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The image designed by Natalia Cano Murillo and colleagues shows the cross section of a ternary composite (boehmite/polycarbonate/epoxy, 80μm x 80μm). The surface was measured by AFM kelvin probe microscopy, yielding the surface potential which is shown as 3D‐surface and contour lines. The sample was further subjected to AFM force spectroscopy with a lateral resolution of 1μm², yielding the local Young's modulus, projected in false colors on the 3D surface. The ternary system, containing boehmite nanoparticles, shows a broad distribution of modulus, desirable for optimized macroscopic mechanical properties, such as high stiffness as well as toughness.
This chapter provides an overview of what standards are, why they are important, and how they are developed. There is a focus on the work of standards committees relevant to nanotechnology measurement and characterization with tables detailing the standards that are currently available for a large number of different techniques, materials, and applications at the nanoscale.
This document is a collection of three JRC Technical Reports that together form the “NanoDefine Methods Manual”, which has been developed within the NanoDefine project ‘Development of an integrated approach based on validated and standardized methods to support the implementation of the EC recommendation for a definition of nanomaterial’, funded by the European Union’s 7th Framework Programme, under grant agreement 604347. The overall goal of the NanoDefine project was to support the implementation of the European Commission Recommendation on the definition of nanomaterial (2011/696/EU). The project has developed an integrated empirical approach, which allows identifying a material as a nano- or not a nanomaterial according to the EC Recommendation. The NanoDefine Methods Manual consists of three parts: Part 1: The NanoDefiner Framework and Tools, which covers the NanoDefiner framework, general information on measurement methods and performance criteria, and tools developed by NanoDefine such as a materials categorisation system, a decision support flow scheme and an e-tool. Part 2: Evaluation of Methods, which discusses the outcome of the evaluation of the nanomaterials characterisation methods for measuring size. Part 3: Standard Operating Procedures (SOPs), which presents the 23 Standard Operating Procedures developed within the NanoDefine project. In this combined document, these three parts are included as stand-alone reports, each having its own abstract, table of contents, page, table and figure numbering, and references.
This chapter first gives an introduction to the concepts of SSA and volume-specific surface area (VSSA) and an outline of the BET method. It continues with a discussion of the relationship between particle size, shape, and the VSSA, followed by an overview of instrumentation, experimental methods, and standards. Finally, sections on the use of the VSSA as a tool to identify nanomaterials and non-nanomaterials and its role in a regulatory context provide some insight on the importance of VSSA in the current Regulation of nanomaterials.
Gold nanocubes with a monodispersed size distribution (edge = 55 nm) deposited on a silicon wafer. These tiny uniform cubes were produced as reference nanoparticles in the frame of the European project nPSize - Improved traceability chain of nanoparticle size measurements. SEM Image acquired at 10 kV with an in-lens secondary electron detector. Image colored in ImageJ using LUT “Orange hot.” Published in Microscopy and Microanalysis 25(S2) (2019) 2328.
Gold nanocubes with a monodispersed size distribution (edge = 55 nm) deposited on a silicon wafer. These tiny uniform cubes were produced as reference nanoparticles within the EMPIR project nPSize - Improved traceability chain of nanoparticle size measurements. SEM image acquired at 10 kV with an in-lens secondary electron detector. Image colored in ImageJ using LUT “Orange hot.” Published in Microscopy and Microanalysis 25(S2) (2019) 2328.
The progress in activities on Microbeam Analysis under VAMAS/TWA 37 is reviewed. Particularly the liaison with the new projects within the ISO technical committee TC 202 is presented and discussed with respect to the possibility of identifying and launching related VAMAS projects. Need of more promotion for the engagement of more participants from industry and academia at national, European and international level is highlighted. Also, the competition with the other technical working areas (on 'nano' or materials-related) is critically discussed.
The present study addresses the capability of measurement of relative particle number concentration by scanning electron microscopy for model bimodal silica and gold samples prepared in the frame of the European research project “nPSize - Improved traceability chain of nanoparticle size measurements” as candidate reference nanoparticles.
In this paper one refined approach is applied to determine the exact orientation of bipyramidal TiO2 nanoparticles prepared with good dispersion as almost isolated particles on a carbon TEM grid. The advantages of the recently developed high-throughput Transmission Kikuchi Diffraction (TKD) are used to identify quickly and reliably the geometrical orientation of the crystalline TiO2 nanoparticle bipyramids (anatase) on a statistically relevant number of particles.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.