TY - CONF A1 - Bayerlein, Bernd T1 - Innovations- Plattform Material Digital N2 - Mit der Initiative MaterialDigital fördert das BMBF seit dem letzten Jahr ein wichtiges Instrument zur Digitalisierung der Materialwissenschaft und Werkstofftechnik in Deutschland. In der ersten Phase dieser Initiative wird seit Juli 2019 die Plattform MaterialDigital von einem Konsortium aufgestellt. Ziel dieser Plattform ist der Aufbau eines virtuellen Materialdatenraums, um zusammen mit allen Interessenten die Systematisierung des Umgangs mit Werkstoffdaten voranzutreiben. In einer zweiten Phase werden akademische F&E-Projekte voraussichtlich Anfang 2021 gefördert. In jedem dieser Projekte wird an einer konkreten Fragestellung das Themenfeld „Digitalisierung der Materialwissenschaft und Werkstofftechnik“ adressiert und multidisziplinär bearbeitet. In einer dritten Phase werden im Rahmen industriegeführter vorwettbewerblicher Verbundprojekte mit der gleichen Zielsetzung gefördert. T2 - Workshop - “Datenmanagement in der Additiven Fertigung” CY - Online meeting DA - 27.10.2020 KW - Digitalisierung KW - Plattform Material Digital KW - Virtueller Materialdatenraum KW - Vernetzung KW - Ontologien PY - 2020 AN - OPUS4-51609 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wang, Lei A1 - Hoyt, J. J. T1 - Layering misalignment and negative temperature dependence of interfacial free energy of B2-liquid interfaces in a glass forming system N2 - From molecular dynamics simulations and the capillary fluctuation method, the solid-liquid interfacial free energy has been computed for the B2-liquid interface in the Cu-Zr system. Consistent with previous results for the FCC-liquid interface in Cu-Zr and Al-Sm but atypical of most alloys, was found to increase as the temperature is lowered. In addition, the temperature dependence was obtained for model Lennard-Jones B2-liquid alloys. In all cases the unusual temperature dependence of is correlated with an atomic structure of the interfacial region characterized by a misalignment of the number density peaks between solvents and solutes. In cases where the number density peaks are aligned, the typical temperature dependence is observed. The results are discussed in terms of the Gibbs theory of the thermodynamics of interfaces. It is proposed that the unique interfacial structure and the atypical temperature dependence of are hallmarks of an easy glass forming alloy. KW - Atomistic simulations KW - Interfacial free energy KW - Layering misalignment KW - Glass forming PY - 2021 DO - https://doi.org/10.1016/j.actamat.2021.117259 SN - 1359-6454 VL - 219 SP - 117259 PB - Elsevier Ltd. AN - OPUS4-53650 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Charmi, Amir T1 - Mechanical anisotropy of additively manufactured stainless steel 316l: an experimental and numerical study N2 - This work aims for a yield function description of additively manufactured (AM) parts of stainless steel 316L at the continuum-mechanical macro-scale by means of so-called virtual experiments using a crystal plasticity model at meso-scale. T2 - 1st Workshop on In-situ Monitoring and Microstructure Development in Additive Manufacturing CY - BAM, Berlin DA - 10.12.2020 KW - Anisotropy KW - Crystal plasticity KW - Additive manufacturing PY - 2020 AN - OPUS4-51941 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Tensile Test: From Standard to PMD Application Ontology N2 - Data analysis methods play an important role in both the experimental and simulation-based digital description of materials but have so far been poorly structured. The platform Material Digital (PMD) should contribute to a standardized description of data processing methods in materials research. The goal is the quality assurance of the processes and the output data, the acquisition and definition of their accuracy as well as the interoperability between applications. Therefore, application ontologies are created to explicitly describe processes and test methods. In this presentation, the first efforts in creating a tensile test application ontology in accordance with the ISO standard 6892-1:2019-11 are shown. Especially, the path of ontology development to be pursued based on standards was focused. T2 - Onboarding Workshop der Plattform Material Digital (PMD) CY - Online meeting DA - 13.04.2021 KW - Ontology KW - Platform MaterialDigital KW - PMD KW - Tensile Test KW - Normung KW - Standardization PY - 2021 AN - OPUS4-52425 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Charmi, Amir T1 - Mechanical anisotropy of LPBF 316L: a modeling approach N2 - The underlying cause of mechanical anisotropy in additively manufactured (AM) parts is not yet fully understood and has been attributed to several different factors like microstructural defects, residual stresses, melt pool boundaries, crystallographic and morphological textures. To better understand the main contributing factor to the mechanical anisotropy of AM stainless steel 316L, bulk specimens were fabricated via laser powder bed fusion (LPBF). Tensile specimens were machined from these AM bulk materials for three different inclinations relative to the build plate. Dynamic Young's modulus measurements and tensile tests were used to determine the mechanical anisotropy. Some tensile specimens were also subjected to residual stress measurement via neutron diffraction, porosity determination with X-ray micro-computed tomography, and texture analysis with electron backscatter diffraction (EBSD). A crystal plasticity model was used to analyze the elastic anisotropy and the anisotropic yield behavior of the AM specimens, and it was able to capture and predict the experimental behavior accurately. Overall, it was shown that the mechanical anisotropy of the tested specimens was mainly influenced by the crystallographic texture. T2 - 2. Online-Workshop "In-situ Monitoring and Microstructure Development in Additive Manufactured Alloys " CY - Online meeting DA - 20.04.2021 KW - Anisotropy KW - Crystal plasticity KW - Additive manufacturing PY - 2021 AN - OPUS4-52603 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Tensile Test Ontology used in Platform Material Digital (PMD) N2 - Data analysis methods play an important role in both the experimental and simulation-based digital description of materials but have so far been poorly structured. The platform Material Digital (PMD) is supposed to contribute to a standardized description of data processing methods in materials research. The goal is the quality assurance of the processes and the output data, the acquisition and