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Zielsetzung des vom Bundesministerium für Bildung und Forschung geförderten Projektes RUSEKU war es, repräsentative Untersuchungsstrategien für die Detektion von Mikroplastik mittels TED GC/MS in wässerigen Medien zu ermitteln. Dabei wurden verschiedene Probenahmekonzepte und – verfahren für unterschiedliche Fallgestaltungen und Fragestellungen untersucht, sowie neue Filtersysteme entwickelt. Bei der Detektion der Partikel lag der Fokus auf der Anwendung und Weiterentwicklung der ThermoExtraktion/Desorption-Gaschromatographie-Massenspektrometrie (TED-GC/MS) zur Bestimmung von Mikroplastikgehalten. Anwendung fanden die Methoden bei der Beprobung von Flaschenwasser, Waschmaschinenabläufen, dem urbanen Abwassersystem der Stadt Kaiserslautern, sowie in Oberflächengewässer.
Secondary fluorescence is an inevitable effect that has to be taken into account in any algorithm for quantitative electron probe microanalysis (EPMA) as an additional correction. Moreover, secondary fluorescence worsens spatial resolution of EPMA. Secondary fluorescence is excited both by characteristic radiation and by the X-ray continuum. In most cases the correction is small. There are, however, cases, e.g. the determination of low heavy metal concentration in a light matrix, where the contribution of secondary fluorescence exceeds 10% of the measured X-ray line intensity.
For secondary fluorescence correction the measured X-ray line intensity has to be divided by the correction factor (1+I_flchar/I_p +I_flcont/I_p )≈(1+I_flchar/I_p )(1+I_flcont/I_p ) in order to get those intensity I_p, which is excited only by the primary electrons. I_flchar and I_flcont mean the calculated characteristic and continuums fluorescence intensities. In order to get the intensity of fluorescence radiation, the absorption of the exciting radiation in the specimen, the photoionization probability and the self-absorption of the emitted line must be calculated. The critical quantity is the X-ray yield of the exciting atoms in case of fluorescence by characteristic radiation and the bremsstrahlung yield of the specimen in case of continuum fluorescence. In the former case it is reasonable to apply the same physical model to calculate I_flchar and I_p.
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.
Most industrial nanoparticles have non-spherical shapes and also possess polydisperse size distributions, and due to their agglomeration/ aggregation state are difficult (or even impossible) to be addressed individually. Further, driven by regulatory purposes related to the identification of a material as a nanomaterial, the accurate measurement of the smallest dimension of a (nano)particulate material makes the analysis even more complex.
In the first phase of the EU Project nPSize - Improved traceability chain of nanoparticle size measurements (https://www.bam.de/Content/DE/Projekte/laufend/nPSize/npsize.html), the efforts are focused on synthesis of nanoparticles of well-defined, non-spherical shape. Following candidates of reference materials (CRM) with certifiable particle size (distribution) are under characterization with respect to their homogeneity and stability: (i) titania nanoplatelets (10-15 nm thickness x 50-60 nm lateral), (ii) titania bipyramides (~60 nm length x 40 nm width), (iii) titania acicular particles (100 nm length x 15-20 nm width; aspect ratio 5.5/6), (iv) gold nanorods (~10 nm width x 30 nm length), and (v) gold nanocubes (~55 nm x 55 nm x 55 nm).
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.
This paper reports a systematic study into the effect of different biomass-derived precursors on the structure and porosity of carbons prepared via catalytic graphitization. Glucose, starch and cellulose are combined with iron nitrate and heated under a nitrogen atmosphere to produce Fe3C nanoparticles, which catalyze the conversion of amorphous carbon to graphitic nanostructures. The choice of organic precursor provides a means of controlling the catalyst particle size, which has a direct effect on the porosity of the material. Cellulose and glucose produce mesoporous carbons, while starch produces a mixture of micro- and mesopores under the same conditions and proceeds via a much slower graphitization step, generating a mixture of graphitic nanostructures and turbostratic carbon. Porous carbons are critical to energy applications such as batteries and electrocatalytic processes. For These applications, a simple and sustainable route to those carbons is essential. Therefore, the ability to control the precise structure of a biomass-derived carbon simply through the choice of precursor will enable the production of a new generation of energy materials.