TY - GEN A1 - Glauer, M. A1 - Schilling, Markus A1 - Stappel, M. T1 - A practical ontology development guide N2 - Knowledge representation is becoming increasingly important in view of the large amounts of data that are handled in the modern scientific landscape. Many of the domains that have most readily realised this problem and worked on potential solutions have been the domain of biochemistry. And although the developments sought here were not accompanied by philosophers, this process organically led to the development of formal and structured representations of certain domains. While the resulting structures were not the first formal ontologies, they are ones that are still in wide use to this day. These approaches have led to major advances in the organisation, structuring and communication of scientific results. Since then, a variety of other domains have tried to adapt a similar process and develop their own ontologies. However, the development of ontologies from the domain of biochemistry was the result of a years-long process that also involved a large number of errors and course corrections. One of the greatest challenges is also one of the greatest strengths of ontologies: Interoperability with other ontologies. To ensure this interoperability, ontologies must follow certain principles. In the field of biochemistry, the OBO Foundry has established itself, which offers functionalities for a rich network of ontologies from the domain, but at the same time also defines rules. The purpose of this document is to define a similar set of rules for open ontology development, but which addresses a broader domain and at the same time lowers the barrier of entry for new ontology developers. To this end, we will outline a workflow that can be used to build new ontologies more efficiently. This workflow is based not only on our own years of experience in ontology development, but also on the rules of external experts such as the OBO Foundry. KW - Ontology KW - Data integration KW - Ontologie KW - Data interoperability PY - 2024 UR - https://scientific-ontology-network.github.io/ UR - https://github.com/scientific-ontology-network/ontology-development-guide/releases/download/v0.1.0/ontology-guide.pdf SP - 1 EP - 27 PB - GitHub CY - San Francisco ET - Version 0.1 AN - OPUS4-61140 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Birkholz, Henk A1 - Bayerlein, Bernd T1 - Evolution of the PMD Core Ontology (PMDco) Towards ISO/IEC 21838-2:2021 Basic Formal Ontology (BFO) N2 - Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific. In this presentation, an approach how to maintain a comprehensive and intuitive MSE-centric terminology composing a mid-level ontology–the PMD Core Ontology (PMDco)–via MSE community-based curation procedures is shown. The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications. T2 - MSE Congress 2024 - Materials Science and Engineering CY - Darmstadt, Germany DA - 24.09.2024 KW - Ontology KW - Semantic Interoperability KW - Knowledge representation KW - FAIR Data Management KW - PMD Core Ontology PY - 2024 AN - OPUS4-61141 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eisenbart, Miriam T1 - Digitalization of a high-throughput alloy development process N2 - Digitalization is nowadays the central key in developing pharmaceutical products, but it also becomes increasingly important in computer aided material development. In this work it is presented how a collaborative ontology development for the alloy development process is approached and a workflow for chemical optimization of copper alloys is introduced. This is done by employing a combination of a high-throughput alloy development method [1] with the calculation of the corresponding phase compositions. The work presented here is part of the publicly funded project KupferDigital. The project is associated with the innovation platform MaterialDigital (PMD) and focusses on the digitalization of processes as well as knowledge representation along the life-cycle of copper and copper alloys. One part of this life cycle is the alloy development of copper alloys, in this case the alloy development employing a high throughput method based on diffusion couples. The alloy development process can be further broken down into several typical material processing steps such as casting, diffusion welding and annealing. As part of the copper life cycle, the constitution and the properties of an alloy play an important role for processes further down the road during product manufacturing and service life and are also crucial for the recycling properties of the alloy. It is therefore important to, on the one hand, communicate data concerning properties, process history and constitution to the following stations of the life cycle, on the other hand, it is also elementary for the material scientist to be aware of the recycling properties of the alloys constituents. This motivates sharing of data along the life cycle and the development of ontology based data spaces, where life-cycle information can be linked across all involved domains. As part of the alloy development process, it is presented how experimental data created at fem are shared using linked data and ontologies with an example based on the digital representation of the chemical composition of copper alloys further processed by CALculation of PHAse Diagrams (CALPHAD) at the Fraunhofer