definition of their accuracy as well as the interoperability between applications. Therefore, application ontologies are created to explicitly describe processes and test methods. In this presentation, the first efforts within the joint project PMD in creating a tensile test application ontology in accordance with the ISO standard 6892-1:2019-11 are shown. Especially, the path of ontology development to be pursued based on standards was focused. Furthermore, the presentation includes a live demonstration of queries possibly performed to query data that was uploaded in the PMD triple store. T2 - Online Workshop: An introduction to the semantic web and ontologies CY - Online meeting DA - 23.04.2021 KW - Ontology KW - Tensile Test KW - Platform Material Digital KW - PMD KW - Knowledge Graphs KW - Semantic Web PY - 2021 AN - OPUS4-52949 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pinomaa, T. A1 - Lindroos, M. A1 - Jreidini, P. A1 - Haapalehto, M. A1 - Ammar, K. A1 - Wang, Lei A1 - Forest, S. A1 - Provatas, N. A1 - Laukkanen, A. T1 - Multiscale analysis of crystalline defect formation in rapid solidification of pure aluminium and aluminium-copper alloys N2 - Rapid solidification leads to unique microstructural features, where a less studied topic is the formation of various crystalline defects, including high dislocation densities, as well as gradients and splitting of the crystalline orientation. As these defects critically affect the material’s mechanical properties and performance features, it is important to understand the defect formation mechanisms, and how they depend on the solidification conditions and alloying. To illuminate the formation mechanisms of the rapid solidification induced crystalline defects, we conduct a multiscale modelling analysis consisting of bond-order potential-based molecular dynamics (MD), phase field crystal-based amplitude expansion simulations, and sequentially coupled phase field–crystal plasticity simulations. The resulting dislocation densities are quantified and compared to past experiments. The atomistic approaches (MD, PFC) can be used to calibrate continuum level crystal plasticity models, and the framework adds mechanistic insights arising from the multiscale analysis. This article is part of the theme issue ‘Transport phenomena in complex systems (part 2)’. KW - Rapid solidification KW - Crystalline defects KW - Molecular dynamics KW - Phase field crystal KW - Phase field method KW - Crystal plasticity PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-542156 DO - https://doi.org/10.1098/rsta.2020.0319 SN - 1364-503X VL - 380 IS - 2217 SP - 1 EP - 20 PB - Royal Society CY - London AN - OPUS4-54215 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Valdestilhas, Andre A1 - Bayerlein, Bernd A1 - Moreno Torres, Benjami A1 - Zia, Ghezal Ahmad Jan A1 - Muth, Thilo T1 - The Intersection Between Semantic Web and Materials Science N2 - The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE. KW - Linked open data KW - Materials science KW - Ontology KW - Semantic web PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-575506 DO - https://doi.org/10.1002/aisy.202300051 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-57550 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schilling, Markus T1 - Tensile Test Ontology (TTO) N2 - This is the stable version 2.0.1 of the PMD ontology module of the tensile test (Tensile Test Ontology - TTO) as developed on the basis of the 2019 standard ISO 6892-1: Metallic materials - Tensile Testing - Part 1: Method of test at room temperature. The TTO was developed in the frame of the PMD project. The TTO provides conceptualizations valid for the description of tensile test and corresponding data in accordance with the respective standard. By using TTO for storing tensile test data, all data will be well structured and based on a common vocabulary agreed on by an expert group (generation of FAIR data) which will lead to enhanced data interoperability. This comprises several data categories such as primary data, secondary data and metadata. Data will be human and machine readable. The usage of TTO facilitates data retrieval and downstream usage. Due to a close connection to the mid-level PMD core ontology (PMDco), the interoperability of tensile test data is enhanced and data querying in combination with other aspects and data within the broad field of material science and engineering (MSE) is facilitated. The TTO class structure forms a comprehensible and semantic layer for unified storage of data generated in a tensile test including the possibility to record data from analysis, re-evaluation and re-use. Furthermore, extensive metadata allows to assess data quality and reproduce experiments. Following the open world assumption, object properties are deliberately low restrictive and sparse. KW - Ontology KW - Tensile Test KW - Digitalization KW - Plattform MaterialDigital KW - Structured Data PY - 2023 UR - https://github.com/MarkusSchilling/application-ontologies/blob/479311832819af695a2c64fa8eb772f2da398061/tensile_test_ontology_TTO/pmd_tto.ttl UR - https://github.com/materialdigital/core-ontology/blob/59f5727b0437ceea5e3d9fcb8fcd0ac211e92cc3/pmd_tto.ttl PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-57935 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - PMD Workshop: Use and benefits of the PMDco N2 - This is an interactive workshop of the Plattform MaterialDigital (PMD) on Semantic Web technologies (SWT) where we delve into the world of ontology development and data structuring in the field of materials science and engineering (MSE). This workshop is designed to equip participants with essential skills in categorizing classes within ontologies, with a special emphasis on the PMD Core Ontology (PMDco). Discover the immense value of ontologies for MSE data reproducibility and reuse and harness the power of PMDco to foster your data management practices. In this workshop, you will explore the intricacies of class categorization when developing ontologies in the MSE domain. Through interactive discussions and hands-on exercises, you will learn effective techniques for structuring and organizing ontologies to enhance data retrieval and analysis. You will gain valuable insights into best practices and considerations for class categorization, aiming at optimal data organization and management within your MSE projects. One of the highlights of this workshop is the introduction to PMDco, a mid-level ontology in the field of MSE developed community-driven in the frame of the project