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We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. We compare the segmentation masks obtained with our suggested workflow qualitatively and quantitatively to state-of-the-art methods using various metrics. Finally, we used the segmentation masks for automatically extracting particle size distributions from the SEM images of TiO2 particles, which were in excellent agreement with particle size distributions obtained manually but could be obtained in a fraction of the time.
Transmission electron microscopy study of rapid thermally annealed Pd/Ge contacts on In0.53Ga0.47As
(1996)
Phase formation in rapid thermally annealed Pd/Ge contacts on In0.53Ga0.47As has been investigated by means of cross-sectional transmission electron microscopy, convergent-beam electron diffraction, and energy-dispersive x-ray analysis. Solid-phase regrowth is observed to occur similarly as in Pd/Ge contacts on GaAs or InP. The reaction starts at low temperatures with the formation of an amorphous Pd–In–Ga–As layer, which crystallizes at elevated temperatures yielding hexagonal Pd4In0.53Ga0.47As being first described in this work. At temperatures .250 °C, this phase decomposes due to epitaxial solid-phase regrowth of In0.53Ga0.47As and formation of Pd–Ge phases. The stable composition is reached at temperatures .350 °C with excess Ge diffused through top Pd–Ge to the contact interface and growing epitaxially on the semiconductor.
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.
As part of the development of a library of accurate and efficient methods for measurement of nanoparticle properties, we develop and optimize a method for the efficient analysis of nanoparticle size distribution from suspensions via microprinting and digital analysis of electron microscopy (SEM and TEM) images, with the ultimate aim of automated quantitative concentration analysis (calculated from drop volume). A series of different nanoparticle suspensions (gold, latex, and SiO2 in varying sizes and concentrations) were printed onto TEM grids in a 4 x 4 array in the concentration range 7x10^8 to 1x10^11 nanoparticles/mL and imaged with SEM. Concentrations and printing conditions (temperature, relative humidity) were varied in order to minimize the coffee-ring effect.
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.
BAM is currently building up a platform of novel nanoRMs relying on iron oxide nanoparticles of different shape, size and surface chemistry. Iron oxide was chosen as a core material because of its relevance to the material and life sciences.
As a first candidate of this series, we present cubic iron oxide nanoparticles with a nominal edge length of 8 nm. These particles were synthesized by thermal decomposition of iron oleate in high boiling organic solvents adapting well-known literature procedures. After dilution to a concentration suitable for electron microscopy (TEM and SEM) as well as for small-angle X-ray scattering (SAXS) measurements, the candidate nanoRM was bottled and assessed for homogeneity and stability by both methods following the guidelines of ISO 17034 and ISO Guide 35.
The particle sizes obtained by both STEM-in-SEM and TEM are in excellent agreement with a minimum Feret of 8.3 nm ± 0.7 nm. The aspect ratio (AR) of the iron oxide cubes were extracted from the images as the ratio of minimum Feret to Feret resulting in an AR of 1.18 for TEM to 1.25 for SEM. Alternatively, a rectangular bounding box was fitted originating from the minimum Feret and the longest distance through the particle in perpendicular direction. This led to AR values of 1.05 for TEM and 1.12 for SEM, respectively. The results confirm the almost ideal cubic shape.
Understanding the interaction between boehmite and epoxy and the formation of their interphases with different mechanical and chemical structures is crucial to predict and optimize the properties of epoxy-boehmite nanocomposites. Probing the interfacial properties with atomic force microscopy (AFM)-based methods, especially particle-matrix long-range interactions, is challenging. This is due to size limitations of various analytical methods in resolving nanoparticles and their interphases, the overlap of interphases, and the effect of buried particles that prevent the accurate interphase property measurement. Here, we develop a layered model system in which the epoxy is cured in contact with a thin layer of hydrothermally synthesized boehmite. Different microscopy methods are employed to evaluate the interfacial properties. With intermodulation atomic force microscopy (ImAFM) and amplitude dependence force spectroscopy (ADFS), which contain information about stiffness, electrostatic, and van der Waals forces, a soft interphase was detected between the epoxy and boehmite. Surface potential maps obtained by scanning Kelvin probe microscopy (SKPM) revealed another interphase about one order of magnitude larger than the mechanical interphase. The AFM-infrared spectroscopy (AFM-IR) technique reveals that the soft interphase consists of unreacted curing agent. The long-range electrical interphase is attributed to the chemical alteration of the bulk epoxy and the formation of new absorption bands.
The minimum information requirements needed to guarantee high-quality surface Analysis data of nanomaterials are described with the aim to provide reliable and traceable Information about size, shape, elemental composition and surface chemistry for risk assessment approaches.
The widespread surface analysis methods electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) were considered. The complete analysis sequence from sample preparation, over measurements, to data analysis and data format for reporting and archiving is outlined. All selected methods are used in surface analysis since many years so that many aspects of the analysis (including (meta)data formats) are already standardized. As a practical analysis use case, two coated TiO2 reference nanoparticulate samples, which are available on the Joint Research Centre (JRC) repository, were selected. The added value of the complementary analysis is highlighted based on the minimum information requirements, which are well-defined for the analysis methods selected. The present paper is supposed to serve primarily as a source of understanding of the high standardization level already available for the high-quality data in surface analysis of nanomaterials as reliable input for the nanosafety community.
Understanding the correlation between the morphological and functional properties of particulate materials is crucial across all fields of physical and natural sciences. This manuscript reports on the investigation of the effect of polyethylene glycol (PEG) employed as a capping Agent in the synthesis of SrTiO3 crystals. The crucial influence of PEG on both the shape and size of the strontium titanate particles is revealed, highlighting the effect on the photocurrents measured under
UV–Vis irradiation.
A range of heat treatments have been developed for wrought Inconel 718 to obtain desired properties. For additively manufactured Inconel 718, the recently developed standard ASTM F3301 provides guidance for heat treatment of powder bed fusion specimens. Although this standard is based on standards developed for wrought Inconel 718, it does not include direct aging. Since direct aging reduces the number of processing steps, it can result in a post processing cost reduction if the desired properties are obtained. In this study, we characterized the microstructure and tensile behavior of Inconel 718 specimens produced by a laser powder bed fusion process. The specimens were heat treated according to two different routines after stress relieving: a full heat Treatment versus a one-step direct aging process. Differences in the resulting texture and grain morphology were observed.
The ex-situ stress-strain behavior was broadly similar. However, a slight increase in yield strength was observed for the direct aged specimen. In order to understand this behavior, investigations with in-situ synchrotron Energy dispersive X-ray diffraction tensile testing revealed differences in the load partitioning among different Crystal directions. Importantly, the elastic anisotropy expressed by the magnitude of the diffraction elastic constants showed a dependency on the microstructures.