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In the present paper we show an approach of measuring large numbers of nanoparticles in a single scan TKD. TiO2 anatase nanoparticles (NP) of bipyramidal shape were deposited on standard carbon grid used for TEM. The procedure used promoted formation of NP ‘monolayer’ islands with uniform distribution of NPs on the carbon surface which allowed mapping of large number of nanoparticles in the single island.
Collection of whole map covering ~2800 nanoparticles took nearly 20 minutes. Inverse pole figure color coded map indicates that the NPs are either lying on a {101} facet (within 10° range around perfect {101} parallel to the carbon surface orientation) on the carbon film or are lying on a {100} facet (within 10° range around the perfect {100} parallel to the carbon surface orientation). Very unlikely was the NP orientation standing on a {001} face. The NPs size distribution described as equivalent circle diameter (ECD) has been also evaluated and the mean NP ECD was 59 nm with standard deviation of 15 nm, i.e. in good agreement with electron microscopy or AFM results.
This study shows high potential of the technique for crystalline NPs analysis with respect to geometrical orientation of the particles on the substrate. With known orientation, the 3D dimensional characterisation of such non-spherical NPs becomes possible from 2D projection electron micrographs. Moreover, the NP size distribution can be easily extracted. Superior accuracies down to 1-2 nm are achievable. The approach is applicable also on thin lamellae extracted from particulate (or mesoporous) layers.
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.