PMD. Learn about PMDco, its underlying concepts, and its application in detail. Discover how PMDco provides a comprehensive framework for MSE data representation, enabling seamless integration and interoperability across different systems and platforms. In addition to exploring PMDco, this workshop will illustrate the benefits of data interoperability and SWT with respect to leveraging the full potential of MSE data. T2 - NFDI MatWerk Conference 2023 CY - Siegburg, Germany DA - 27.06.2023 KW - Workshop KW - Ontology KW - Plattform MaterialDigital KW - PMDco PY - 2023 AN - OPUS4-57802 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Plattform MaterialDigital in DIN NA 062-01-42 AA N2 - In dieser Präsentation werden die letzten Entwicklungen in der Plattform MaterialDigital (PMD) im DIN Normenausschuss 062-01-42 AA zur Zug- und Duktilitätsprüfung für Metalle vorgestellt. Dabei werden hauptsächlich die Entwicklungen und Neustrukturierung der PMD Core Ontology (PMDco) sowie die entsprechende Anpassung der Zugversuchsontologie (Tensile Test Ontology - TTO) inklusive des Datenmappings adressiert. Für das Datenmapping wurde ein speziell im Zusammenhang mit der PMD erstellter Zugversuchsdatensatz verwendet, welcher frei verfügbar in einem online Zenodo Repository veröffentlicht ist. Weiterhin wird die Weiterentwicklung der Norm in Verbindung mit ihrer folgenden Revision hinsichtlich der Integration von Aspekten zur Digitalisierung in der Materialwissenschaft und Werkstofftechnik sowie der Verwendung von semantischen Technologien, wie unter anderem ontologischen Repräsentationen von Materialien und Prozessen, diskutiert. T2 - DIN NA 062-01-42 AA Meeting CY - Berlin, Germany DA - 14.06.2023 KW - Ontologie KW - Semantic Web Technologies KW - Normung KW - DIN KW - Plattform MaterialDigital KW - Zugversuch KW - Tensile Test KW - Materialcharakterisierung PY - 2023 AN - OPUS4-57803 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schilling, Markus T1 - Full-Notch Creep Test Ontology (ontoFNCT) N2 - This is the stable version of the full-notch creep test ontology (OntoFNCT) that ontologically represents the full-notch creep test. OntoFNCT has been developed in accordance with the corresponding test standard ISO 16770:2019-09 Plastics - Determination of environmental stress cracking (ESC) of polyethylene - Full-notch creep test (FNCT). The OntoFNCT provides conceptualizations that are supposed to be valid for the description of full-notch creep tests and associated data in accordance with the corresponding test standard. By using OntoFNCT for storing full-notch creep test data, all data will be well structured and based on a common vocabulary agreed on by an expert group (generation of FAIR data) which is meant to lead to enhanced data interoperability. This comprises several data categories such as primary data, secondary data and metadata. Data will be human and machine readable. The usage of OntoFNCT facilitates data retrieval and downstream usage. Due to a close connection to the mid-level PMD core ontology (PMDco), the interoperability of full-notch creep test data is enhanced and querying in combination with other aspects and data within the broad field of materials science and engineering (MSE) is facilitated. The class structure of OntoFNCT forms a comprehensible and semantic layer for unified storage of data generated in a full-notch creep test including the possibility to record data from analysis and re-evaluation. Furthermore, extensive metadata allows to assess data quality and reliability. Following the open world assumption, object properties are deliberately low restrictive and sparse. KW - Ontology KW - Full-Notch Creep Test KW - FNCT KW - Knowledge Representation KW - Semantic Web Technologies KW - Data Structures KW - Data Management PY - 2024 UR - https://github.com/MarkusSchilling/ontoFNCT/blob/4abce82852190a5e444d302da077aa7404f433f0/ontoFNCT.ttl UR - https://raw.githubusercontent.com/MarkusSchilling/ontoFNCT/main/ontoFNCT.ttl PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-59815 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Birkholz, H. A1 - Bayerlein, Bernd T1 - PMD Core Ontology: A Community Driven Mid-Level Ontology in the MSE Domain 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 - FEMS EUROMAT 2023 CY - Frankfurt a. M., Germany DA - 03.09.2023 KW - Knowledge Representation KW - Semantic Interioerability KW - Mid-Level Ontology for MSE KW - FAIR Data Management PY - 2023 AN - OPUS4-58201 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - PMDco - Platform MaterialDigital Core Ontology N2 - The PMD Core Ontology (PMDco) is a comprehensive set of building blocks produced via consensus building. The ontological building blocks provide a framework representing knowledge about fundamental concepts used in Materials Science and Engineering (MSE) today. The PMDco is a mid-level ontology that establishes connections between narrower MSE application ontologies and domain neutral concepts used in already established broader (top-level) ontologies. The primary goal of the PMDco design is to enable interoperability between various other MSE-related ontologies and other common ontologies. PMDco’s class structure is both comprehensive and extensible, rendering it an efficient tool to structure MSE knowledge. The PMDco serves as a semantic middle-layer unifying common MSE concepts via semantic mapping to other semantic representations using well-known key terms used in the MSE domain. The PMDco enables straight-forward documentation and tracking of science data generation and in consequence enables high-quality FAIR data that allows for precise reproducibility of scientific experiments. The design of PMDco is based on the W3C Provenance Ontology (PROV-O), which provides a standard framework for capturing the production, derivation, and attribution of resources. Via this foundation, the PMDco enables the integration of data from various data origins and the representation of complex workflows. In summary, the PMDco is a valuable advancement for researchers and practitioners in MSE domains. It provides a common MSE vocabulary to represent and share knowledge, allowing for efficient collaboration and promoting interoperability between diverse domains. Its design allows for the systematic integration of data and metadata, enabling seamless tracing of science data. Overall, the PMDco is a crucial step towards a unified and comprehensive understanding of the MSE domain in general. T2 - FEMS EUROMAT 2023 CY - Frankfurt a. M., Germany DA - 03.09.2023 KW - Knowledge