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Rapid detection of metal impurities on the surfaces of intact objects with irregular shapes using electrochemical mass spectrometry

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Abstract

New approaches are demanded in daily life and industry for the rapid inspection of chemical impurities on various objects, particularly those with irregular shapes. Herein, an analytical strategy combining electrochemistry (EC) and mass spectrometry (MS) has been developed for the direct inspection of metal impurities on various objects which are commonly used in daily life and industry. An intact object (e.g., necklace, bearing, ring) was immersed in an electrolytic cell containing EDTA/acetonitrile/water solution at appropriate potentials to form metal ions. The formed metal ions were instantly chelated with specific ligands (e.g. ethylenediaminetetraacetic acid) and sampled for online electrospray ionization (ESI) with high-resolution MS detection. The unique feature of the method is that metal speciation information can be obtained even when just a metal impurity (e.g., Pb, Ni) is localized on a hard-to-reach tiny spot on the inner surface of objects with extremely irregular shapes. A single sample analysis requires less than 10 minutes, regardless of the object shape. The limit of detection is 0.05 ppb with sample consumption on the nanogram level. The experimental results demonstrate that the method is promising for the non-destructive quality and safety inspection of metal impurities on virtually any kinds of objects with high chemical sensitivity.

Graphical abstract: Rapid detection of metal impurities on the surfaces of intact objects with irregular shapes using electrochemical mass spectrometry

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Publication details

The article was received on 21 Dec 2018, accepted on 26 Mar 2019 and first published on 27 Mar 2019


Article type: Paper
DOI: 10.1039/C8AN02472C
Citation: Analyst, 2019, Advance Article

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    Rapid detection of metal impurities on the surfaces of intact objects with irregular shapes using electrochemical mass spectrometry

    L. Song, J. Xu, D. Zhong, K. Chingin, Y. Qu and H. Chen, Analyst, 2019, Advance Article , DOI: 10.1039/C8AN02472C

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