Elemental fingerprints in natural nanomaterials determined using SP-ICP-TOF-MS and clustering analysis

Abstract

Detection and quantification of engineered nanomaterials in environmental systems require precise knowledge of the elemental composition, association, and ratios in homologous natural nanomaterials (NNMs). Here, we characterized soil NNMs at the single particle level using single particle-inductively coupled plasma-time of flight-mass spectrometer (SP-ICP-TOF-MS) in order to identify the elemental purity, composition, associations, and ratios within NNMs. Elements naturally present as a major constituent in NNMs such as Ti, and Fe occurred predominantly as pure/single metals, whereas elements naturally present at trace levels in NNMs occurred predominantly as impure/multi-metal NNMs such as V, Nb, Pr, Nd, Sm, Eu, Gd, Tb, Er, Dy, Yb, Lu, Hf, Ta, Pb, Th, and U. Other elements occurred as a mixture of single metal and multi-metal NNMs such as Al, Si, Cr, Mn, Ni, Cu, Zn, Ba, La, Ce, W, and Bi. Thus, elemental purity can be used to differentiate ENMs vs. NNMs only for those elements that occur at trace level in NNMs. We also classified multi-metal NNM into clusters of similar elemental composition and determined their mean elemental composition. Six major clusters accounted for more than 95% of the detected multi-metal NNMs including Al-, Fe-, Ti-, Si-, Ce-, and Zr-rich particles' clusters. The elemental composition of these multi-metal NNM clusters is consistent with naturally occurring minerals. Titanium occurred as a major element (>70% of the total metal mass in NNMs) in Ti-rich cluster and as a minor (<25% of the total metal mass in NNMs) element in likely clay, titanomagnetite, and aluminum oxide phases. Two rare earth element (REE) clusters were identified, characteristic of light REEs and heavy REEs. The findings of this study provide a methodology and baseline information on the elemental composition, associations, and ratios of NNMs, which can be used to differentiate NNMs vs. ENMs in environmental systems.

Keywords: Clustering analysis; Elemental composition and associations; Natural nanomaterials; Single particle-inductively coupled plasma-time of flight-mass spectrometer.