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Die Angabe von Unsicherheiten bei zertifizierten Werten von Referenzmaterialien ist von entscheidender Bedeutung. Die korrekte Einbindung der Unsicherheiten zur Berechnung von Verfahrensmessunsicherheiten ist wesentlich für die Gewährleistung der Genauigkeit und Zuverlässigkeit von Messungen. In diesem Vortrag werden die verschiedenen Einflussfaktoren auf die Unsicherheit zertifizierter Werte gemäß ISO Guide 35 dargestellt. Dabei werden insbesondere die Charakterisierung, Homogenität und Stabilität als entscheidende Faktoren für die Bestimmung der Unsicherheit eines Referenzmaterials betrachtet. Abschließend wird das Konzept anhand eines konkreten Beispiels veranschaulicht, um die praktische Anwendung und die Auswirkungen auf die Berechnung von Verfahrensmessunsicherheiten zu verdeutlichen.
Software-driven scientific workflows are often characterized by a complex interplay of various pieces of software executed in a particular order. The output of a computational step may serve as input to a subsequent computation, which requires them to be processed sequentially with a proper mapping of outputs to inputs. Other computations are independent of each other and can be executed in parallel. Thus, one of the main tasks of a workflow tool is a proper and efficient scheduling of the individual processing steps.
Each processing step, just as the workflow itself, typically processes some input and produces output data. Apart from changing the input data to operate on, processing steps can usually be configured by a set of parameters to change their behavior. Moreover, the behavior of a processing step is determined by its source code and/or executable binaries/packages that are called within it. Beyond this, the computation environment not only has a significant influence on its behavior, but is also crucial in order for the processing step to work at all. The environment includes the versions of the interpreters or compilers, as well as all third-party libraries and packages that contribute to the computations carried out in a processing step.
The frequency-domain (FD) method provides an alternative to the commonly used time-domain (TD) approach in characterizing the luminescence kinetics of luminophores, with its own strengths, e.g., the capability to decouple multiple lifetime components with higher reliability and accuracy. While extensively explored for characterizing luminophores with down-shifted emission, this method has not been investigated for studying nonlinear luminescent materials such as lanthanide-doped upconversion nanoparticles (UCNPs), featuring more complicated kinetics. In this work, employing a simplified rate-equation model representing a standard two-photon energy-transfer upconversion process, we thoroughly analyzed the response of the luminescence of UCNPs in the FD method. We found that the FD method can potentially obtain from a single experiment the effective decay rates of three critical energy states of the sensitizer/activator ions involved in the upconversion process. The validity of the FD method is demonstrated by experimental data, agreeing reasonably well with the results obtained by TD methods.
AbstractMicroplastics (MP) can be detected in all environmental systems. Marine and terrestrial aquatic systems, especially the transported suspended solids, have often been the focus of scientific investigations in the past. Sediments of aquatic river systems, on the other hand, were often ignored due to the time‐consuming sample preparation and analysis procedures. Spectroscopic measurement methods counting particle numbers are hardly suitable as detection methods, because there are plenty of natural particles next to a small number of MP particles. Integral methods, such as thermoanalytical methods are determining the particle mass independently of the inorganic components.In this study, a workflow for sample preparation via density separation and subsequent analysis by thermal extraction desorption‐gas chromatography/mass spectrometry is presented, which leads to representative and homogeneous samples and allows fast and robust MP mass content measurements suitable for routine analysis. Polymers were identified and quantified in all samples. Polyethylene and styrene‐butadiene rubber are the dominant polymers, besides polypropylene and polystyrene. Overall, total polymer masses between 1.18 and 337.0 µg/g could be determined. Highest MP concentrations in riverbed sediment are found in sites characterized by low flow velocities in harbors and reservoirs, while MP concentrations in sandy/gravelly bed sediments with higher flow velocities are small.
The development of hydrogen technologies entails high safety requirements in distribution and dispensing infrastructure. Therefore, it is necessary to pursue research on material compatibility in hydrogen, especially for critical parts with tribological issues.
The focus of this study is to evaluate the influence of hydrogen on a wider range of commercially available polymer materials. Thereby, the friction and wear behavior of different grades of TPE, POM, PA66, PA12, PPA, PEEK, PPS, PTFE, PAI, PI and PBI were investigated against a rotating steel disk (AISI 304). Filled and unfilled polymers from different suppliers were evaluated at room temperature in air, vacuum and hydrogen gas (H2) as well as in liquid hydrogen at - 253°C (LH2).
