Literature DB >> 30173385

Orthogonal design-guided preparation of multi-level porous-activated carbon by pyrolysis of waste polyester textiles.

Xiaoying Yu1, Shuhua Wang2, Yindong Gao1, Zhanxia Bao1.   

Abstract

Multi-level porous amorphous-activated carbon with excellent adsorption performance was prepared by a ZnCl2-assisted pyrolysis of waste polyester textiles. Experimental parameters were optimized by using orthogonal design. Result of orthogonal design revealed that pyrolysis temperature and pyrolysis time were the dominant individual factors. Samples prepared at the optimal condition were systematically characterized by Brunauer-Emmett-Teller (BET) porosity analyzer, FT-IR spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscope (SEM), and transmission electron microscope (TEM). Iodine (I2), methylene blue (MB) and phenol (PhOH) were selected as target dyes to measure the adsorption performance. Experimental results showed that porous-activated carbon with multi-level pores could be obtained by optimizing experimental parameters. The specific surface area and total pore volume were calculated to be 846.37 m2 g-1 and 0.726 cm3 g-1, respectively. Benefit from its multi-level rich porosity, the optimized sample possessed attractive adsorption performance toward different types of dyes. The corresponding adsorption capacity toward I2, MB, and PhOH were calculated to be 980.48, 384.00, and 300.62 mg g-1, respectively.

Entities:  

Keywords:  Activated carbon; Adsorption; Orthogonal design; Waste polyester textiles

Mesh:

Substances:

Year:  2018        PMID: 30173385     DOI: 10.1007/s11356-018-3002-2

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  7 in total

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Journal:  Nanotechnology       Date:  2018-03-23       Impact factor: 3.874

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Journal:  Int J Environ Res Public Health       Date:  2018-02-01       Impact factor: 3.390

  7 in total
  1 in total

1.  Research on Online Rapid Sorting Method of Waste Textiles Based on Near-Infrared Spectroscopy and Generative Adversity Network.

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  1 in total

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