ArticleAnalytical science advances2022
Toward a greener approach to detect inorganic arsenic using the Gutzeit method and X-ray fluorescence spectroscopy.
Article in Analytical science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Colorimetric Detection of Arsenic (III) and Mercury (II) Ions in Human Serum Albumin Samples Using Cysteine-Capped Gold Nanoparticles.Sensors (Basel, Switzerland) · 2026Article
- Affordable Arsenic Detection Device Using Handmade Lokta Paper for Decentralized and Sustainable Manufacturing.Journal of analytical methods in chemistry · 2026Article
- Role of the Sn-TiOACS applied materials & interfaces · 2024Article
- Toward a greener approach to detect inorganic arsenic using the Gutzeit method and X-ray fluorescence spectroscopy.Analytical science advances · 2022Article
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3 authors.
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Abstract
Inorganic arsenic is a carcinogen repeatedly found in water and foods threatening global human health. Prior work applied the Gutzeit method and X-ray fluorescence spectroscopy to quantify inorganic arsenic based on a harmful chemical, i.e., mercury bromide, to capture the arsine gas. In this project, we explored silver nitrate as an alternative to mercury bromide for the capture and detection of inorganic arsenic. To compare the performance of mercury bromide and silver nitrate, two standard curves were established in the range from 0 to 33.3 µg/L after optimization of reaction conditions such as the quantity of reagents and reaction time. Our result shows silver nitrate-based standard curve had a lower limit of detection and limit of quantification at 1.02 µg/L and 3.40 µg/L, respectively, as compared to the one built upon mercury bromide that has limit of detection of 4.86 µg/L and limit of quantification of 16.2 µg/L. The relative higher sensitivity when using silver nitrate was contributed by the less interfering elements for X-ray fluorescence analysis and thus lower background signals. A commercial apple juice was studied for matrix inference, and the results show 85%-99% recoveries and 7.4%-24.5% relative standard deviation. In conclusion, we demonstrated silver nitrate is a better choice in terms of safety restrictions and detection capability at lower inorganic arsenic concentrations.
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