4.6 Article

Label-free gold nanorod-based plasmonic sensing of arsenic(iii) in contaminated water

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ANALYST
卷 144, 期 15, 页码 4708-4718

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ROYAL SOC CHEMISTRY
DOI: 10.1039/c9an00668k

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  1. DST-PURSE fund from the Government of India
  2. UGC-UPOE fund from the Government of India

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In this paper, we report a strategy based on unmodified gold nanorods for sensitive and selective detection of arsenic(iii) in contaminated water for the first time. The strategy relies on the inhibitory effect of arsenic(iii) on iron(iii)-mediated oxidative shortening of gold nanorods (Au-NRs) in acidic pH and at increased temperature. The arsenic(iii)-mediated inhibition of Au-NR oxidation is demonstrated by the red-shift of the longitudinal surface plasmon resonance (LSPR) band of Au-NRs. The novelty of our sensing strategy is the fact that it is label-free as it doesn't include any arsenic(iii) selective functionalization of Au-NRs. Moreover, this strategy can detect the arsenic(iii) content in water down to 10 ppb, which is the maximum permissible limit of the arsenic trace in drinking water according to the World Health Organization (WHO) guidelines. The effect of H2O2 in controlling the selectivity of our sensing strategy is investigated. It is found that in the absence of H2O2, the strategy is selective for arsenic(iii) with a broad dynamic response range (10-500 ppb), except for the interference from copper(ii). However, the interference of copper(ii) is efficiently eliminated by selective removal of copper(ii) from water via magnetic separation using polyethyleneimine-functionalized cobalt ferrite nanoparticles. The morphology of Au-NRs and the shift of the LSPR band during the sensing of arsenic(iii) are established by electron microscopy images and Vis-NIR absorption spectroscopy. This strategy is successfully applied for the estimation of arsenic(iii) in the real water sample and this paves the way for the implementation of our strategy for the real-time estimation of arsenic(iii) contamination levels found across prevalent drinking water sources, which are otherwise difficult to achieve with traditional sensors.

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