IWM. The calculation results are used to correlate measured hardness data with the equilibrium phases of the alloys. Selected Compositions are cast and heat treated and subjected to mechanical testing at BAM and the resulting mechanical property-data are again linked to the measured and simulated data from the alloy development process. T2 - MSE2024 CY - Darmstadt, Germany DA - 24.09.2024 KW - Digitalization KW - Alloy development PY - 2024 AN - OPUS4-61150 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Höhne, Patrick T1 - Optimized spray granules for dry pressing by means of slurry destabilization and ultrasonic atomization N2 - The homogeneous introduction of organic additives is a prerequisite for good processability of ceramic powders during dry pressing. The addition of organic additives by wet route via ceramic slurries offers advantages over dry processing. The organic content can be reduced and a more homogeneous distribution of the additives on the particle surface is achieved. In addition to the measurements of zeta potential and viscosity, sedimentation analysis by optical centrifugation was also tested and successfully used to characterize the ceramic slurries and accurately evaluate of the suitability of different types, amounts, and compositions of organic additives. Spray drying of well-stabilized slurries usually results in mostly hollow granules with a hard shell leading to sintered bodies with defects and reduced strength and density. By purposefully degrading the slurry stability after dispersion of the ceramic powder, the drying behavior of the granules in the spray drying process and thus the granule properties can be influenced. Destabilization of the slurry and thus partial flocculation was quantified by optical centrifugation. Spray drying of the destabilized alumina slurries resulted in "non-hollow" granules without the detrimental hard shell and thus improved granule properties. Further improvement of the granules was achieved by installing ultrasonic atomization in the spray dryer. A narrower granule size distribution was achieved, which had a positive effect on, among other things, the flowability of the granules. Specimens produced from this granules had fewer defects of smaller size, leading to better results for the density and strength of the sintered bodies. The observations made for alumina could be transferred to zirconia and as well to ZTA with 20 wt% zirconia. T2 - Ceramics in Europe 2022 CY - Krakau, Poland DA - 10.07.2022 KW - Ultrasound KW - Spray drying KW - Slurry PY - 2022 AN - OPUS4-56171 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hemmleb, M. T1 - Integrated topographic SEM imaging for software assisted fractography N2 - The aim of a fractographic investigation is the evaluation of macroscopic and microscopic fracture surface characteristics and, as a result, the determination of the fracture mechanism of a component from a failure case. The basis for such evaluations of fracture characteristics comes from actual comparative mechanical testing and from the literature. A fractographic analysis can be very complex and, in any case, requires considerable experience. Machine learning methods enables the quantitative determination of fracture characteristics and fracture mechanisms utilizing digitized expert knowledge [1]. Although the application of SE images provides promising results, additional information is required to obtain reliable solutions. As expected, BSE and 3D information helps to improve the classification (Fig. 1). But only a fast, widely integrated, and automated topography measurement can provide the required amount of referenced surface data for the application of machine learning methods. To fulfil these requirements, topographical data are obtained from a BSE detector with four symmetric segments (4Q-BSE) using shape-from-shading technology [2]. Surface height calculation is performed live during image acquisition and provides immediate feedback in three dimensions. All available signals (SE, BSE and more if applicable) are recorded simultaneously together with the surface topography and stored in a multichannel data file. This guaranties the same geometrical reference for all data, which is required for further analysis (Fig. 2). When applying machine learning methods to topographic data together with SEM images, topographic information must be provided as depth image. Consequently, a unique height scale is required for all applied data with different magnifications. This requires a calibrated height measurement, which is ensured with the integrated 3D calibration of the topographic acquisition and a dedicated calibration sample. Thus, a large number of data sets from different fracture samples was generated and used as training data for machine learning. T2 - 16th Multinational Congress on Microscopy CY - Brno, Czech Republic DA - 04.09.2022 KW - Fractography KW - Machine Learning KW - Topography PY - 2022 AN - OPUS4-55937 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schmies, Lennart T1 - Using Machine Learning and Topographic SEM Imaging for Software Assisted Fractography N2 - The aim of a fractographic investigation is the evaluation of macroscopic and microscopic fracture surface characteristics and, as a result, the determination of the fracture mechanism of a component from a failure case. The basis for such evaluations of