Modification mechanism of caking property of polystyrene waste using low-temperature pyrolysis and its use in coal-blending coking

被引:0
|
作者
Liu, Xiangchun [1 ]
Chen, Ying [1 ]
Song, Huan [1 ]
Cui, Ping [1 ]
机构
[1] Anhui Univ Technol, Sch Chem & Chem Engn, Anhui Prov Key Lab Coal Clean Convers & High Value, Maanshan 243032, Peoples R China
基金
中国国家自然科学基金;
关键词
Polystyrene; pyrolysis; Caking index; Coking property; THERMAL-DEGRADATION; STRUCTURAL CHARACTERISTICS; PLASTIC WASTES; COKE QUALITY; PRODUCTS; RECOVERY; DIMER;
D O I
10.1016/j.cjche.2024.09.025
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Polystyrene (PS) waste was depolymerized using a low-temperature pyrolysis treatment (LTPT) to increase its caking index. The mechanism of caking index modification was revealed by using Fourier transform infrared spectroscopy, thermogravimetric (TG) analysis, pyrolysis-gas chromatography with mass spectrometric detection, and solid-state 13 C nuclear magnetic resonance spectroscopy. The crucible coal-blending coking tests were carried out using an industrial coal mixture and the treated-PS with the highest caking index (PS30 0) or raw PS. Some properties of the resultant cokes were also analyzed. It was demonstrated that the caking index of PS dramatically increased by LTPT; however, exceeding 300 degrees C did not yield any benefit. The caking index increased due to the formation of the caking components, whose molecules are medium in size, caused by LTPT. Additionally, the coke reactivity index of the coke obtained from the mixture containing PS30 0 decreased by 5.1% relative to that of the coke made from the mixture with PS and the coke strength after reaction index of the former increased by 7.3% compared with that of the latter, suggesting that the ratio of depolymerized PS used for coal-blending coking could increase relative to that of PS. (c) 2024 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press Co., Ltd. (CIP). Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:93 / 101
页数:9
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