The sliding behavior of the polymer materials is discussed by means of surface analyses, whereby special attention is paid to the formation of a transfer film.
According to the results at ambient temperature, the effect of hydrogen environment on the tribological behavior of neat polymers may be related to lack of moisture, but also to saturated hydrocarbons in gaseous hydrogen. In liquid hydrogen, the best tribological performances were achieved with neat PA polymers as well as PPS and PI composites.
Reclassification of bridges, i.e., a change in load rating, using reliability-based methods and a direct update with proof load information has been presented by many authors. However, bridge reclassification has hardly been studied from a decision analytic perspective, i.e., with quantification of the risks and benefits of different classification choices, and the expected benefit gain from proof loading. We derive, explain and exemplify a decision analytic approach for bridge reclassification along with models for (1) elastic and ultimate capacity and their adaptation with proof load information, (2) proof load information with classification outcomes accounting for target reliabilities and, (3) utilities including socio-economic benefits from reclassification. The approach and models are exemplified with a case study based on reclassification of bridges with a low existing classification. Decision rules, for practical use by a highway authority to find the optimal classification, are identified and documented based on: (1) the measurement of the capacity at elastic limit by proof loading, (2) the bridge reclassification benefits, and, (3) the required annual reliability level. From a Value of Information analysis, it is concluded that the proof load information is highly valuable for reclassification in cases of high socio-economic benefits and high reliability requirements.
Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibil- ity and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in form of a bead-on- plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is devel- oped, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the tem- perature. The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.
Thermoelectric generators are very attractive devices for waste heat energy harvesting as they transform a temperature difference into electrical power. However, commercially available generators show poor power density and limited operation temperatures. Research focuses on high‐temperature materials and innovative generator designs. Finding the optimal design for a given material system is challenging. Here, a theoretical framework is provided that allows appropriate generator design selection based on the particular material properties. For high‐temperature thermoelectric oxides, it can be clearly deduced that unileg multilayer generators have the highest potential for effective energy harvesting. Based on these considerations, prototype unileg multilayer generators from the currently best thermoelectric oxide Ca3Co4O9 are manufactured for the first time by industrially established ceramic multilayer technology. These generators exhibit a power density of 2.2 mW/cm² at a temperature difference of 260 K, matching simulated values and confirming the suitability of the technology. Further design improvements increase the power density by a factor of 22 to facilitate practicable power output at temperature differences as low as 7 K. This work demonstrates that reasonable energy harvesting at elevated temperatures is possible with oxide materials and appropriate multilayer design.
The BAM Data Store
(2023)
As a partner in several NFDI consortia, the Bundesanstalt für Materialforschung und -prüfung (BAM, German federal institute for materials science and testing) contributes to research data standardization efforts in various domains of materials science and engineering (MSE). To implement a central research data management (RDM) infrastructure that meets the requirements of MSE groups at BAM, we initiated the Data Store pilot project in 2021. The resulting infrastructure should enable researchers to digitally document research processes and store related data in a standardized and interoperable manner. As a software solution, we chose openBIS, an open-source framework that is increasingly being used for RDM in MSE communities.
The pilot project was conducted for one year with five research groups across different organizational units and MSE disciplines. The main results are presented for the use case “nanoPlattform”. The group registered experimental steps and linked associated instruments and chemicals in the Data Store to ensure full traceability of data related to the synthesis of ~400 nanomaterials. The system also supported researchers in implementing RDM practices in their workflows, e.g., by automating data import and documentation and by integrating infrastructure for data analysis.
Based on the promising results of the pilot phase, we will roll out the Data Store as the central RDM infrastructure of BAM starting in 2023. We further aim to develop openBIS plugins, metadata standards, and RDM workflows to contribute to the openBIS community and to foster RDM in MSE.
The main objective was to assess homogeneity of two bimodal gold materials, namely nPsize1 and nPSize2, containing approximately 1:1 and 10:1 particle number-based ratio of ~30nm and ~60nm particles. Particle number-based concentration within the two size fractions was determined with spICP-MS using the particle frequency method of calibration.