fracture characteristics comes from actual comparative mechanical testing and from the literature. A fractographic analysis can be very complex and, in any case, requires considerable experience. In the IGF project "iFrakto", software is being developed that quantitatively determines fracture characteristics and fracture mechanisms utilizing digitized expert knowledge, machine learning, and standard 2D and topographical data from SEM imaging. Topographical data are obtained from 4QBSE detector using shape-from-shading technology. In the medium term, a software tool should provide knowledge-based suggestions for the evaluation of fracture surfaces in real time during SEM work or at subsequent evaluation. As a basis for this, round robins were carried out among fractographers in order to create a knowledge base, to query the practice-relevant requirements for such tools and to carry out first practical tests. Actual results are presented and the relevance of the evaluation strategy is evaluated. T2 - Material Science and Engineering 2022 CY - Darmstadt, Germany DA - 27.9.2022 KW - Fractography KW - Machine Learning KW - Topography PY - 2022 AN - OPUS4-55938 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - INPR A1 - Langer, Carlotta A1 - Georgie, Yasmin Kim A1 - Porohovoj, Ilja A1 - Hafner, Verena Vanessa A1 - Ay, Nihat T1 - Analyzing Multimodal Integration in the Variational Autoencoder from an Information-Theoretic Perspective N2 - Human perception is inherently multimodal. We integrate, for instance, visual, proprioceptive and tactile information into one experience. Hence, multimodal learning is of importance for building robotic systems that aim at robustly interacting with the real world. One potential model that has been proposed for multimodal integration is the multimodal variational autoencoder. A variational autoencoder (VAE) consists of two networks, an encoder that maps the data to a stochastic latent space and a decoder that reconstruct this data from an element of this latent space. The multimodal VAE integrates inputs from different modalities at two points in time in the latent space and can thereby be used as a controller for a robotic agent. Here we use this architecture and introduce information-theoretic measures in order to analyze how important the integration of the different modalities are for the reconstruction of the input data. Therefore we calculate two different types of measures, the first type is called single modality error and assesses how important the information from a single modality is for the reconstruction of this modality or all modalities. Secondly, the measures named loss of precision calculate the impact that missing information from only one modality has on the reconstruction of this modality or the whole vector. The VAE is trained via the evidence lower bound, which can be written as a sum of two different terms, namely the reconstruction and the latent loss. The impact of the latent loss can be weighted via an additional variable, which has been introduced to combat posterior collapse. Here we train networks with four different weighting schedules and analyze them with respect to their capabilities for multimodal integration. KW - Multimodal Integration KW - Variational Autoencoder KW - Information Theory KW - Posterior Collapse PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-616420 DO - https://doi.org/10.48550/arXiv.2411.00522 SP - 1 EP - 17 PB - Cornell University CY - Ithaca, NY AN - OPUS4-61642 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Digital Transformation in Materials Science: Insights from Platform MaterialDigital (PMD), Tensile Test Ontology (TTO), Electronic Lab Notebooks (ELN) N2 - The digital era has led to a significant increase in innovation in scientific research across diverse fields and sectors. Evolution of data-driven methodologies lead to a number of paradigm shifts how data, information, and knowledge is produced, understood, and analyzed. High profile paradigm shifts in the field of materials science (MS) include exploitative usage of computational tools, machine learning algorithms, and high-performance computing, which unlock novel avenues for investigating materials. In these presentations, we highlight prototype solutions developed in the context of the Platform MaterialDigital (PMD) project that addresses digitalization challenges. As part of the Material Digital Initiative, the PMD supports the establishment of a virtual materials data space and a systematic handling of hierarchical processes and materials data using a developed ontological framework as high priority work items. In particular, the mid-level ontology PMDco and its augmentation through application-specific ontologies are illustrated. As part of the conclusion, a discussion encompasses the evolutionary path of the ontological framework, taking into account standardization efforts and the integration of modern AI methodologies such as natural language processing (NLP). Moreover, demonstrators illustrated in these presentations highlight: The integration and interconnection of tools, such as digital workflows and ontologies, Semantic integration of diverse data as proof of concept for semantic interoperability, Improved reproducibility in image processing and analysis, and Seamless data acquisition pipelines supported by an ontological framework. In this