AI Article Synopsis

  • This study explores the use of single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) to classify titanium-containing nanoparticles as either engineered or naturally occurring by analyzing their elemental composition and mass ratios.
  • The research involved evaluating four types of titanium particles: engineered food-grade TiO particles and naturally occurring particles sourced from minerals like rutile, ilmenite, and biotite.
  • The classification method reported a high accuracy rate with minimal false positives, successfully distinguishing engineered particles in the submicron size range from naturally occurring particles in the nanoregime.

Article Abstract

Titanium-containing nanoparticles (NPs) and submicrometer particles (μPs) in the environment can come from natural or anthropogenic sources. In this study, we investigate the use of single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) to measure and classify individual Ti-containing particles as either engineered (Ti-eng) or naturally occurring (Ti-nat) based on elemental composition and multielement mass ratios. We analyze mixtures of four Ti-containing particle types: anthropogenic food-grade TiO particles and particles from rutile, ilmenite, and biotite mineral samples. Through characterization of neat particle suspensions, we develop a decision-tree-based classification scheme to distinguish Ti-eng from Ti-nat particles and to classify individual Ti-nat particles by mineral type. Engineered TiO and rutile particles have the same major-element composition. To distinguish Ti-eng particles from rutile, we developed particle-type detection limits based on the average crustal abundance ratio of titanium to niobium. For our measurements, the average Ti mass needed to classify Ti-eng particles is 9.3 fg, which corresponds to a diameter of 211 nm for TiO. From neat suspensions, we demonstrate classification rates of 55%, 32%, 75%, and 72% for Ti-eng, rutile, ilmenite, and biotite particles, respectively. Our classification approach minimizes false-positive classifications, with rates below 5% for all particle types. Individual Ti-eng particles can be accurately classified at the submicron size range, while the Ti-nat particles are classified in the nanoregime (diameter < 100 nm). Efficacy of our classification approach is demonstrated through the analysis of controlled mixtures of Ti-eng and Ti-nat and the analysis of natural streamwater spiked with Ti-eng particles. In control mixtures, Ti-eng particles can be measured and classified at particle-number concentrations (PNCs) 60-times lower than that of Ti-nat particles and across a PNC range of at least 3 orders of magnitude. In the streamwater sample, Ti-eng particles are classified at environmentally relevant PNCs that are 44-times lower than the background Ti-nat PNC and 2850-times lower than the total PNC.

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http://dx.doi.org/10.1021/acs.est.3c04473DOI Listing

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Article Synopsis
  • This study explores the use of single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) to classify titanium-containing nanoparticles as either engineered or naturally occurring by analyzing their elemental composition and mass ratios.
  • The research involved evaluating four types of titanium particles: engineered food-grade TiO particles and naturally occurring particles sourced from minerals like rutile, ilmenite, and biotite.
  • The classification method reported a high accuracy rate with minimal false positives, successfully distinguishing engineered particles in the submicron size range from naturally occurring particles in the nanoregime.
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