Particle size distributions by transmission electron microscopy: An interlaboratory comparison case study

Stephen B. Rice, Christopher Chan, Scott C. Brown, Peter Eschbach, Li Han, David S. Ensor, Aleksandr B. Stefaniak, John Bonevich, András E. Vladár, Angela R.Hight Walker, Jiwen Zheng, Catherine Starnes, Arnold Stromberg, Jia Ye, Eric A. Grulke

Research output: Contribution to journalArticlepeer-review

111 Scopus citations


This paper reports an interlaboratory comparison that evaluated a protocol for measuring and analysing the particle size distribution of discrete, metallic, spheroidal nanoparticles using transmission electron microscopy (TEM). The study was focused on automated image capture and automated particle analysis. NIST RM8012 gold nanoparticles (30 nm nominal diameter) were measured for area-equivalent diameter distributions by eight laboratories. Statistical analysis was used to (1) assess the data quality without using size distribution reference models, (2) determine reference model parameters for different size distribution reference models and non-linear regression fitting methods and (3) assess the measurement uncertainty of a size distribution parameter by using its coefficient of variation. The interlaboratory area-equivalent diameter mean, 27.6 nm ± 2.4 nm (computed based on a normal distribution), was quite similar to the area-equivalent diameter, 27.6 nm, assigned to NIST RM8012. The lognormal reference model was the preferred choice for these particle size distributions as, for all laboratories, its parameters had lower relative standard errors (RSEs) than the other size distribution reference models tested (normal, Weibull and Rosin-Rammler-Bennett). The RSEs for the fitted standard deviations were two orders of magnitude higher than those for the fitted means, suggesting that most of the parameter estimate errors were associated with estimating the breadth of the distributions. The coefficients of variation for the interlaboratory statistics also confirmed the lognormal reference model as the preferred choice. From quasi-linear plots, the typical range for good fits between the model and cumulative number-based distributions was 1.9 fitted standard deviations less than the mean to 2.3 fitted standard deviations above the mean. Automated image capture, automated particle analysis and statistical evaluation of the data and fitting coefficients provide a framework for assessing nanoparticle size distributions using TEM for image acquisition.

Original languageEnglish
Pages (from-to)663-678
Number of pages16
Issue number6
StatePublished - Dec 2013

Bibliographical note

Funding Information:
* Corresponding author. E-mail: Foundation item: Supported by State Program of Large Oil and Gas Fields and CBM Development (2008ZX05001-004; 2008ZX05004-001); PetroChina “Stratigraphic Oil and Gas Reservoirs accumulation rules and Exploration Technique Research” Major Program (2008B-0103); PetroChina Technological Innovation Fund (2010D-5006-0104); PetroChina “Large Marine Carbonates Oil and Gas Field Exploration and Production Technique” Major Program (2008E-0706). Copyright © 2011, Research Institute of Petroleum Exploration and Development, PetroChina. Published by Elsevier BV. All rights reserved.

ASJC Scopus subject areas

  • Engineering (all)


Dive into the research topics of 'Particle size distributions by transmission electron microscopy: An interlaboratory comparison case study'. Together they form a unique fingerprint.

Cite this