Representation KW - Ontology KW - Semantic Interoperability KW - FAIR KW - Automation PY - 2023 AN - OPUS4-58197 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - FAIR Data in Platform MaterialDigital (PMD) - Ontologies , Semantic Data Integration and Data Exchange N2 - Following the new paradigm of materials development, design, and optimization, digitalization is the main goal in materials sciences and engineering (MSE) which imposes a huge challenge. In this respect, the quality assurance of processes and output data as well as the interoperability between applications following FAIR principles are to be ensured. For storage, processing, and querying of data in contextualized form, Semantic Web technologies (SWT) are used since they allow for machine-actionable and human-readable knowledge representations needed for data management, retrieval, and (re)use. The project ‘platform MaterialDigital’ (PMD, https://materialdigital.de) aims to bring together and support interested parties from both industrial and academic sectors in a sustainable manner in solving digitalization tasks and implementing digital solutions. Therefore, the establishment of a virtual material data space and the systematization of the handling of hierarchical, process-dependent material data are focused. Core points to be dealt with are the development of agreements on data structures and interfaces implemented in distinct software tools and to offer users specific support in their projects. Furthermore, the platform contributes to a standardized description of data processing methods in materials research. In this respect, selected MSE methods are semantically represented which are supposed to serve as best practice examples with respect to knowledge representation and the creation of knowledge graphs used for material data. Accordingly, this presentation shows the efforts taken within the PMD project towards the digitalization in MSE such as the development of the mid-level PMD core ontology (PMDco, https://github.com/materialdigital/core-ontology). Furthermore, selected results of a PMD partner project use case addressing data and knowledge management from synthesis, production, and characterization of materials are shown. T2 - 1st VMAP User Meeting 2024 CY - Sankt Augustin, Germany DA - 14.02.2024 KW - Ontology KW - Semantic Web Technologies KW - Plattform MaterialDigital KW - Data Interoperability KW - Data Exchange KW - Data Structures PY - 2024 AN - OPUS4-59567 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schilling, Markus A1 - Bayerlein, Bernd A1 - Birkholz, H. A1 - Fliegener, S. A1 - Grundmann, J. A1 - Hanke, T. A1 - von Hartrott, P. A1 - Waitelonis, J. T1 - PMD Core Ontology (PMDco) N2 - The PMD Core Ontology (PMDco) is a comprehensive framework for representing knowledge that encompasses fundamental concepts from the domains of materials science and engineering (MSE). The PMDco has been designed as a mid-level ontology to establish a connection between specific MSE application ontologies and the domain neutral concepts found in established top-level ontologies. The primary goal of the PMDco is to promote interoperability between diverse domains. PMDco's class structure is both understandable and extensible, making it an efficient tool for organizing MSE knowledge. It serves as a semantic intermediate layer that unifies MSE knowledge representations, enabling data and metadata to be systematically integrated on key terms within the MSE domain. With PMDco, it is possible to seamlessly trace data generation. The design of PMDco is based on the W3C Provenance Ontology (PROV-O), which provides a standard framework for capturing the generation, derivation, and attribution of resources. By building on this foundation, PMDco facilitates the integration of data from various sources and the creation of complex workflows. In summary, PMDco is a valuable tool for researchers and practitioners in the MSE domains. It provides a common language for representing and sharing knowledge, allowing for efficient collaboration and promoting interoperability between diverse domains. Its design allows for the systematic integration of data and metadata, enabling seamless traceability of data generation. Overall, PMDco is a crucial step towards a unified and comprehensive understanding of the MSE domain. PMDco at GitHub: https://github.com/materialdigital/core-ontology KW - Ontology KW - Semantic Web technologies KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology PY - 2023 UR - https://github.com/materialdigital/core-ontology/blob/f2bd420348b276583fad6fa0fb4225f17b893c78/pmd_core.ttl PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-59352 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bayerlein, Bernd A1 - Schilling, Markus A1 - Birkholz, Henk A1 - Jung, Matthias A1 - Waitelonis, Jörg A1 - Mädler, Lutz A1 - Sack, Harald T1 - PMD Core Ontology: Achieving semantic interoperability in materials science 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 (consistent) and variant (context-specific) 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 paper, an approach how to maintain a comprehensive MSE-centric terminology composing a mid-level ontology–the Platform MaterialDigital Core Ontology (PMDco)–via MSE community-based curation procedures is presented. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics. Additionally, it demonstrates how the PMDco lowers development and integration thresholds. Moreover, the research highlights how to fuel it with real-world data sources ranging from manually conducted experiments and simulations with continuously automated industrial applications. KW - Ontology KW - Materials science and engineering KW - Knowledge representation KW - Reproducibility KW - Semantic interoperability KW - Semantic data integration PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-592948 DO - https://doi.org/10.1016/j.matdes.2023.112603 SN - 0264-1275 VL - 237 SP - 1 EP - 12 PB - Elsevier CY - Amsterdam AN - OPUS4-59294 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Hochwertige, verlässliche und FAIRe Daten erstellen: Von Ontologien und elektronischen Laborbüchern zu Datenmanagement und Wissenstransfer N2 - Das hochaktuelle Thema der Integration und Wiederverwendung von Wissen und Daten aus Herstellung, Bearbeitung und Charakterisierung von Materialien wird im Zuge der digitalen Transformation in der Materialwissenschaft und Werkstofftechnologie in verschiedenen Projekten adressiert. Dabei stehen die Interoperabilität von nach FAIR-Prinzipien erstellten und