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Cited by 369

The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.

Enhanced dyes adsorption from wastewater via Fe3O4 nanoparticles functionalized activated carbon

Liu, Xiaoduo, Tian, Jiefu, Li, Yuanyuan, Sun, Ningfei, Mi, Shu, Xie, Yong, Chen, Ziyu·2019·Journal of Hazardous Materials

Abstract

Fe3O4 nanoparticles functionalized activated carbon (Fe3O4/AC) as an adsorbent was prepared and used for fast and effectively removing rhodamine B (RhB) and methyl orange (MO) from aqueous solution. Its physical and chemical properties characterized indicate that the adsorbent possesses abundant surface functional groups, sensitive magnetic response and enhanced specific surface area. Batch experiments were carried out to investigate the adsorption capacity and mechanisms. The obtained experimental data fitted well with the general-order kinetic equation and Liu's isotherm model with a maximum adsorption capacity of 182.48 mg g-1 for RhB and 150.35 mg g-1 for MO, respectively. The thermodynamic parameter was analyzed further and it showed an exothermic and spontaneous adsorption process. This composite with high adsorption efficiency and rapid magnetic separation can be a promising and recyclable adsorbent for practical wastewater treatment and purification processes.

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Metadata

Authors
Liu, X., Tian, J., Li, Y., Sun, N., Mi, S., Xie, Y., & Chen, Z.
Venue
Journal of Hazardous Materials
Publisher
Elsevier BV
Published
2019-07
Volume
373
Pages
397-407
ISSN
0304-3894 (ISSN-L)
OpenAlex
W2926994832
Cited by
369
References
62
FWCI
17.52
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Enhanced dyes adsorption from wastewater via Fe3O4 nanoparticles functionalized activated carbon. https://app.cochat.ai/papers/10.1016/j.jhazmat.2019.03.103
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Liu, X., Tian, J., Li, Y., Sun, N., Mi, S., Xie, Y., & Chen, Z. (2019). Enhanced dyes adsorption from wastewater via Fe3O4 nanoparticles functionalized activated carbon. Journal of Hazardous Materials. https://doi.org/10.1016/j.jhazmat.2019.03.103

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.