Ingenieurwissenschaften und zugeordnete Tätigkeiten
Filtern
Dokumenttyp
- Vortrag (6)
- Posterpräsentation (3)
- Zeitschriftenartikel (2)
- Forschungsdatensatz (1)
Sprache
- Englisch (12)
Schlagworte
- Reference data (12) (entfernen)
Organisationseinheit der BAM
- 5 Werkstofftechnik (5)
- 5.2 Metallische Hochtemperaturwerkstoffe (5)
- 6 Materialchemie (5)
- 1 Analytische Chemie; Referenzmaterialien (4)
- 1.2 Biophotonik (3)
- 6.1 Oberflächen- und Dünnschichtanalyse (3)
- 6.4 Materialinformatik (2)
- 9 Komponentensicherheit (2)
- 1.0 Abteilungsleitung und andere (1)
- 4 Material und Umwelt (1)
Paper des Monats
- ja (1)
Eingeladener Vortrag
- nein (6)
As industries move for ever faster development and adoption cycles of emerging new technologies in the field of welding, the meticulous and longer-winded approach of the scientific research process can feel harder to integrate. To help bridge this gap and increase the speed, quality, and adoption rate of publicly funded research, the Bundesanstalt für Materialforschung und -prüfung (BAM) continues to work towards enabling scientists with direct access to necessary software tools and - in the future – highest quality welding research reference data to further foster collaborations.
On the experimental side, the arc welding group at BAM division 9.3 “welding technologies” is continuing to expand and upgrade its capacities of robotic welding systems with integrated state of the art sensor technologies and software solutions. This allows all experiments to be recorded and measured in micro-millimeter accuracy and at sub-millisecond precision, including welding process data, complete spatial geometry and temperature measurements, process video recordings and more. The custom software-based solutions and interfaces allow scaling of the welding systems from large thick plate offshore applications to small additive repair weldments in wind turbine blades to multi-hour continuous weldments in additive manufacturing applications. In addition to the data gathered during the welding process itself, the relevant testing results and materials properties produced at BAM or externally can be integrated seamlessly. This allows detailed traceability of all results back to the actual welding process.
Regardless of the scope and application, complete datasets can be made accessible for research or industry partners in the highest resolution based on the open source WelDX (welding data exchange) file format.
Figure 1. Welding experiment representation including dynamic process data, cross-section imaging and hardness measurements from a single weldx file.
The talk will give an overview of the experimental facilities and workflows as well as current software developments with a focus on research data quality assurance, traceability, and accessibility.
Based on the integration into latest research trends and activities of the “welding technologies” division, the path to publishing reference datasets for arc welding process for various applications and materials is outlined and discussed.
In the focus of division Biophotonics are the design, preparation, analytical and spectroscopic characterization, and application of molecular and nanoscale
functional materials, particularly materials with a photoluminescence in the visible, near infrared (NIR) and short-wave infrared (SWIR). This includes optical reporters for bioimaging and sensing, security and authentication barcodes, and materials for solid state lighting, energy conversion, and photovoltaics. For the identification of optimum particle structures quantitative spectroscopic studies are performed under application-relevant conditions, focusing on the key performance parameter photoluminescence quantum yield. In addition, simple, cost-efficient, and standardizable strategies for quantifying functional groups on the surface of nano- and microparticles are developed, here with a focus on optical assays and electrochemical titration methods, cross-validated by more advanced methods such as quantitative NMR. In addition, reference materials and reference products are developed for optical methods, particularly luminescence techniques, and for analytical methods utilized for the characterization of nanomaterials.