veröffentlichten Daten und Anwendungen im Vordergrund. Zur Umsetzung eines komplexen Datenmanagements sowie der Digitalisierung im Bereich der Materialwissenschaften etablieren sich Ontologien zunehmend als belastbares Werkzeug. Sie ermöglichen sowohl menschenlesbare als auch maschinenverständliche und -interpretierbare Wissensrepräsentationen durch semantische Konzeptualisierungen. Im Rahmen des Projektes Plattform MaterialDigital (PMD, materialdigital.de) werden Ontologien verschiedener Ebenen entwickelt (verbindende mid-level sowie Domänen-Ontologien). Die PMD-Kernontologie (PMD Core Ontology - PMDco) ist eine Ontologie der mittleren Ebene), die Verbindungen zwischen spezifischeren MSE-Anwendungsontologien und domänenneutralen Konzepten herstellt, die in bereits etablierten Ontologien höherer Ebenen (top-level Ontology) verwendet werden. Sie stellt somit einen umfassenden Satz von durch Konsensbildung in der Gemeinschaft (geteiltes Vokabular) entstanden Bausteinen grundlegender Konzepte aus der Materialwissenschaft und Werkstofftechnik (MSE) dar. Das primäre Ziel des PMDco-Designs ist es, die Interoperabilität zwischen verschiedenen MSE-bezogenen und anderen Ontologien zu ermöglichen. Die PMDco dient als umfassend ausgelegte und erweiterbare semantische Zwischenschicht, die gemeinsame MSE-Konzepte durch semantisches Mapping auf andere Darstellungen vereinheitlicht, was sie zu einem effizienten Werkzeug zur Strukturierung von MSE-Wissen macht. In dieser Präsentation wird die Version 2.0 der PMDco vorgestellt. Weiterhin wird eine auf die PMDco bezogene normenkonforme ontologische Repräsentation zur Speicherung und Weiterverarbeitung von Zugversuchsdaten präsentiert, die in enger Zusammenarbeit mit Standardisierungsgremien erstellt wurde. Dies umfasst den Weg von der Entwicklung einer Ontologie nach Norm, der Konvertierung von Daten aus Standardtests in das interoperable RDF-Format bis hin zur Verbindung von Ontologie und Daten. Letztendlich können die entsprechenden Daten in einem Triple Store abgelegt und abgefragt werden. Auf Basis dieser Zugversuchsontologie wurde im Folgenden unter Verwendung eines elektronischen Laborbuches (electonic lab notebook – ELN) zur Datenaufnahme eine Praktikumsreihe von Universitätsstudierenden digitalisiert. Dadurch wurde eine vollständig digital integrierte Versuchsführung ermöglicht, die auf andere Versuchsreihen und Experimente übertragbar ist und ebenfalls vorgestellt werden soll. Neben einer erleichterten Aufnahme, Analyse und (Wieder-)Verwendbarkeit von Daten wird damit eine Sensibilisierung von Studierenden für Datenstrukturierung sowie semantische Technologien im Sinne der Aus- und Weiterbildung erreicht. T2 - DVM-Tagung Werkstoffprüfung CY - Berlin, Germany DA - 23.11.2023 KW - Ontologie KW - Semantic Web Technologies KW - Plattform MaterialDigital KW - PMDco KW - Zugversuchsontologie KW - Zugversuch KW - Elektronisches Laborbuch (ELN) PY - 2023 AN - OPUS4-59030 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - PMDco: Achieving High-Quality & Reliable FAIR Data 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 - Kupfer-Symposium CY - Jena, Germany DA - 29.11.2023 KW - Ontology KW - Semantic Web Technologies KW - Plattform MaterialDigital KW - PMDco PY - 2023 AN - OPUS4-59031 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - PMDco - Platform MaterialDigital Core Ontology: Achieving High-Quality & Reliable FAIR Data 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 poster 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 - DVM Arbeitskreis Betriebsfestigkeit - Potenziale der Betriebsfestigkeit in Zeiten des technologischen und gesellschaftlichen Wandels CY - Munich, Germany DA - 11.10.2023 KW - Digitalization KW - Semantic Web Technologies KW - FAIR KW - Data Interoperability KW - PMD Core Ontology PY - 2023 AN - OPUS4-58602 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Platform MaterialDigital Core Ontology (PMDco): A Community Driven Mid-Level Ontology in the MSE Domain 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. 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 - Patents4Science CY - Berlin, Germany DA - 05.10.2023 KW - Knowledge Representation KW - Semantic Interoperability KW - FAIR data management KW - Knowledge graph and ontologies KW - PMD Core Ontology PY - 2023 AN - OPUS4-58507 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - News from the working area - Semantic Interoperability N2 - This presentation provides a comprehensive overview of recent developments and the current status within the Semantic Interoperability work area, with a particular emphasis on the advancements related to the Platform MaterialDigital Core Ontology (PMDco). The presentation will delve into the collaborative and community-supported curation process that has been instrumental in shaping PMDco. Additionally, we will introduce the innovative Ontology Playground, showcasing its role in fostering experimentation and exploration within the realm of ontology development. T2 - MaterialDigital Vollversammlung CY - Karlsruhe, Germany DA - 21.09.2023 KW - Semantic Representation KW - FAIR data management KW - Semantic Interoperability KW - Knowledge graph and ontologies KW - PMD Core Ontology KW - MaterialDigital PY - 2023 AN - OPUS4-58422 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 - JOUR A1 - Schilling, Markus A1 - Bruns, Sebastian A1 - Bayerlein, Bernd A1 - Kryeziu, Jehona A1 - Schaarschmidt, Jörg A1 - Waitelonis, Jörg A1 - Dolabella Portella, Pedro A1 - Durst, Karsten T1 - Seamless Science: Lifting Experimental Mechanical Testing Lab Data to an Interoperable Semantic Representation N2 - The scientific landscape is undergoing rapid transformations with the advent of the digital age which revolutionizes research methodologies. In materials science and engineering, an adoption of modern data management techniques is desirable to maximize the efficiency and accessibility of research efforts. Traditional practices in testing laboratories are usually inadequate for efficient data acquisition and utilization as they lead to local storage and difficulty in publication and correlation with other results. Electronic laboratory notebooks (ELNs) are promising prospects in this respect. Semantic concepts and ontologies enhance interoperability by standardizing experimental data representation. An in‐laboratory pipeline seamlessly integrating an ELN with transformation scripts to convert experimental into interoperable data in a machine‐actionable format is created in this study as a proof of concept. Tensile test