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- 1 Analytische Chemie; Referenzmaterialien (1)
- 1.3 Instrumentelle Analytik (1)
- 6 Materialchemie (1)
- 6.5 Synthese und Streuverfahren nanostrukturierter Materialien (1)
- 7 Bauwerkssicherheit (1)
- 7.5 Technische Eigenschaften von Polymerwerkstoffen (1)
- 8 Zerstörungsfreie Prüfung (1)
- 8.4 Akustische und elektromagnetische Verfahren (1)
- 8.5 Röntgenbildgebung (1)
- 9 Komponentensicherheit (1)
The prediction of the properties of the materials used in the operation of components is of enormous importance, in order to accelerate the development process of new components. To evaluate new materials in terms of their performance (in a component), the development of new innovative methods is necessary. These methods can also be summarized under the term lab-to-field or materials – upscaling, meaning materials being characterised in a laboratory and their properties being upscaled to the component performance by means of e.g. simulation. i-TRIBOMAT is a EU funded project (H2020, GA Nr. 814494) aiming at building an Open Innovation Test Bed for tribological material characterization and offering corresponding services from tribological characterization of new materials to simulation models for predicting the performance of industrial components. By bundling the infrastructure, know-how for characterization and building a digital platform, i-TRIBOMAT becomes the world’s largest open innovation test bed for tribological material characterization.
Towards the standardization of biochar analysis: the COST action TD1107 interlaboratory comparison
(2016)
Biochar produced by pyrolysis of organic residues is increasingly used for soil amendment and many other applications. However, analytical methods for its physical and chemical characterization are yet far from being specifically adapted, optimized, and standardized. Therefore, COST Action TD1107 conducted an interlaboratory comparison in which 22 laboratories from 12 countries analyzed three different types of biochar for 38 physical–chemical parameters (macro- and microelements, heavy metals, polycyclic aromatic hydrocarbons, pH, electrical conductivity, and specific surface area) with their preferential methods. The data were evaluated in detail using professional interlaboratory testing software. Whereas intralaboratory repeatability was generally good or at least acceptable, interlaboratory reproducibility was mostly not (20% < mean reproducibility standard deviation < 460%). This paper contributes to better comparability of biochar data published already and provides recommendations to improve and harmonize specific methods for biochar analysis in the future.
The capabilities of National Metrology Institutes (NMIsthose which are members of the Comité Consultatif pour la Quantité de Matière (CCQM)of the CIPM) and selected outside "expert" laboratories to quantitate (C4H9)3Sn+ (TBT) in a prepared marine sediment were assessed. This exercise was sanctioned by the 7th CCQM meeting, April 46, 2001, as an activity of the Inorganic Analysis Working Group and was jointly piloted by the Institute for National Measurement Standards of the National Research Council of Canada (NRC) and the Laboratory of the Government Chemist (LGC), UK. A total of 11 laboratories submitted results (7 NMIs, and 4 external labs). Two external laboratories utilized a standard calibration approach based on a natural abundance TBT standard, whereas all NMIs relied upon isotope dilution mass spectrometry for quantitation. For this purpose, a species specific 117Sn-enriched TBT standard was supplied by the LGC. No sample preparation methodology was prescribed by the piloting laboratories and, by consequence, a variety of approaches was adopted by the participants, including mechanical shaking, sonication, accelerated solvent extraction, microwave assisted extraction and heating in combination with Grignard derivatization, ethylation and direct sampling. Detection techniques included ICPMS (with GC and HPLC sample introduction), GCMS, GCAED and GCFPD. Recovery of TBT from a control standard (NRCC CRM PACS-2 marine sediment) averaged 93.5±2.4% (n=14). Results for the pilot material averaged 0.680±0.015 µmol kg1 (n=14; 80.7±1.8 µg kg1) with a median value of 0.676 µmol kg1. Overall, performance was substantially better than state-of-the-art expectations and the satisfactory agreement amongst participants permitted scheduling of a follow-up Key comparison for TBT (K-28), a Pilot intercomparison for DBT (P-43), and certification of the test sediment for TBT content and its release as a new Certified Reference Material (HIPA-1) with a TBT content of 0.679±0.089 µmol kg1 (expanded uncertainty, k=2, as Sn) (80.5±10.6 µg kg1). Electronic Supplementary Material Supplementary material is available in the online version of this article at http://dx.doi.org/10.1007/s00216-003-2016-9.
Living organisms constantly interact with their environment, including through the exchange of gases. Respiration and the release and uptake of volatile organic compounds (VOCs) create dynamic microenvironments in biological systems. Studying the kinetics of volatiles in biological systems requires expensive instruments, and data analysis is challenging. Therefore, we aimed to design a minimal analytical device for measuring the composition of gaseous mixtures in realtime.
We built the ‘Modular Biological Mass Spectrometer’ (MoBiMS) from 3D-printed parts and custom sensors to fit a wide array of experimental set-ups. We tested the chemical detection range and temporal resolution of the MoBiMS employing pure compounds and complex biological samples.
