Thomas Slater

Spectroscopic signals such as EDS and EELS provide an effective way of characterising multi-element samples such as Pt-Co nanoparticles in STEM. The advantage of spectroscopy over imaging is the ability to decouple composition and mass-thickness effects for thin samples, into the number of various types of atoms in a sample. This is currently not possible for multi element samples using conventional ADF quantification techniques alone. With recent developments in microscope hardware and software, it is now possible to acquire the ADF, EDS and EELS signals simultaneously and at high speed. However, the methods of quantifying the signals emitted from the sample vary greatly. Most approaches use pure-element standards in the form of needles, nanoparticles and wedges to quantify the spectroscopic signal into either partial scattering cross-sections, zeta-factors or k-factors. But self-consistency between the different methods has not been verified and the units of the quantification are not standardised. We present a robust approach for measuring and combining ADF, EDS and EELS signals using needle and nanoparticle standards in units of the partial scattering cross-section. The partial scattering cross-section allows an easy interpretation of the signals emitted from the sample and enables accurate atom-counting of the sample.

Transmission electron microscopy (TEM) represents a unique and powerful modality for capturing spatial features of nanoparticles, such as size and shape. However, poor statistics arise as a key obstacle, due to the challenge in accurately and automatically segmenting nanoparticles in TEM micrographs. Towards remedying this deficit, we introduce an automatic particle picking device that is based on the concept of variance hybridized mean local thresholding. Validation of this new segmentation model is accomplished by applying a program written in Matlab to a database of 150 bright field TEM micrographs containing approximately 2,000 nanoparticles. We compare the results to global thresholding, local thresholding, and manual segmentation. It is found that this novel automatic particle picking device reduces false positives and false negatives significantly, while increasing the number of individual particles picked on regions of particle overlap.

In this paper, we propose an algorithm to obtain a three-dimensional reconstruction of a single nanoparticle based on the method of atom counting. The location of atoms in three dimensions has been successfully performed using simulations of high-angle-annular-dark-field images from only three zone-axis projections, [110], [310] and [211], for a face-centred cubic particle. These three orientations are typically accessible by low-tilt holders often used in high-performance scanning transmission electron microscopes.

Looking at objects and being able to count the atoms constituting it is a challenging task for materials scientists. Electron microscopists are now using scanning transmission electron microscopes (STEM) of outstanding capabilities and have developed statistical methods allowing atom counting in nano-objects from their 2D-projections. However, retrieving the 3D morphology of an object from few projections is not a trivial issue. This is even more difficult when the microscope configuration does not allow projecting the nano-object along very distinct orientations. Such an approach, designated as “discrete tomography”, has demonstrated very strong capabilities in the last 5 years. Nevertheless, no detailed reconstruction algorithm has ever been published for discrete tomography performed in STEM. In addition, no study has been published which actually demonstrates the accuracy of the method based on its application to simulated data. In the present work, we present the details of a discrete tomography reconstruction algorithm which is applied to simulated projections of a nanoparticle. The choice of the projection angles has been done to reproduce the unfavorable conditions encountered in many STEM instruments, for which large specimen tilt capabilities are not accessible. Based on three close projections, it is demonstrated that a very satisfying and faithful reconstruction of the nanoparticle can be reached.

A sample of a nanomaterial contains a distribution of nanoparticles of various shapes and/or sizes. A scanning electron microscopy image of such a sample often captures only a fragment of the morphological variety present in the sample. In order to quantitatively analyse the sample using scanning electron microscope digital images, and, in particular, to derive numerical representations of the sample morphology, image content has to be assessed. In this work, we present a framework for extracting morphological information contained in scanning electron microscopy images using computer vision algorithms, and for converting them into numerical particle descriptors. We explore the concept of image representativeness and provide a set of protocols for selecting optimal scanning electron microscopy images as well as determining the smallest representative image set for each of the morphological features. We demonstrate the practical aspects of our methodology by investigating tricalcium phosphate, Ca₃(PO₄)₂, and calcium hydroxyphosphate, Ca₅(PO₄)₃(OH), both naturally occurring minerals with a wide range of biomedical applications.

A typical sample of a nanomaterial contains a distribution of nanoparticles of various shapes and/or sizes. A single scanning electron microscopy (SEM) image of such a sample often captures only a fragment of the sample, and therefore only a fragment of the morphological variety present in the sample. In order to obtain more complete information about the "true" sample morphology, one needs to asses the content of a series of SEM images. In our article, we present a framework for extracting morphological information contained in SEM images using computer vision algorithms, and for converting them into numerical particle descriptors representing the particle morphology. We then explore the concept of image representativeness and provide a set of protocols for selecting optimal SEM images as well as determining the smallest representative image set for each of the morphological features. We demonstrate the practical aspects of our methodology by investigating SEM images of a tricalcium phosphate sample, a naturally occurring mineral with a wide range of biomedical applications.

The aim of the this study is improvement of qualitative and quantitative analysis of scanning electron microscope micrographs by development of computer program, which enables automatic crack analysis of scanning electron microscopy (SEM) micrographs. Micromechanical tests of pneumatic ventricular assist devices result in a large number of micrographs. Therefore, the analysis must be automatic. Tests for athrombogenic titanium nitride/gold coatings deposited on polymeric substrates (Bionate II) are performed. These tests include microshear, microtension and fatigue analysis. Anisotropic surface defects observed in the SEM micrographs require support for qualitative and quantitative interpretation. Improvement of qualitative analysis of scanning electron microscope images was achieved by a set of computational tools that includes binarization, simplified expanding, expanding, simple image statistic thresholding, the filters Laplacian 1, and Laplacian 2, Otsu and reverse binarization. Several modifications of the known image processing techniques and combinations of the selected image processing techniques were applied. The introduced quantitative analysis of digital scanning electron microscope images enables computation of stereological parameters such as area, crack angle, crack length, and total crack length per unit area. This study also compares the functionality of the developed computer program of digital image processing with existing applications. The described pre- and postprocessing may be helpful in scanning electron microscopy and transmission electron microscopy surface investigations.

