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Pyrolysis Characteristics and Non-Isothermal Kinetics of Integrated Circuits.
Chen, Ziwei; Liu, Linhao; Wang, Hao; Liu, Lili; Wang, Xidong.
Afiliação
  • Chen Z; Department of Energy and Resources Engineering, College of Engineering, Peking University, Beijing 100871, China.
  • Liu L; Beijing Key Laboratory for Solid Waste Utilization and Management, Peking University, Beijing 100871, China.
  • Wang H; Energy Bureau of Guangdong Province, Guangzhou 510030, China.
  • Liu L; School of Energy and Environmental Engineering, University of Science & Technology Beijing, Beijing 100083, China.
  • Wang X; Department of Energy and Resources Engineering, College of Engineering, Peking University, Beijing 100871, China.
Materials (Basel) ; 15(13)2022 Jun 24.
Article em En | MEDLINE | ID: mdl-35806585
ABSTRACT
Due to the complexity of components and high hazard of emissions, thermochemical conversions of plastics among waste-integrated circuits (ICs) are more favorable compared with the common treatment options of electronic waste (E-waste), such as chemical treatment and burning. In this study, the waste random-access memory, as the representative IC, was used to investigate the thermal degradation behaviors of this type of E-waste, including a quantitative analysis of pyrolysis characteristics and non-isothermal kinetics. The results show that the pyrolysis of the ICs can be divided into three different decomposition stages. The pyrolysis temperature and gas atmosphere play an important role in the pyrolysis reaction, and the heating rate greatly affects the rate of the pyrolysis reaction. The non-isothermal kinetic parameters and reaction mechanisms of ICs are determined using the Friedman method, Coats and Redfern (CR) method, and Kissinger method. The results show that the actual average activation energy of the pyrolysis reaction of ICs should be between 170 and 200 kJ·mol-1. The optimally fitting model for the ICs pyrolysis is the three-step parallel model consisting of the random nucleation model (Am) and reaction order model (Cn).
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China