Pyrolysis conversion of multi-layer packaging waste under a CO2 atmosphere: Thermo-kinetic study, evolved products analysis and artificial neural networks modeling

被引:9
|
作者
Wang, Binhui [1 ]
Yao, Zhitong [1 ]
Kumar, Sachin [2 ]
Mohamed, Mohammed Salama Abdelhady [3 ]
Sattar, Ahmed Mohamed Abdel [3 ]
Ortuno, Nuria [4 ]
Wang, Xiaobo [5 ]
Qi, Wei [5 ]
机构
[1] Hangzhou Dianzi Univ, Coll Mat Sci & Environm Engn, Hangzhou 310018, Peoples R China
[2] Cent Univ Jharkhand, Ctr Excellence Green & Efficient Energy Technol Co, Dept Energy Engn, Ranchi 835205, India
[3] Cairo Univ, Irrigat & Hydraul Dept, Giza 12613, Egypt
[4] Univ Alicante, Univ Inst Chem Proc Engn, Carretera San Vicente del Raspeig S-N, Alicante 03690, Spain
[5] Chinese Acad Sci, Guangzhou Inst Energy Convers, Guangzhou 510640, Peoples R China
关键词
Municipal solid waste; Packing waste; Paperboard; Beverage carton; Thermo-chemical conversion; Artificial neural networks; POSTCONSUMER TETRA PAK; CELLULOSE; ALUMINUM; BIOMASS; RECOVERY; POLYETHYLENE; ENERGY; MICRO;
D O I
10.1016/j.ces.2024.120584
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Packaging waste such as beverage carton forms a significant part of municipal solid waste and its pyrolysis behavior, kinetics, and thermodynamics were studied. A four-stage decomposition process was revealed: dehydration below 200 degree celsius, paperboard degradation at 200-400 degree celsius, polyethylene devolatilization at 400-550 degree celsius, and inorganic decomposition at 550-900 degree celsius. The evolved products included furans and acetic acid during stage II, followed by the presence of 2-butene and 1-pentene in the subsequent stage. Apparent activation energy (Ea) were determined using model-free models, revealing a notable level of comparability among these results. The average Ea was 123.6 kJ/mol within alpha range of 0.10-0.60, increasing to 233.3 kJ/mol beyond that range. The most probable reaction mechanism was determined, with the one-dimensional model proving more reliable. An artificial neural network model was developed to predict the thermal degradation. The selected topology of 5*15*1 displayed a robust ability to predict the thermal data.
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页数:11
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