Cloud point extraction hyphenated to single-particle ICP-MS minimizes background signals and improves particle size detection limit for ultra trace analysis of nanoparticulate rhodium. Issue 10 (21st September 2022)

• Record Type: Journal Article
• Authors: Weigl, Florian; Schuster, Michael
• Is Part Of: Journal of analytical atomic spectrometry. Volume 37:Issue 10(2022)
• Page Start: 2182
• Page End: 2189
• Publication Date: 2022-09-21
• Subjects: Atomic spectra -- Periodicals; Atomic absorption spectroscopy -- Periodicals; 543.0858
• DOI: 10.1039/d2ja00068g
• Languages: English
• ISSNs: 0267-9477

Abstract

Abstract : Cloud point extraction eliminates the background signal in inductively coupled plasma mass spectrometry (spICP-MS) analysis improving particle counting accuracy, particle mass quantification, and particle size determination. Abstract : The lack of adequate methods to remove background signals in single-particle inductively coupled plasma mass spectrometry (spICP-MS) is hindering the use of this analytical technique for the determination and characterization of metal-based nanoparticles in environmental samples. The high levels of dissolved species in environmental samples generate a background signal in spICP-MS analysis that overlaps with the signal from small nanoparticles, which leads to an incomplete size distribution and an underestimation of the particle concentration. In this study, we propose an analytical platform, which eliminates the ionic background signal by coupling cloud point extraction (CPE) with spICP-MS (CPE–spICP-MS) in the case of rhodium. Therefore, we have developed, verified, and validated CPE of rhodium nanoparticles (RhNPs) and coupled it to a spICP-MS system. This allows the accurate determination of RhNPs with a size detection limit of 9 nm, even in the presence of high levels of dissolved rhodium (RhNP/Rh III : 1/1–1/1000). We show systematically how this analytical method improves the resolution of the particle signal to the signal of dissolved species, which in turn improves the accuracy of particle count, quantification of particulate mass, and the determination of particle size. Finally, the method is applied to study RhNPs in urban road dust originating from car exhaust catalysts. The technique proposed here offers a reliable, simple, and effective analytical platform for the analysis of metal-based nanoparticles in environmental samples by coupling two well-studied analytical tools: CPE with spICP-MS.