Micrographs of scanning electron microscopy obtained from micromechanical tests performed for athrombogenic titanium nitride/gold coatings deposited on polymeric substrates applied in pneumatic ventricular assist devices are present in large numbers due to a multistage character of the micromechanical testing. Anisotropic surface defects observed in the SEM micrographs require support for qualitative and quantitative interpretation. Improvement of qualitative analysis of scanning electron microscope results was proposed by a computer program for image processing, which uses image processing algorithms. Authors proposed several modifications of the known image processing techniques and also applied combinations of the selected image processing techniques. Introduced quantitative analysis of digital scanning electron microscope results enables computation of the selected stereological parameters. The study also compares the functionality of developed computer program of digital image processing with existing applications.

Gallium-based focused ion beams generated from liquid–metal sources are widely used in micromachining and sample preparation for transmission electron microscopy, with well-known drawbacks such as sample damage and contamination. In this work, an alternative (neon) focused ion beam generated by a gas field-ionization source is evaluated for the preparation of electron-transparent specimens. To do so, electron-transparent sections of Si and an Al alloy are prepared with both Ga and Ne ion beams for direct comparison. Diffraction-contrast imaging and energy dispersive x-ray spectroscopy are used to evaluate the relative damage induced by the two beams, and cross-sections of milled trenches are examined to compare the implantation depth with theoretical predictions from Monte Carlo simulations. Our results show that for the beam voltages and materials systems investigated, Ne ion beam milling does not significantly reduce the focused ion beam induced artefacts. However, the Ne ion beam does enable more precise milling and may be of interest in cases where Ga contamination cannot be tolerated.

Transmission electron microscopy (TEM) is an extremely powerful tool used to examine the smallest objects imaginable, down to single atoms. This is increasingly relevant in many fields, such as semiconductor devices, which are always shrinking, and materials science, where nanostructure materials offer unique properties not previously achievable. TEM analysis relies on an extremely thin sample, often thinner than 100 nm, and producing a representative sample without artefacts from the sample preparation itself is often a concern. One of the most useful techniques in obtaining a thin sample is gallium focused ion beam machining, analogous to controlled sand blasting, but using gallium ions instead of sand particles. The beam of ions used can be manipulated to intensely remove material from a spot, or a large area by rastering the beam across the defined pattern. With careful application of the focused ion beam, extremely thin samples suitable for TEM can be made from site-specific areas from heterogeneous samples. In this paper, a new ion species (neon) is examined for its suitability in ion milling. This ion beam removes material more slowly, but can offer better resolution and control of the milling pattern. Several experiments were performed to evaluate the efficacy of this new method, with the conclusion that it produces similar artefacts, but can be an alternative to gallium-based milling in situations that require it, which include samples that are contaminated by gallium, or when extremely high precision milling is required.

When producing asphalt concrete mixture with high amounts of reclaimed asphalt pavement (RAP), the mixing temperature plays a significant role in the resulting spatial distribution of the components as well as on the quality of the resulting mixture, in terms of workability during mixing and compaction as well as in service mechanical properties. Asphalt concrete containing 50% RAP was investigated at mixing temperatures of 140, 160 and 180°C, using a multiscale approach. At the microscale, using energy dispersive X-ray spectroscopy the RAP binder film thickness was visualized and measured. It was shown that at higher mixing temperatures this film thickness was reduced. The reduction in film thickness can be attributed to the loss of volatiles as well as the mixing of RAP binder with virgin binder at higher temperatures. X-ray computer tomography was used to characterize statistically the distribution of the RAP and virgin aggregates geometric features: volume, width and shape anisotropy. In addition using X-ray computer tomography, the packing and spatial distribution of the RAP and virgin aggregates was characterized using the nearest neighbour metric. It was shown that mixing temperature may have a positive effect on the spatial distribution of the aggregates but did not affect the packing. The study shows a tendency for the RAP aggregates to be more likely distributed in clusters at lower mixing temperatures. At higher temperatures, they were more homogeneously distributed. This indicates a higher degree of blending both at microscale (binder film) and macroscale (spatial distribution) between RAP and virgin aggregates as a result of increasing mixing temperatures and the ability to quantify this using various imaging techniques.

Recycling of asphalt concrete is a result of combining reclaimed asphalt pavement (RAP) with virgin aggregates and virgin binder. The mixing temperature of RAPand virgin materials and the resulting distribution of the components have a significant effect on the quality of the mixture. In this study, asphalt concrete containing 50% RAP was investigated at mixing temperatures of 140, 160 and 180°C, using a multiscale approach. At the microscale the RAP binder film thickness was visualized and measured. It was shown that at higher mixing temperatures this film thickness was reduced. The reduction in film thickness can be attributed to the loss of volatiles as well as the mixing of RAP binder with virgin binder at higher temperatures. X-Ray computer tomography was used to characterize the RAP and virgin aggregates’ geometric features: volume, width and shape anisotropy. In addition using X-ray computer tomography, the packing and spatial distribution of the RAP and virgin aggregates was characterized. It was shown that mixing temperature had a positive effect on the spatial distribution of the aggregates but did not affect the packing. The study shows a tendency for the RAP aggregates to be more likely grouped into clusters at lower mixing temperatures. At higher temperatures, they were more homogeneously distributed. This result indicates a higher degree of blending both at microscale (binder film) and macro scale (spatial distribution) between RAP and virgin aggregates as a result of increasing mixing temperatures and the ability to quantify this using various imaging techniques.