The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Nanoparticle Size Detection Limits by Single Particle ICP-MS for 40 Elements
Abstract
The quantification and characterization of natural, 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 matrices. To accurately obtain the nanoparticle size distribution, it is critical to have knowledge of the size detection limit (denoted as Dmin) using spICP-MS for a wide range of elements (other than a few available assessed ones) that have been or will be synthesized 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 Dmin values, greater than 200 nm. A range of parameters that influence the Dmin, 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 Dmin 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 Dmin values. Overall, this work identifies the elements and nanoparticles to which current spICP-MS approaches can be applied, in order to enable quantification of very small nanoparticles at low concentrations in aqueous 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.
Integrity signals
Registry
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.
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
Cites
Nanomaterials in the environment: Behavior, fate, bioavailability, and effects
Klaine, S. J., Alvarez, P. J. J., Batley, G. E., Fernandes, T. F., Handy, R. D., Lyon, D. Y., Mahendra, S., McLaughlin, M. J., & Lead, J. R. (2008) · Environmental Toxicology and Chemistry · doi:10.1897/08-090.1 · Cited by 2,764
Gottschalk, F., Sonderer, T., Scholz, R. W., & Nowack, B. (2009) · Environmental Science & Technology · doi:10.1021/es9015553 · Cited by 2,388
Titanium Dioxide Nanoparticles in Food and Personal Care Products
Weir, A., Westerhoff, P., Fabricius, L., Hristovski, K., & von Goetz, N. (2012) · Environmental Science & Technology · doi:10.1021/es204168d · Cited by 2,161
Self-citationTowards a definition of inorganic nanoparticles from an environmental, health and safety perspective
Auffan, M., Rose, J., Bottero, J.-Y., Lowry, G. V., Jolivet, J.-P., & Wiesner, M. R. (2009) · Nature Nanotechnology · doi:10.1038/nnano.2009.242 · Cited by 1,950
Exposure Modeling of Engineered Nanoparticles in the Environment
Mueller, N. C., & Nowack, B. (2008) · Environmental Science & Technology · doi:10.1021/es7029637 · Cited by 1,828
Nanoparticle Silver Released into Water from Commercially Available Sock Fabrics
Benn, T. M., & Westerhoff, P. (2008) · Environmental Science & Technology · doi:10.1021/es7032718 · Cited by 1,710
Self-citationLongerich, H. P., Jackson, S. E., & Günther, D. (1996) · J. Anal. At. Spectrom. · doi:10.1039/ja9961100899 · Cited by 1,651
Size Dependent and Reactive Oxygen Species Related Nanosilver Toxicity to Nitrifying Bacteria
Choi, O., & Hu, Z. (2008) · Environmental Science & Technology · doi:10.1021/es703238h · Cited by 1,391
Assessing the Risks of Manufactured Nanomaterials
Wiesner, M. R., Lowry, G. V., Alvarez, P., Dionysiou, D., & Biswas, P. (2006) · Environmental Science & Technology · doi:10.1021/es062726m · Cited by 1,160
Pace, H. E., Rogers, N. J., Jarolimek, C., Coleman, V. A., Higgins, C. P., & Ranville, J. F. (2011) · Analytical Chemistry · doi:10.1021/ac201952t · Cited by 816
Self-citation
Cited by
Nanomaterials Versus Ambient Ultrafine Particles: An Opportunity to Exchange Toxicology Knowledge
Stone, V., Miller, M. R., Clift, M. J. D., Elder, A., Mills, N. L., Møller, P., Schins, R. P. F., Vogel, U., Kreyling, W. G., Alstrup Jensen, K., et al. (2017) · Environmental Health Perspectives · doi:10.1289/ehp424 · Cited by 370
Characterization of Nanomaterials
Mudalige, T., Qu, H., Van Haute, D., Ansar, S. M., Paredes, A., & Ingle, T. (2019) · Nanomaterials for Food Applications · doi:10.1016/b978-0-12-814130-4.00011-7 · Cited by 261
Nanoparticle Transport Across the Placental Barrier: Pushing the Field Forward!
Muoth, C., Aengenheister, L., Kucki, M., Wick, P., & Buerki-Thurnherr, T. (2016) · Nanomedicine · doi:10.2217/nnm-2015-0012 · Cited by 146
Hanigan, D., Truong, L., Schoepf, J., Nosaka, T., Mulchandani, A., Tanguay, R. L., & Westerhoff, P. (2018) · Water Research · doi:10.1016/j.watres.2018.03.062 · Cited by 69
Self-citationHandy, R. D., Ahtiainen, J., Navas, J. M., Goss, G., Bleeker, E. A. J., & von der Kammer, F. (2018) · Environmental Science: Nano · doi:10.1039/c7en01139c · Cited by 18
Metadata
- Authors
- Lee, S., Bi, X., Reed, R. B., Ranville, J. F., Herckes, P., & Westerhoff, P.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-08-22
- Volume
- 48
- Issue
- 17
- Pages
- 10291-10300
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W2321195647
- Cited by
- 448
- References
- 46
- FWCI
- 32.13
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Nanoparticle Size Detection Limits by Single Particle ICP-MS for 40 Elements. https://app.cochat.ai/papers/10.1021/es502422v
- The paper
- Lee, S., Bi, X., Reed, R. B., Ranville, J. F., Herckes, P., & Westerhoff, P. (2014). Nanoparticle Size Detection Limits by Single Particle ICP-MS for 40 Elements. Environmental Science & Technology. https://doi.org/10.1021/es502422v
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.