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Thermal degradation of hazardous 3-layered COVID-19 face mask through pyrolysis: Kinetic, thermodynamic, prediction modelling using ANN and volatile product characterization.
Nawaz, Ahmad; Kumar, Pradeep.
  • Nawaz A; Department of Chemical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi 221005, India.
  • Kumar P; Department of Chemical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi 221005, India.
J Taiwan Inst Chem Eng ; 139: 104538, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2049588
ABSTRACT
Nowadays, wearing a 3-layered face mask (3LFM) to protect against coronavirus illness (COVID-19) has become commonplace, resulting in massive, hazardous solid waste. Since most of them are infected with viruses, a secure way of disposal is necessary to prevent further virus spread. Pyrolysis treatment has recently developed as an effective method for disposing of such hazardous waste and consequently converting them into energy products. In this regard, the goal of the present study is to physicochemically characterize the 3LFM followed by pyrolysis in a TGA to evaluate the pyrolysis performance, kinetic, and thermodynamic parameters and in a semi-batch reactor to characterize the volatile product. Furthermore, an artificial neural network (ANN) was used to forecast thermal deterioration data. The results demonstrated a strong correlation between real and anticipated values. The study proved the relevance of the ANN model and the applicability of pyrolysis for disposing of 3LFM while simultaneously producing energy products.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: J Taiwan Inst Chem Eng Year: 2022 Document Type: Article Affiliation country: J.jtice.2022.104538

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: J Taiwan Inst Chem Eng Year: 2022 Document Type: Article Affiliation country: J.jtice.2022.104538