results and the corresponding tensile test ontology are used exemplary. Linking ELN data to semantic concepts enriches the stored information while improving interpretability and reusability. Involving undergraduate students builds a bridge between theory and practice during their training and promotes their digital skills. This study underscores the potential of ELNs and knowledge representations as beneficial means toward improved data management practices that enhance collaborative research and education while ensuring compatibility with evolving standards and technologies. KW - Semantic Data KW - Data Integration KW - Tensile Test Ontology KW - Electronic Lab Notebook KW - Wissensrepräsentation KW - Education PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-618251 DO - https://doi.org/10.1002/adem.202401527 SP - 1 EP - 13 PB - Wiley VHC-Verlag AN - OPUS4-61825 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Interoperabilität und Wiederverwendung von Materialdaten: Der Weg zu Daten- und Wissensrepräsentationen in der PMD N2 - Die Integration und Wiederverwendung von Wissen und Daten aus der Herstellung, Bearbeitung und Charakterisierung von Materialien wird im Zuge der digitalen Transformation in der Materialwissenschaft und Werkstofftechnologie in verschiedenen Projekten behandelt. Dabei liegt der Fokus auf der Interoperabilität von Daten und Anwendungen, die nach den FAIR-Prinzipien erstellt und veröffentlicht werden. Zur Umsetzung eines komplexen Datenmanagements und der Digitalisierung im Bereich der Materialwissenschaften gewinnen Ontologien zunehmend an Bedeutung. Sie ermöglichen sowohl menschenlesbare als auch maschinenverständliche und -interpretierbare Wissensrepräsentationen durch semantische Konzeptualisierungen. Im Rahmen des Projektes Plattform MaterialDigital (PMD, materialdigital.de), welches in dieser Präsentation vorgestellt wird, werden Ontologien verschiedener Ebenen entwickelt (verbindende mid-level sowie Domänen-Ontologien). Die PMD-Kernontologie (PMD Core Ontology - PMDco) ist eine Ontologie der mittleren Ebene, die Verbindungen zwischen spezifischeren MSE-Anwendungsontologien und domänenneutralen Konzepten herstellt, die in bereits etablierten Ontologien höherer Ebenen (top-level Ontology) verwendet werden. Sie stellt somit einen umfassenden Satz von durch Konsensbildung in der Gemeinschaft (geteiltes Vokabular) entstanden Bausteinen grundlegender Konzepte aus der Materialwissenschaft und Werkstofftechnik (MSE) dar. In dieser Präsentation wird die PMDco adressiert. Weiterhin wird eine auf die PMDco bezogene normenkonforme ontologische Repräsentation zur Speicherung und Weiterverarbeitung von Zugversuchsdaten – die Tensile Test Ontology (TTO) – präsentiert, die in enger Zusammenarbeit mit dem zugehörigen DIN-Standardisierungsgremium NA 062-01-42 AA erstellt wurde. Dies umfasst den Weg von der Entwicklung einer Ontologie nach Norm, der Konvertierung von Daten aus Standardtests in das interoperable RDF-Format bis hin zur Verbindung von Ontologie und Daten. Auf Grundlage der dabei entwickelten Struktur und Vorgehensweise können weitere Materialcharakterisierungsmethoden semantisch beschrieben werden, woraus sich in diesem Zusammenhang Kooperationsmöglichkeiten ergeben. T2 - 20. Sitzung des NA 062-01-43 AA CY - Online meeting DA - 28.05.2024 KW - Semantische Daten KW - Plattform Material Digital KW - Ontologie KW - Normung KW - Wissensrepräsentation PY - 2024 AN - OPUS4-60178 LA - deu 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 - Bayerlein, Bernd T1 - PMD core ontology: Building Bridges at the Mid-Level – A Community Effort for Achieving Semantic Interoperability in Materials Science 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. This poster presents an approach to create and maintain a comprehensive and intuitive MSE-centric terminology by developing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures. 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 - TMS - Specialty Congress 2024 CY - Cleveland, Ohio, US DA - 16.06.2024 KW - Interoperability KW - Semantic Interoperability KW - Digtial Representation KW - Knowledge graph and ontologies PY - 2024 AN - OPUS4-60378 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Digital Transformation in Materials Science: Insights From the Platform MaterialDigital (PMD) 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 on Digital Transformation CY - Gaithersburg, MD, USA DA - 11.06.2024 KW - Digital Transformation KW - Research Data Management KW - Ontology KW - Reusability KW - FAIR PY - 2024 AN - OPUS4-60381 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bayerlein, Bernd A1 - Schilling, Markus A1 - Curran, Maurice A1 - Campbell, Carelyn E. A1 - Dima, Alden A. A1 - Birkholz, Henk A1 - Lau, June W. T1 - Natural Language Processing-Driven Microscopy Ontology Development N2 - AbstractThis manuscript describes the accelerated development of an ontology for microscopy in materials science and engineering, leveraging natural language processing (NLP) techniques. Drawing from a comprehensive corpus comprising over 14 k contributions to the Microscopy and Microanalysis conference series, we employed two neural network-based algorithms for NLP. The goal was to semiautomatically create the Microscopy Ontology (MO) that encapsulates and interconnects the terminology most frequently used by the community. The MO, characterized by its interlinked entities and relationships, is designed to enhance the quality of user query results within NexusLIMS. This enhancement is facilitated through the concurrent querying of related terms and the seamless integration of logical connections. KW - Microscopy Ontology KW - Knowledge Representation KW - Semantic Interoperability KW - Natural Language Processing KW - Ontology Development PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-616942 DO - https://doi.org/10.1007/s40192-024-00378-y SP - 1 EP - 12 PB - Springer Science and Business Media LLC AN - OPUS4-61694 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Advancing Digital Workflows in Materials Science: The Role of PMDco in Data Integration and Semantic Representation N2 - The field of Materials Science and Engineering (MSE) is undergoing a transformative shift towards digitalization, emphasizing the need for structured and interoperable data management. The Platform MaterialDigital Core Ontology (PMDco), now in version 3.0, addresses these challenges by providing a robust mid-level semantic framework. PMDco bridges the gap between abstract high-level ontologies, such as the Basic