Issue 7, 2018

Green synthesis and evaluation of an iron-based metal–organic framework MIL-88B for efficient decontamination of arsenate from water

Abstract

Iron-containing metal–organic frameworks (MOFs) have gradually emerged as environmentally benign alternatives for reducing the levels of environmental contamination because of their advantages, such as readily obtained raw materials with low cost, nontoxic metal source with good biocompatibility, and distinguished physicochemical features e.g., high porosity, framework flexibility, and semiconductor properties. In this study, we reported an innovative strategy for synthesizing an iron-based MOF, MIL-88B, at room temperature. The novelty of this strategy was the use of ethanol as solvent and the pretreatment of dry milling with neither the bulk use of a toxic organic solvent nor the addition of extremely dangerous hydrofluoric acid or strong alkali. The synthesized MIL-88B(Fe) was evaluated as a sorbent for removing arsenate in water and it exhibited high adsorption capacity (156.7 mg g−1) at a low dosage. The removal capacity of trace arsenate on MIL-88B(Fe) was 32.3 mg g−1 at a low equilibrium concentration (6.4 μg L−1), which satisfied the arsenic threshold for drinking water. The results of Fourier transform infrared and X-ray photoelectron spectroscopy indicated that the As(V) molecules bonded with the oxygen molecules, which were coordinated with FeO clusters in the framework. This work presented the potential use of the up-scaled MIL-88B as an excellent sorbent for purifying arsenate-contaminated water.

Graphical abstract: Green synthesis and evaluation of an iron-based metal–organic framework MIL-88B for efficient decontamination of arsenate from water

Supplementary files

Article information

Article type
Paper
Submitted
08 Oct 2017
Accepted
04 Jan 2018
First published
05 Jan 2018

Dalton Trans., 2018,47, 2222-2231

Green synthesis and evaluation of an iron-based metal–organic framework MIL-88B for efficient decontamination of arsenate from water

S. Hou, Y. Wu, L. Feng, W. Chen, Y. Wang, C. Morlay and F. Li, Dalton Trans., 2018, 47, 2222 DOI: 10.1039/C7DT03775A

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