan & Pan, Longwei & Qi, Yongfeng, 2025. "A combined heuristic optimization algorithm and Gaussian deconvolution procedure for the kinetics extraction of building wood panel pyrolysis," Energy, Elsevier, vol. 332(C).
    3. Caferra, Rocco & D'Adamo, Idiano & Morone, Piergiuseppe, 2023. "Wasting energy or energizing waste? The public acceptance of waste-to-energy technology," Energy, Elsevier, vol. 263(PE).
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    5. Ma, Xingxing & Tian, Yajun & Wang, Nana & Zhao, Jinghao & Li, Wen-ying & Xie, Kechang, 2026. "Machine learning methods for understanding coal pyrolysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PC).
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    7. Ding, Yanming & Chen, Wenlu & Zhang, Wenlong & Zhang, Xueting & Li, Changhai & Zhou, Ru & Miao, Fasheng, 2022. "Experimental and numerical simulation study of typical semi-transparent material pyrolysis with in-depth radiation based on micro and bench scales," Energy, Elsevier, vol. 258(C).

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