Formal Ontology (BFO) standardized in ISO/IEC 21838-2, and highly specific domain terminologies to ensure consistency and interoperability across diverse MSE applications. Developed through MSE community-based curation, PMDco facilitates the integration of real-world data from experiments, simulations, and industrial processes. This presentation will explore PMDco's role in enabling advanced digital workflows and its integration into demonstrators within the Platform MaterialDigital (PMD) initiative. Highlighted use cases include the semantic representation of tensile test data in compliance with ISO 6892-1:2019-11, utilizing the corresponding tensile test ontology (TTO) built on PMDco. Through an electronic laboratory notebook (ELN), data from experiments performed by undergraduate students were transformed into machine-actionable knowledge graphs, demonstrating the potential for education and fully digitalized experimental procedures. Additionally, a possible extension of PMDco as a linking point for semantically representing simulation data will be presented, aligning with the focus of VMAP. This includes linking experimental, simulation, and computational datasets to create comprehensive, FAIR-compliant knowledge ecosystems. By showcasing best practices in data acquisition, semantic integration, and knowledge graph generation, this presentation underscores PMDco’s versatility and its critical role in advancing digital MSE workflows. T2 - VMAP User Forum 2025 CY - Sankt Augustin, Germany DA - 18.02.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology PY - 2025 AN - OPUS4-62607 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Digital Transformation in Materials Science through Semantic Technologies and Knowledge Graphs N2 - The field of materials science is undergoing a transformative shift driven by digitalization. In this respect, semantic and AI technologies are paving the way for advancements in materials development, design, and optimization while leaping towards an Industry 4.0 environment. Addressing the dual challenges of quality assurance and data interoperability, this presentation examines the integration of semantic technologies and knowledge representation methods. By adhering to FAIR principles, this approach enhances data management, storage, and reuse. That way, both machine-actionable and human-understandable data structures crucial for digital research environments are fostered. This presentation focuses on the ‘platform MaterialDigital’ (PMD) initiative, which aims to support efforts from both industrial and academic sectors to solve digitalization challenges and implement sustainable digital solutions. Besides establishing structures to create virtual material data spaces, PMD develops solutions for systematizing and unifying the handling of hierarchical, process-dependent material data. Semantic technologies play a crucial role in digitalization efforts as they enable the storage, processing, and querying of data in a contextualized form. Therefore, the development and prototypical application of the PMD Core Ontology 3.0 (PMDco 3.0) tailored for materials science is highlighted. This includes the design and documentation of graph patterns that may be compiled into rule-based semantic shapes. Its integration into daily lab life is demonstrated through its application to electronic lab notebooks (ELN). This illustrates potentials of standardized protocols and automation-ready solutions for managing diverse experimental data across different sources. Outlining best practices and illustrating the possibilities that semantic technologies bring to modern labs, examples from materials processing and mechanical testing will underscore how knowledge graphs bridge the gap between data and decision-making in materials science, with potential for increased productivity and streamlined workflows across the field. T2 - Materials Week 2025 CY - Frankfurt am Main, Germany DA - 03.04.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology PY - 2025 AN - OPUS4-62866 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Rosenbusch, Sjard Mathis A1 - Diercks, Philipp A1 - Kindrachuk, Vitaliy A1 - Unger, Jörg F. T1 - Integrating custom constitutive models into FEniCSx: A versatile approach and case studies N2 - The development and integration of user-defined constitutive relationships into finite element (FE) tools using standardized interfaces play a pivotal role in advancing the capabilities of FE solvers for structural mechanics applications. While commercial FE solvers like Abaqus and Ansys have designed their interfaces to provide custom stresses, tangents, and updated history variables, the open-source solver FEniCSx remains efficient only when the constitutive update has an analytical representation. This restricts the application of FEniCSx for non-linear structural mechanics. Since FEniCSx has become a powerful and popular open-source tool for solving partial differential equations, particularly due to its automatic computation of Hessians, we aim to develop a generalized interface to enhance its capability for constitutive modeling. This approach will address complex constitutive equations that require iterative solutions at the quadrature point level. Specific implementation challenges, such as using return-mapping procedures, can then be managed commonly. The provided interface for custom constitutive models offers a versatile way to implement them in various languages, including C++, Python, Rust, and Fortran. Finally, with UMATs for viscoplastic models as an example, we demonstrate how existing user subroutines can be incorporated into the interface and utilized within the FEniCSx framework. KW - Finite element method KW - Constitutive models KW - FEniCSx KW - UMAT KW - Rust KW - Python KW - C++ PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-630439 DO - https://doi.org/10.1016/j.advengsoft.2025.103922 SN - 0965-9978 VL - 206 SP - 1 EP - 11 PB - Elsevier CY - Amsterdam AN - OPUS4-63043 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Dub, S. A1 - Haftaoglu, Cetin A1 - Kindrachuk, Vitaliy T1 - Estimate of theoretical shear strength of C60 single crystal by nanoindentation N2 - The onset of plasticity in a single crystal C60 fullerite was investigated by nanoindentation on the (111) crystallographic plane. The transition from elastic to plastic deformation in a contact was observed as pop-in events on loading curves. The respective resolved shear stresses were computed for the octahedral slip systems ⟨011¯¯¯⟩{111}, supposing that their activation