Photoluminescence Quantum Yields of Luminescent Nanocrystals and Particles in the UV/vis/NIR/SWIR
(2023)
The rational design of functional luminescent materials such as semiconductor quantum dots and lanthanide-based upconversion nanoparticles, all photophysical and mechanistic studies, and the comparison of different emitters require accurate and quantitative photoluminescence measurements. Particularly the reliable determination of the key performance parameter photoluminescence quantum yield (f), the number of emitted per absorbed photons, and the brightness are of special importance for luminescence applications in the life and material sciences and nano(bio)photonics.[1] In this context, examples for absolute measurements of the photoluminescence quantum yields of UV/vis/NIR/SWIR emissive semiconductor quantum dots and rods, made from different materials, and spectrally shifting lanthanide upconversion nanocrystals with different surface chemistries in transparent matrices are presented including excitation wavelength and power density dependent studies utilizing integration sphere spectroscopy.[2,3] In addition, procedures for the absolute determination of the photoluminescence quantum yields of scattering dispersions of larger size quantum rods and differently sized inorganic particles have been developed as well as procedures for the characterization of solid luminescent nanomaterials such as different perovskites and YAG:Cer converter materials.[4] Thereby, challenges and pitfalls of f measurements in different wavelength regions including the SWIR and material-specific effects related to certain emitter classes are addressed, achievable uncertainties are quantified, and relative and absolute measurements of photoluminescence quantum yield measurements are compared to underline limitations of the former approach. Finally, a set of novel UV/vis/NIR quantum yield standards is presented including their certification with a complete uncertainty budget.[5]
The rational design of next generation molecular and nanoscale reporters and the comparison of different emitter classes require the determination of the fluorometric key performance parameter fluorescence quantum yield (Φf), i.e., the number of emitted photons per number of absorbed photons. Main prerequisites for reliable Φf measurements, which are for transparent luminophore solutions commonly done relative to a reference, i.e., a fluorescence quantum yield standard of known Φf, are reliable and validated instrument calibration procedures to consider wavelength-, polarization-, and time-dependent instrument specific signal contributions, and sufficiently well characterized fluorescence quantum yield standards. As the standard’s Φf value directly contributes to the calculation of the sample’s Φf, its accuracy presents one of the main sources of uncertainty of relative Φf measurements. To close this gap, we developed a first set of 12 fluorescence quantum yield standards, which absorb and emit in the wavelength region of 330−1000 nm and absolutely determined their Φf values with two independently calibrated integrating sphere setups.
Criteria for standard selection and the configuration of these novel fluorescence reference materials are given, and the certification procedure is presented including homogeneity and stability studies and the calculation of complete uncertainty budgets for the certified Φf values. The ultimate goal is to provide the community of fluorescence users with available reference materials as a basis for an improved comparability and reliability of quantum yield data since the measurement of this spectroscopic key property is an essential part of the characterization of any new emitter.
This article reports temperature-dependent elastic properties (Young’s modulus, shear modulus) of three alloys measured by the dynamic resonance method. The alloys Ti-6Al-4V, Inconel IN718, and AISI 316 L were each investigated in a variant produced by an additive manufacturing processing route and by a conventional manufacturing processing route. The datasets include information on processing routes and parameters, heat treatments, grain size, specimen dimensions, and weight, as well as Young’s and shear modulus along with their measurement uncertainty. The process routes and methods are described in detail. The datasets were generated in an accredited testing lab, audited as BAM reference data, and are hosted in the open data repository Zenodo. Possible data usages include the verification of the correctness of the test setup via Young’s modulus comparison in low-cycle fatigue (LCF) or thermo-mechanical fatigue (TMF) testing campaigns, the design auf VHCF specimens and the use as input data for simulation purposes.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
Reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) of the consortium Materials Science and Engineering (MatWerk) of National Research Data Infrastructure (NFDI) aims to develop, together with BAM and other Participant Projects (PP), a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for identifying reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
Nanoforms with at least one dimension below 100 nm have an important part to play in more and more areas of our daily life. Therefore, risk assessment of these materials is becoming increasingly important. In this context, the European Chemical Agency (ECHA) considered eleven physico-chemical properties as relevant, of which the following six are essential for the registration: chemical composition, crystallinity, particle size, particle shape, surface chemistry and specific surface area. Four of these priority properties can be obtained with electron microscopy and surface analytics like XPS and ToF-SIMS. The reliability of this data must be ensured, especially for their use for grouping and read across approaches. On the other hand, the “reproducibility” crisis has revealed major shortcomings in the reliability of published data.
In a case study, we show how the quality of the data can be ensured by using existing standards and protocols of each step in the workflow of sample characterization. As exemplary samples, two Al-coated TiO2 samples as nanopowders were selected from the JRC repository, capped either with a hydrophilic or a hydrophobic organic ultrathin shell. SEM results provided the size and shape of the nanoparticles, a first overview about the composition was obtained with EDS. XPS and ToF-SIMS supplied the surface chemistry, especially information about the shell and the coating of the particles. Standards and protocols of all steps of the analytical workflow including preparation and data reduction are discussed regarding reliable and reproducible data. Additionally, uncertainties for the different steps are specified.
Only such a detailed description of all these factors allows a comprehensive physico-chemical characterization of the nanoparticles with understanding of their potential risk assessment.
Based on practical examples of analysis with Electron Microscopy and Energy-Dispersive X-ray Spectroscopy, the minimum information requirements for reliable and reproducible nanomaterial characterization data such as particle size and shape distribution and elemental analysis are presented and discussed.