context, concepts regarding the application of modern research data management tools, such as electronic laboratory notebooks (ELN) and laboratory information management systems (LIMS), are presented and elaborated on. Furthermore, the growing relevance of a standardized adoption of such technologies in the future landscape of digital initiatives is addressed. This is supposed to provide an additional basis for discussion with respect to possible collaborations. T2 - NIST Seminar Series CY - Gaithersburg, MD, USA DA - 11.06.2024 KW - Semantic Data KW - Plattform Material Digital KW - Digitalization KW - Data Interoperability KW - NIST KW - Tensile Test Ontology KW - Elctronic Lab Notebook PY - 2024 AN - OPUS4-60392 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - de Camargo, Andrea Simone Stucchi T1 - Structure-property correlations in RE-doped fluoride-phosphate glasses sought by NMR, EPR & PL N2 - As the development of optimized glass compositions by traditional trial-and-error methods is laborious, expensive, and time consuming, it is desirable to gather fundamental understanding of structure and to develop structure-property relation models, which allow best and faster choices. Particularly, when it comes to optical applications of glasses doped with emissive trivalent rare earth ions (RE), the chemical environmental around the ions will have a direct influence on the radiative/non-radiative emission probabilities. The vibrational environment and the chemical nature of the bonds in the first coordination sphere of the ions can be tailored, to some extent, based on structural information given by magnetic resonance (NMR and EPR) techniques associated to Raman and photophysical characterization. For the past 5 years, one of the interests of my research group at the University of São Paulo, in Brazil, has been the development of high-density fluoride-phosphate glasses as promising UV and X-ray scintillator materials. The targeted glasses offer a lower vibrational energy, less hygroscopic fluoride environment for the RE ions whereas the phosphate network provides improved mechanical and chemical stability than a purely fluoride glass matrix. Different sets of glasses, based on the compositional system (Ba/Sr)F2-M(PO3)3-MF3-(Sc/Y)F3 where M = Al, In, Ga, and the phosphate component is substituted by the fluoride analogue in 10-30 mol%, were investigated, using Sc3+, Y3+, and the Eu3+ and Yb3+ dopants, as structural probes. Overall, results show that the desired RE coordination by F, at a given F/P ratio, is proportional to the atomic mass of M (In> Ga> Al) and that the Ga- and In- based systems differ from the Al- one by near absence of P-O-P network linkages i.e, the network structures are dominated by Ga-O-P or In-O-P linkages as evidenced by 31P MAS-NMR and Raman. These results are nicely corroborated by observation of decreased intensity in the vibronic band of Eu3+ and significant increase in the excited state lifetime values. Radioluminescence studies were carried out for a series of In-based glasses doped with Ce3+ and Tb3+ yielding intense emissions in the blue and green, respectively, compatible to the spectral region of highest sensitivity of radiation sensor detectors. The aim of the presentation is to show how powerful the combination of NMR, EPR, Raman and PLE spectroscopies can be to provide structural information and to present the perspectives for their introduction in the research agenda of Division 5.6 – Glass, which I now lead, at the Federal Institute for Materials Research and Testing (BAM) in Berlin, Germany. T2 - GOMD 2024 - Glass and Optical Division Meeting, ACerS CY - Las Vegas, NV, USA DA - 19.05.2024 KW - Glass Digital KW - Glasses KW - Robotic melting PY - 2024 AN - OPUS4-60357 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Galleani, Gustavo A1 - Lodi, Thiago A. A1 - Conner, Robin L. A1 - Jacobsohn, Luiz G. A1 - de Camargo, Andrea Simone Stucchi T1 - Photoluminescence and X-ray induced scintillation in Gd3+-Tb3+ co-doped fluoride-phosphate glasses, and derived glass-ceramics containing NaGdF4 nanocrystals N2 - The glass system (50NaPO3–20BaF2–10CaF2–20GdF3)-xTbCl3 with x = 0.3, 1, 3, 5, and 10 wt % was investigated. We successfully produced transparent glass ceramic (GC) scintillators with x = 1 through a melt-quenching process followed by thermal treatment. The luminescence and crystallization characteristics of these materials were thoroughly examined using various analytical methods. The nanocrystallization of Tb3+-doped Na5Gd9F32 within the doped fluoride-phosphate glasses resulted in enhanced photoluminescence (PL) and radioluminescence (RL) of the Tb3+ ions. The GC exhibited an internal PL quantum yield of 33 % and the integrated RL intensity across the UV-visible range was 36 % of that reported for the commercial BGO powder scintillator. This research showcases that Tb-doped fluoridephosphate GCs containing nanocrystalline Na5Gd9F32 have the potential to serve as efficient scintillators while having lower melting temperature compared to traditional silicate and germanate glasses. KW - Glass scintillator KW - Fluoride phosphate glasses KW - Gd3+ KW - Tb3+ PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-603588 DO - https://doi.org/10.1016/j.omx.2023.100288 VL - 21 SP - 1 EP - 9 PB - Elsevier B.V. AN - OPUS4-60358 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -