Catalytic pyrolysis of oxygen-containing waste polycarbonate for the preparation of carbon nanotubes and H2-rich syngas.

IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Waste management Pub Date : 2024-12-23 DOI:10.1016/j.wasman.2024.12.022
Pengpeng Luan, Tiecheng Liu, Jinglan Wang, Beibei Yan, Guanyi Chen, Zhanjun Cheng
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引用次数: 0

Abstract

In this study, ex-situ catalytic pyrolysis of oxygen-containing polycarbonate (PC) was conducted to prepare carbon nanotubes (CNTs) and H2-rich syngas. This study examined the influence of the active metal components (Ni and Fe), catalyst pre-reduction, and pre-deoxygenation of pyrolysis volatiles on the catalytic performance and mechanism. Results show that the reductive constituents in pyrolysis volatiles make it difficult to reduce the Fe oxides, thus hindering the CNTs growth on Fe catalysts, compared to Ni catalysts. H2 pre-reduction of Ni and Fe catalysts enhances the generation of CNTs and syngas. The pre-reduced Fe catalyst exhibits better carbon deposit performance, reaching 263 mg/gplastics. The pre-reduced Ni catalyst better facilitates the reforming reaction of CO2 and H2O, resulting in higher syngas yields of 32.75 mmol/gplastics, with a volume proportion of 94.4 vol%. The addition of the deoxygenation catalyst Ni/HZSM-5 promotes the growth of CNTs with fewer defects and higher graphitization on Ni catalysts. The excess CO2 and H2O generated by the introduction of Ni/HZSM-5 may oxidize the Fe0 on pre-reduced Fe catalysts, inhibiting the growth of CNTs. The mechanism of the growth of CNTs and syngas from PC is also explored. The findings can provide theoretical guidance for the disposal of waste plastics.

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来源期刊
Waste management
Waste management 环境科学-工程:环境
CiteScore
15.60
自引率
6.20%
发文量
492
审稿时长
39 days
期刊介绍: Waste Management is devoted to the presentation and discussion of information on solid wastes,it covers the entire lifecycle of solid. wastes. Scope: Addresses solid wastes in both industrialized and economically developing countries Covers various types of solid wastes, including: Municipal (e.g., residential, institutional, commercial, light industrial) Agricultural Special (e.g., C and D, healthcare, household hazardous wastes, sewage sludge)
期刊最新文献
Evaluating drivers of PM2.5 air pollution at urban scales using interpretable machine learning. Catalytic pyrolysis of oxygen-containing waste polycarbonate for the preparation of carbon nanotubes and H2-rich syngas. Fabrication of SS 316L particle-infilled PLA composite filaments from cast-off bi-material extrudates for 3D printing applications. Unveiling the resource potential of space debris: A forecast of valuable metals to 2050. ECCDN-Net: A deep learning-based technique for efficient organic and recyclable waste classification.
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