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.
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http://dx.doi.org/10.1016/j.ultramic.2019.112847 | DOI Listing |
Sci Rep
January 2025
Department of Physics, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
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View Article and Find Full Text PDFNanoscale
January 2025
School of Materials and Chemistry, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China.
Thermoplastic polyurethane (TPU) fabrics often possess good mechanical, waterproofing, and breathability properties. However, the resistance of TPU to excessive ultraviolet (UV) irradiation is poor and often does not meet the UV resistance requirements of fabrics. Electrospun nanofibers with a side-by-side structure can combine the advantages of different materials.
View Article and Find Full Text PDFAnalyst
January 2025
Jiangsu Key Laboratory for Carbon-based Functional Materials and Devices, Institute of Functional Nano and Soft Materials (FUNSOM), Soochow University, Suzhou, Jiangsu Province 215123, China.
The choices of matrices and protocols for sample deposition are critical factors, which impact each other in the matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). Previous reports on MALDI MS matrices have only compared their performances in terms of their MS signal intensities and provided optical microphotos or MALDI MS images of sample spots but typically lacked quantitative evaluation. Therefore, there is an urgent need to develop a multivariate model to evaluate the performance of different combinations of matrices and sample protocols.
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January 2025
School of Art and Design, Zhejiang Sci-Tech University, Hangzhou, China.
Urban parks are the primary places where urban residents reconnect with natural environments. Numerous studies have shown that natural landscape features benefit human mental health and promote perceived restoration. However, few studies have explored the extent to which natural landscape features in urban parks can mitigate or compensate for the negative effects of artificial landscape features on emotions and restoration.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Physics, Isfahan University of Technology, Isfahan 84156-83111, Iran.
This paper presents the first-time synthesis of CoFe Co O nanoparticles (where x = 0.0, 0.1, 0.
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