Literature DB >> 30388437

Comparison between a low-voltage benchtop electron microscope and conventional TEM for number size distribution of nearly spherical shape constituent particles of nanomaterial powders and colloids.

C Dazon1, B Maxit2, O Witschger3.   

Abstract

Nanomaterial powders and colloids are already a large industry and are expected to continue to grow rapidly. In the context of risk assessment associated with nanomaterials, characterization of nanoparticle size and morphology is required. Until now, the best method giving direct access to these parameters has been electron microscopy (EM), in particular, transmission electron microscopy (TEM). Although this method is widely used, several issues are highlighted such as cost, maintenance, sample representativity and damage for sensitive materials. Low-voltage transmission electron microscopes (LVTEMs) could be an alternative approach to solve some of these issues. This paper presents a first comparison between a benchtop LVTEM and a conventional device to determine the number size distribution of the constitutent particles of two polydispersed industrial powders (TiO2 and SiO2) with particle sizes close to 100 nm and two colloids referenced for their particle size (ERM FD 304 and NM 300 K). The samples were prepared with an optimized deposition protocol involving glow discharging and Alcian blue solution pre-treatment on the EM grids. The benchtop LVTEM produced a rather good resolution and the relative differences obtained for the median diameters D50 are generally within ± 15 %. On the basis of these results, benchtop LVTEM could be promoted for identifying nanomaterials within the framework of risk assessment strategy.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Benchtop electron microscope; Colloids; Constituent particles; Nanomaterial classification; Nanomaterials; Powders; Size distribution

Year:  2018        PMID: 30388437     DOI: 10.1016/j.micron.2018.09.007

Source DB:  PubMed          Journal:  Micron        ISSN: 0968-4328            Impact factor:   2.251


  1 in total

1.  Bayesian Particle Instance Segmentation for Electron Microscopy Image Quantification.

Authors:  Batuhan Yildirim; Jacqueline M Cole
Journal:  J Chem Inf Model       Date:  2021-03-08       Impact factor: 4.956

  1 in total

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