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Feasible water flow filter with facilely functionalized Fe3O4-non-oxidative graphene/CNT composites for arsenic removal

•Couette-Taylor flow technique was used to facilely functionalize nanomaterials.•Fe3O4-non-oxidative graphene/CNTs were equipped for water flow filter.•The water flow filter was better than a batch method for removing arsenic.•3D structure of Fe3O4-non-oxidative graphene/CNTs improved the removal ef...

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Bibliographic Details
Published in:Journal of environmental chemical engineering 2016-09, Vol.4 (3), p.3246-3252
Main Authors: Park, Won Kyu, Yoon, Yeojoon, Kim, Seungdu, Yoo, Seonmi, Do, Youngjin, Kang, Joon-Wun, Yoon, Dae Ho, Yang, Woo Seok
Format: Article
Language:English
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Summary:•Couette-Taylor flow technique was used to facilely functionalize nanomaterials.•Fe3O4-non-oxidative graphene/CNTs were equipped for water flow filter.•The water flow filter was better than a batch method for removing arsenic.•3D structure of Fe3O4-non-oxidative graphene/CNTs improved the removal efficiency. Practical applications of carbon-based nanomaterials are important issues for water treatment technologies, especially for heavy metal adsorption. For the applications, a facile method to functionalize the carbon-based nanomaterials and a strategy for their typical uses are required. Here, we report a highly feasible water flow filter filled with Fe3O4-functionalized non-oxidative graphene/CNT prepared via facile functionalization in a Couette-Taylor flow reactor for arsenic removal. Fe3O4 was uniformly functionalized on the CNTs and the non-oxidative graphene using the Couette-Taylor flow method, which allows fast production of a large number of filters. The hybrid composite of Fe3O4-functionalized non-oxidative graphene/CNT demonstrated an improvement in the arsenic removal efficiency when it served as a flow filter rather than when used in the batch method because its 3D structure enhanced both the water flow pathway and the contact area with Fe3O4. Adaption for household use for continuous purification of water is simple for this proposed filter.
ISSN:2213-3437
2213-3437
DOI:10.1016/j.jece.2016.06.028