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The quantification and characterization of natural, 1000 engineered, and incidental nano- to micro-size particles are beneficial to assessing a nanomaterial's performance in manufacturing, their fate and transport in the environment, and their potential risk to human health. Single particle inductively coupled plasma mass spectrometry (spICP-MS) can sensitively quantify the amount ? and size distribution of metallic nanoparticles suspended in aqueous Dmin matrices. To accurately obtain the nanoparticle size distribution, it is critical to have knowledge of the size detection limit (denoted as Dminusing spICP-MS for a wide range of elements (other than a few available assessed ones) that have been or will be synthesized 10 into engineered nanoparticles. Herein is described a method to estimate the size detection limit using spICP-MS and then apply it to nanoparticles composed of 40 different elements. The calculated Dmin values correspond well for a few of the elements with their detectable sizes that are available in the literature. Assuming each nanoparticle sample is composed of one element, Dmin values vary substantially among the 40 elements: Ta, U, Ir, Rh, Th, Ce, and Hf showed the lowest Dmin values, ⩽10 nm; Bi, W, In, Pb, Pt, Ag, Au, Tl, Pd, Y, Ru, Cd, and Sb had Dmin in the range of 11-20 nm; Dmin values of Co, Sr, Sn, Zr, Ba, Te, Mo, Ni, V, Cu, Cr, Mg, Zn, Fe, Al, Li, and Ti were located at 21-80 nm; and Se, Ca, and Si showed high Dmjn values, greater than 200 nm. A range of parameters that influence the Dmjn, such as instrument sensitivity, nanoparticle density, and background noise, is demonstrated. It is observed that, when the background noise is low, the instrument sensitivity and nanoparticle density dominate the significantly. Approaches for reducing the Dmin, e.g., collision cell technology (CCT) and analyte isotope selection, are also discussed. To validate the Dmin estimation approach, size distributions for three engineered nanoparticle samples were obtained using spICP-MS. The use of this methodology confirms that the observed minimum detectable sizes are consistent with the calculated Dminvalues. Overall, this work identifies the elements and nanoparticles to which current spICPMS approaches can be applied, in order to enable quantification of very small nanoparticles at low concentrations in aqueous media. [ABSTRACT FROM AUTHOR]

Sensitive and accurate characterization of nanoparticle size in aqueousmatrices at environmentally relevant concentrations is still challenging for current nano-analysis techniques. Single particle inductively coupled plasma mass spectrometry (spICP-MS) is an emerging method to characterize the size distribution of nanoparticles and determine their concentrations. Herein for the first time the K-means clustering algorithm is applied to signal processing of spICP-MS raw data. Compared with currently used data processing approaches, the K-means algorithm improved discrimination of particle signals from background signals and provides a sophisticated, statistically based method to quantitatively resolve different size groups contained within a nanoparticle suspension. In tests with commercial Au nanoparticles (AuNPs), spICP-MS with the K-means clustering algorithm can quantitatively discriminate secondary "impurity-size nanoparticles," present at fractions of less than 2% by mass, from primary-size nanoparticles with the minimum resolvable size difference between the primary and secondary nanoparticles at ~20 nm. AuNP mixtures in which 80 nm particles act as the "primary size group" and 20 nm, 50 nm, or 100 nm particles act as the "impurity size group" were analyzed by spICP-MS, which reliably measured percentages of secondary impurity-size nanoparticles that are consistent with the expected experimentally determined values. Compared with dynamic light scattering (DLS), spICP-MS has remarkably better particle size resolution capability. We also demonstrated the size measurement advantage of spICP-MS over DLS for commercial CeO2 nanoparticles that are commonly used in the semiconductor industry, where quality control of the nanoparticle size distribution is critical for the wafer polishing process. [ABSTRACT FROM AUTHOR]

Titanium dioxide (TiO2) is widely used in food products, which will eventually enter wastewater treatment plants and terrestrial or aquatic environments, yet little is known about the fraction of this TiO2 that is nanoscale, or the physical and chemical properties of TiO2 that influence its human and environmental fate or toxicity. Instead of analyzing TiO2 properties in complex food or environmental samples, we procured samples of food-grade TiO2 obtained from global food suppliers and then, using spectroscopic and other analytical techniques, quantified several parameters (elemental composition, crystal structure, size, and surface composition) that are reported to influence environmental fate and toxicity. Another sample of nano-TiO2 that is generally sold for catalytic applications (P25) and widely used in toxicity studies, was analyzed for comparison. Food-grade and P25 TiO2 are engineered products, frequently synthesized from purified titanium precursors, and not milled from bulk scale minerals. Nanosized materials were present in all of the food-grade TiO2 samples, and transmission electron microscopy showed that samples 1-5 contained 35, 23, 21, 17, and 19% of nanosized primary particles (<100 nm in diameter) by number, respectively (all primary P25 particles were <100 nm in diameter). Both types of TiO2 aggregated in water with an average hydrodynamic diameter of >100 nm. Food-grade samples contained phosphorus (P), with concentrations ranging from 0.5 to 1.8 mg of P/g of TiO2. The phosphorus content of P25 was below inductively coupled plasma mass spectrometry detection limits. Presumably because of a P-based coating detected by X-ray photoelectron spectroscopy, the ζ potential of the food-grade TiO2 suspension in deionized water ranged from -10 to -45 mV around pH 7, and the iso-electric point for food-grade TiO2 (