journal article·2020-07

Preparation and excellent adsorption of water pollution dyes over magnetic Fe3O4/C nanoparticles with hollow grape cluster morphology

Junhong Wang, Qiang Zhang, Junhai Liu, Xiaohui Ji, Jianqi Ma, Guanghui Tian

Journal of Nanoparticle Research· Volume 22· Issue 7
Publisher page

Abstract

Magnetic Fe3O4/C nanoparticles with hollow grape cluster morphology were synthesized through hydrothermal method, using SBA-15 as the hard template, glucose as the carbon source, and ferric chloride hexahydrate as the iron source. As-synthesized magnetic nanomaterials were characterized by means of X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), N2 adsorption-desorption isotherms, vibrating sample magnetometer (VSM), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy. Meanwhile, the adsorption of organic dyes in water by magnetic nanoparticles was further studied. Results indicated that these magnetic nanomaterials exhibited hollow spherical structure similar to a bunch of grapes, and that magnetite Fe3O4 particles were embedded in the matrix of carbon nanoscale. The specific surface area, pore volume, pore diameter, and saturation magnetization of prepared samples were 522.7 m2/g, 0.4454 cm3/g, 3.5 nm, and 31.9 emu/g, respectively. At the same time, as-synthesized materials presented excellent adsorption properties and reutilization, so the total adsorption capacities for methyl orange, methylene blue, and rhodamine B were as high as 400 mg/g, 600 mg/g, and 150 mg/g under the natural pH of solution, respectively. Therefore, it is anticipated that these hollow magnetic Fe3O4/C nanoparticles will have potential industrial application prospects in environment water purification.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Nanomaterials for catalytic reactions · Adsorption and biosorption for pollutant removal · Carbon and Quantum Dots Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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