Compounds with a higher than 0.4 mmHg vapor pressure and a molecular weight up to 154 g/mol were reliably sensed within seconds. The generated electron impact (EI) spectra were directly comparable with standard databases like the NIST EI library. Under a direct analysis approach, the MoBiMS identified the characteristic odor of banana (Musa sp.), that is, isoamyl acetate; tracked the dynamics of CO2 release while the Alka-Seltzer® reaction occurred showed the kinetics of the transient production and consumption of carbon dioxide during photosynthesis. MoBiMS also discriminated between volatile compounds ions coming from tobacco (Nicotiana benthamiana) leaves and the surrounding air through untargeted analysis. The small footprint of the MoBiMS and its relatively low energy consumption facilitate in situ analyses, as an additional gas supply is not necessary with EI ionization. The MoBiMS is easy to assemble, and its construction and operation are very cost-efficient compared to commercial devices. The analytical performance of the MoBiMS is suitable for real-time studies of biological systems, environmental monitoring, and medical diagnostics.
Clustering of magnetic nanoparticles can drastically change their collective magnetic properties, which in turn may influence their performance in technological or biomedical applications. Here, we investigate a commercial colloidal dispersion (FeraSpinTMR), which contains dense clusters of iron oxide cores (mean size around 9 nm according to neutron diffraction) with varying cluster size (about 18–56 nm according to small angle x-ray diffraction), and its individual size fractions (FeraSpinTMXS, S, M, L, XL, XXL). The magnetic properties of the colloids were characterized by isothermal magnetization, as well as frequency-dependent optomagnetic and AC susceptibility measurements. From these measurements we derive the underlying moment and Relaxation frequency distributions, respectively. Analysis of the distributions shows that the clustering of the initially superparamagnetic cores leads to remanent magnetic moments within the large clusters. At frequencies below 105 rad s−1, the relaxation of the clusters is dominated by Brownian (rotation) relaxation. At higher frequencies, where Brownian relaxation is inhibited due to viscous friction, the clusters still show an appreciable magnetic relaxation due to internal moment relaxation within the clusters. As a result of the internal moment relaxation, the colloids with the large clusters (FSL, XL, XXL) excel in magnetic hyperthermia experiments.
A novel approach for rating fatigue-initiating inclusions in highly demanding steel (INCAFAT)
(2018)
INCAFAT project aimed to improve existing fatigue damage models by establishing the most suitable combination of measurement techniques to characterise harmful inclusion populations in highly demanding steels. The different inclusion assessments carried out confirm that, chemical composition, secondary metallurgy and manufacturing route affect content, nature, size and shape of inclusions. According to the FEM model, inclusions produce an alteration of the stress field in their surrounding region, which can promote a fatigue failure. Experimental work on fatigue testing has demonstrated that depending on the stressed direction fatigue failures in highly demanding steels could be produced by different types of inclusions. Fractography analyses confirmed that meso-inclusions harmful in fatigue cannot be rated by standard methods, nor 10 MHz ultrasonic testing (macro) or micro-cleanness assessments. The necessity of rating these meso-inclusions has led to critical evaluation of Extreme Value Analysis according to ASTM E2283-08 and the development of high frequency immersion ultrasonic testing. EVA methodology based on inclusion width can be applied reliably when principal stress is parallel to the rolling direction. On the contrary, if inclusions are testing in the elongated directions its fails. On the other hand, the guidelines and recommendations for high frequency ultrasonic testing have been compiled in a new European standard draft. This method based on focal beam probes and high-resolution devices is able to provide information on meso-inclusion distribution.
Hydroliquefaction is a possible pathway to produce liquid transportation fuels from solid feedstocks like coal or biomass. Though much effort has been put into the investigation of maximizing the oil yield using expensive catalysts and pasting oils in batch setups, little is known about how to commercialize the process. This work aims at the demonstration of lignin hydroliquefaction under conditions interesting for commercial operation. The results from hydroliquefaction experiments of two different lignin types using a cheap iron-based catalyst and anthracene oil as the pasting oil in a semibatch system are presented here. Oil yields of above 50% are reached without observing coke formation. Extensive analyses of the feedstocks and product oils were performed. The process supplies high-quality oil, while differences in the decomposition path of both lignin types are observed. An high heating value of 39 400 J/g and H/C and O/C ratios of up to 1.6 and 0.1, respectively, are detected for the produced bio-oils.
In the present study, we applied a regularized inversion method to extract the particle size, magnetic moment and relaxation-time distribution of magnetic nanoparticles from small-angle x-ray scattering (SAXS), DC magnetization (DCM) and AC susceptibility (ACS) measurements. For the measurements the particles were colloidally dispersed in water. At first approximation the particles could be assumed to be spherically shaped and homogeneously magnetized single-domain particles. As model functions for the inversion, we used the particle form factor of a sphere (SAXS), the Langevin function (DCM) and the Debye model (ACS). The extracted distributions exhibited features/peaks that could be distinctly attributed to the individually dispersed and non-interacting nanoparticles. Further analysis of these peaks enabled, in combination with a prior characterization of the particle ensemble by electron microscopy and dynamic light scattering, a detailed structural and magnetic characterization of the particles. Additionally, all three extracted distributions featured peaks, which indicated deviations of the scattering (SAXS), magnetization (DCM) or relaxation (ACS) behavior from the one expected for individually dispersed, homogeneously magnetized nanoparticles. These deviations could be mainly attributed to partial agglomeration (SAXS, DCM, ACS), uncorrelated surface spins (DCM) and/or intra-well relaxation processes (ACS). The main advantage of the numerical inversion method is that no ad hoc assumptions regarding the line shape of the extracted distribution functions are required, which enabled the detection of these contributions. We highlighted this by comparing the results with the results obtained by standard model fits, where the functional form of the distributions was a priori assumed to be log-normal shaped.