Overcoming challenges in single particle inductively coupled plasma mass spectrometry measurement of silver nanoparticles

Abstract

Single particle ICP-MS has evolved rapidly as a quantitative method for determining nanoparticle size and number concentration at environmentally relevant exposure levels. Central to the application of spICP-MS is a commonly used, but not rigorously validated, calibration approach based on the measured transport efficiency and the response of ionic standards. In this work, we present a comprehensive and systematic study of the accuracy, precision and robustness of spICP-MS using the rigorously characterized reference material (RM) 8017 (Polyvinylpyrrolidone Coated Nominal 75 nm Silver Nanoparticles), recently issued by the National Institute of Standards and Technology (NIST). We report for the first time, statistically significant differences in frequency-based and size-based measures of transport efficiency with NIST RM 8013 Gold Nanoparticles and demonstrate that the size-based measure of transport efficiency is more robust and yields accurate results for the silver nanoparticle RM relative to TEM-based reference values. This finding is significant, because the frequency-based method is more widely applied. Furthermore, we demonstrate that the use of acidified ionic standards improves measurement of ICP-MS Ag response, but does not degrade the accuracy of the results for AgNP suspensions in water or various other diluents. Approaches for controlling AgNP dissolution were investigated and are shown to effectively improve particle stability in dilute suspensions required for spICP-MS analysis, while minimally affecting the measured intensity and allowing for more robust analysis. This study is an important and necessary advancement toward full validation and adoption of spICP-MS by the broader research community.

Characterisation of Engineered Nanomaterials in Nano-Enabled Products Exhibiting Priority Environmental Exposure

“…Furthermore, it is challenging to obtain consistent/reproducible measurements of size, size distribution, and the number of particle concentration using spICP-MS [ 49 ]. Nonetheless, spICP-MS is a promising technique that can rapidly provide comprehensive physico-chemical properties data of ENMs (i.e., particle concentration, size distribution, apparent core density, and state of aggregation) [ 47 , 50 , 51 ].…”

Single-particle ICP-TOFMS with online microdroplet calibration for the simultaneous quantification of diverse nanoparticles in complex matrices

“…† The median sizes value obtained from SEM are in agreement with the manufacturer data but the standard deviation for our measurement is high due to the relatively small sample size: only ∼100 particles per SEM size distribution. Furthermore, silver NPs-which are sensitive particle to light 21 -show a wider distribution tail toward smaller NP diameter; this is evidence for degradation of the NPs (see Fig. S5e †).…”

“…sensitivity) are determined. [19][20][21] Depending on the NP-containing matrix, both transport efficiency and/or elemental sensitivity may change and cause inaccurate calibration of PNC or element mass. 22 In the context of environmental analysis, temporally and spatially variable matrix characteristics, such as dissolved organic content, total salt content, or pH, could impact the accuracy of sp-ICP-MS analysis.…”

Detection of nanoparticles in edible plant tissues exposed to nano-copper using single-particle ICP-MS

“…Laborda et al present a very detailed explanation of the principles and key considerations for successful sp-ICP-MS (Laborda et al 2013(Laborda et al , 2016. Earlier studies discussed a number of challenges even for the measurement of very well-defined NPs in simple aqueous matrices (Liu et al 2017;Mitrano et al 2012Mitrano et al , 2014Reed et al 2012), but more recent work indicates that this technique is becoming more common for aqueous samples (Montano et al 2016). As the technique has matured, it has been applied to a wider range of elemental compositions (Frechette-Viens et al 2017;Lee et al 2014;Praetorius et al 2017) and samples (Azodi et al 2016;Hadioui et al 2015;Schwertfeger et al 2016).…”