Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 209

The DOI matches its Crossref record.

Single Particle Inductively Coupled Plasma-Mass Spectrometry: A Performance Evaluation and Method Comparison in the Determination of Nanoparticle Size

Pace, Heather E., Rogers, Nicola J., Jarolimek, Chad, Coleman, Victoria A., Gray, Evan P., Higgins, Christopher P., Ranville, James F.·2012·Environmental Science & Technology

Abstract

Sizing engineered nanoparticles in simple, laboratory systems is now a robust field of science; however, application of available techniques to more complex, natural systems is hindered by numerous challenges including low nanoparticle number concentrations, polydispersity from aggregation and/or dissolution, and interference from other incidental particulates. A new emerging technique, single particle inductively coupled plasma-mass spectrometry (spICPMS), has the potential to address many of these analytical challenges when sizing inorganic nanoparticles in environmental matrices. However, to date, there is little beyond the initial feasibility studies that investigates the performance characteristics and validation of spICPMS as a nanoparticle sizing technique. This study compares sizing of four silver nanoparticle dispersions (nominal diameters of 40, 60, 80, and 100 nm) by spICPMS to four established sizing techniques: dynamic light scattering, differential centrifugal sedimentation, nanoparticle tracking analysis, and TEM. Results show that spICPMS is able to size silver nanoparticles, across different sizes and particle number concentrations, with accuracy similar to the other commercially available techniques. Furthermore, a novel approach to evaluating particle coincidence is presented. In addition, spICPMS size measurements were successfully performed on nanoparticles suspended in algal growth media at low concentrations. Overall, while further development of the technique is needed, spICPMS yields important advantages over other techniques when sizing nanoparticles in environmentally relevant media.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/es301787d

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

Metadata

Authors
Pace, H. E., Rogers, N. J., Jarolimek, C., Coleman, V. A., Gray, E. P., Higgins, C. P., & Ranville, J. F.
Venue
Environmental Science & Technology
Published
2012-07-30
Volume
46
Issue
22
Pages
12272-12280
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2333926292
Cited by
209
References
0
FWCI
13.89
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.