Classification of zirconium-rich engineered and natural nano particles using single particle ICP-TOFMS

Abstract

Zirconium (Zr) is an important material in the field of ceramics, dentistry, and nuclear energy. It is also present in particulate form in our environment and can come from naturally occurring minerals such as zircon (ZrSiO₄) or from anthropogenic sources such as zirconia (ZrO₂). In this study, we present the detection and classification of Zr-particles at the individual particle level by using single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS). Neat suspensions of engineered zirconia particles (Zr-eng) and natural zircon particles (Zr-nat) were analyzed by spICP-TOFMS, and a decision tree-based classification strategy was developed to distinguish the particle types based on their multi-elemental compositions. In both Zr-eng and Zr-nat particles, the only well-correlated element with Zr was hafnium (Hf), with Zr : Hf mass ratios converging to 47 : 1 and 75 : 1 for Zr-eng and Zr-nat, respectively. The detection of Hf along with Zr is indicative of both Zr-eng and Zr-nat particle types; however, the Zr : Hf mass ratios are too similar to be used to distinguish between individual nano- and sub-micron Zr-eng and Zr-nat particles. Instead, Zr-nat particles can be distinguished from Zr-eng particles based on the detection of minor-elements, such as iron, yttrium, lanthanum, cerium, and thorium, along with Hf in the Zr-nat particles. With our classification scheme, we demonstrate true-positive classification rates of 40% and 80% for Zr-eng and Zr-nat particle types, respectively. False-positive classification of Zr-nat as Zr-eng was below 2%. We validate our classification scheme by classifying the Zr-particles in controlled mixtures of Zr-nat and Zr-eng particles. In these mixtures, Zr-eng particles are classified at particle-number concentrations (PNCs) down to 49-times lower than that of Zr-nat particles and across a PNC range of 3 orders of magnitude.