Issue 22, 2019

An amino-functionalized zirconium-based metal–organic framework/graphene oxide nanocomposite for 2,4-dichlorophenoxyacetic acid determination by ion mobility spectrometry

Abstract

The applicability of an amino-functionalized zirconium-based metal–organic framework/graphene oxide nanocomposite as a sorbent for thin-film microextraction of 2,4-dichlorophenoxyacetic acid was studied. A flexible thin-film was fabricated by the simple spreading of a nylon-6 and polyethylene glycol mixture containing the sorbent material in a plastic Petri dish. Secondary electrospray ionization-ion mobility spectrometry, as the detection method, was combined with the extraction method. The parameters affecting the signal intensity including extraction conditions (solution pH, ionic strength and extraction time) and desorption conditions (desorption solvent, solvent volume and desorption time) were studied and optimized. The extraction efficiency of the present thin-film was higher than those of pristine graphene oxide and the sorbent without graphene oxide. The linear dynamic range of the method was between 0.3 and 200 μg L−1. The limit of detection and limit of quantification were 0.09 and 0.3 μg L−1, respectively. The intra- and inter-day relative standard deviations were lower than 6.1 and 8.9%, respectively. The thin-film was successfully used for extracting 2,4-dichlorophenoxyacetic acid from environmental water and rice samples with satisfactory spiking recoveries in the range of 82–115%.

Graphical abstract: An amino-functionalized zirconium-based metal–organic framework/graphene oxide nanocomposite for 2,4-dichlorophenoxyacetic acid determination by ion mobility spectrometry

Supplementary files

Article information

Article type
Paper
Submitted
09 Feb 2019
Accepted
20 May 2019
First published
20 May 2019

Anal. Methods, 2019,11, 2929-2936

An amino-functionalized zirconium-based metal–organic framework/graphene oxide nanocomposite for 2,4-dichlorophenoxyacetic acid determination by ion mobility spectrometry

M. Saraji, M. T. Jafari and V. Mohammadi, Anal. Methods, 2019, 11, 2929 DOI: 10.1039/C9AY00287A

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