A new method for measuring nanoparticle diameter from a set of SEM images using a remarkable point
Résumé
Scanning Electron Microscopy (SEM) is considered as a reference technique for the determination of nanoparticle (NP) dimensional properties. Nevertheless, the image analysis is a critical step of SEM measuring process and the initial segmentation phase consisting in determining the contour of each nano-object to be measured must be correctly carried out in order to identify all pixels belonging to it. Several techniques can be applied to extract NP from SEM images and evaluate their diameter like thresholding or watershed. However, due to the lack of reference nanomaterials, few papers deals with the uncertainty associated with these segmentation methods. This article proposes a novel approach to extract the NP boundaries from SEM images using a remarkable point. The method is based on the observation that, by varying the electron beam size, the secondary electron profiles crosses each other at this point. First, a theoretical study has been performed using Monte Carlo simulation on silica NP to evaluate the robustness of the method compared with more conventional segmentation techniques (Active Contour or binarization at Full Width at Half-Maximum, FWHM). The simulation results show especially a systematic discrepancy between the NP real size and the measurements performed with both conventional methods. Moreover, generated errors are NP size-dependent. By contrast, it has been demonstrated that a very good agreement between measured and simulated diameters has been obtained with this new technique. As an example, this method of the remarkable point has been applied on SEM images of silica particles. The quality of the segmentation has been shown on silica reference nanoparticles by measuring the modal equivalent projected area diameter and comparing with calibration certificate. The results show that the NP contour can be very accurately delimited with using this point. The measurement uncertainty has been also reduced from 4.3 nm (k = 2) with conventional methods to 2.6 nm (k = 2) using the remarkable point.
Domaines
Mécanique des fluides [physics.class-ph] Matériaux et structures en mécanique [physics.class-ph] Physique Quantique [quant-ph] Acoustique [physics.class-ph] Biomécanique [physics.med-ph] Matériaux Polymères Acoustique [physics.class-ph] Automatique / Robotique Electromagnétisme Milieux fluides et réactifs Energie électrique Thermique [physics.class-ph] Vibrations [physics.class-ph] Physique mathématique [math-ph]
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