resulted in the onset of plasticity. A finite element analysis was applied, which reproduced the elastic loading until the first pop-in, using a realistic geometry of the Berkovich indenter blunt tip. The obtained estimate of the C60 theoretical shear strength was about 1/11 of the shear modulus on {111} planes. KW - Finite element analysis KW - Fullerite KW - Nanoindentation PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-523208 DO - https://doi.org/10.1007/s10853-021-05991-2 VL - 56 IS - 18 SP - 10905 EP - 10914 PB - Springer Nature AN - OPUS4-52320 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bruns, Sebastian T1 - Digitalizing a lab course for undergraduate students: ELN, ontology, data management N2 - We report about a joint project aiming at the digitalization of a lab course in materials testing. The undergraduate students were asked to prepare samples of a precipitation hardened aluminum alloy and characterize them using hardness and tensile tests. In a first step, we developed the frames for the digital labor notebook using eLabFTW. The primary data and the relevant metadata of each run were saved in a central database and made available for analysis and report issues. The whole set of results produced in a course was made available in the database. This database can be improved and serve as an open repository for data on this specific alloy. The logical frame for the joint project was provided by the PMD Core Ontology (PMDco), a mid-level ontology that enables the representation and description of processes and process chains in an MSE-specific manner, ensuring full traceability of generated data. For the digitalization of this lab course, the tensile test ontology (TTO) was applied which is designed as a module of the PMDco using strongly related semantic concepts. T2 - FEMS EUROMAT 2023 CY - Frankfurt a. M., Germany DA - 03.09.2023 KW - Electronic Lab Notebook KW - FAIR data management KW - Digtial Representation KW - Knowledge graph and ontologies PY - 2023 AN - OPUS4-58207 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eisenbart, M. T1 - KupferDigital – Datenökosystem für die digitale Materialentwicklung auf Basis Ontologie-basierter digitaler Repräsentationen von Kupfer und Kupferlegierungen N2 - Kern des Projektes KupferDigital ist es, einen Demonstrator für ein digitales Datenökosystem zu erstellen, der der Digitalisierung der Materialforschung und der metallverarbeitenden Industrie als zukunftsfähige Plattform zur Verfügung stehen soll. Das Projekt KupferDigital entwickelt Methoden und Konzepte, um den Lebenszyklus am Beispiel von Kupfer – von der Erzgewinnung bis zum Recycling – digital zu erfassen. Grundlage ist die Entwicklung sogenannter Ontologien. Diese können als eine Art Wissensnetz verstanden werden. Sie dienen als gemeinsame Standards für die Beschreibung von Werkstoffen und technischen Vorgängen. Sie helfen bei der digitalen Erfassung von Prozessschritten sowie von Materialeigenschaften. Parallel dazu werden Konzepte für Datenstrukturen, die Speicherung und den Austausch von Werkstoffdaten über neu zu definierende Schnittstellen erarbeitet. Über die Bereitstellung digitalisierter Lebenszyklen von Kupfer wird die Industrie bei der Pro-duktentwicklung befähigt, neue Werkstoffentwicklungen frühzeitig zu bewerten, beispielsweise unter dem Gesichtspunkt der Nachhaltigkeit. Kupfer kommt hier eine aktuelle Bedeutung zu, weil es für die digitale Transformation sowie die Energie- und Mobilitätswende von fundamentaler Bedeutung ist und somit von hohem gesellschaftlichem Wert. Die Projektziele sind sowohl auf weitere metallische Struktur- und Funktionswerkstoffe als auch auf andere Industriebereiche übertragbar. Die Projektergebnisse werden im Rahmen der Aktivitäten der Innovationsplattform MaterialDigital allen Interessierten zur Verfügung gestellt. T2 - MatFo2022 „Vom Material zur Innovation: Digital, Neutral, Vital“ CY - Online meeting DA - 14.11.2022 KW - Kupfer KW - Datenökosystem KW - Materialentwicklung KW - Ontologie PY - 2022 AN - OPUS4-56405 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bayerlein, Bernd A1 - Schilling, Markus A1 - von Hartrott, Philipp A1 - Waitelonis, Jörg T1 - Semantic integration of diverse data in materials science: Assessing Orowan strengthening N2 - AbstractThis study applies Semantic Web technologies to advance Materials Science and Engineering (MSE) through the integration of diverse datasets. Focusing on a 2000 series age-hardenable aluminum alloy, we correlate mechanical and microstructural properties derived from tensile tests and dark-field transmission electron microscopy across varied aging times. An expandable knowledge graph, constructed using the Tensile Test and Precipitate Geometry Ontologies aligned with the PMD Core Ontology, facilitates this integration. This approach adheres to FAIR principles and enables sophisticated analysis via SPARQL queries, revealing correlations consistent with the Orowan mechanism. The study highlights the potential of semantic data integration in MSE, offering a new approach for data-centric research and enhanced analytical capabilities. KW - Semantic Interoperability KW - Knowledge Graph KW - Orowan Mechanism KW - Aluminum Alloy Aging KW - Ontology KW - Semantic Data Integration PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-599780 DO - https://doi.org/10.1038/s41597-024-03169-4 VL - 11 IS - 1 SP - 1 EP - 12 PB - Springer Science and Business Media LLC AN - OPUS4-59978 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kindrachuk, Vitaliy A1 - Klunker, Andre T1 - Phase field modeling of Hertzian cone cracks under spherica indentation N2 - A phase field model of brittle fracture has been developed to simulate the Hertzian crack induced by penetration of a rigid sphere to an isotropic linear-elastic half-space. The fracture formation is regarded as a diffusive field variable, which is zero for the intact material and unity if there is a crack. Crack growth is assumed to be driven by a strain invariant. The numerical implementation is performed with the finite element method and an implicit time integration scheme. The mechanical equilibrium and the phase field equations are solved in a staggered manner, sequentially updating the displacement field and the phase field variable. Numerical examples demonstrate the capability of the model to reproduce the nucleation and growth of the Hertzian cone crack. KW - Hertzian cracks KW - Phase field model KW - Contact mechanics PY - 2021 DO - https://doi.org/10.1007/s11223-021-00251-9 VL - 52 IS - 6 SP - 967 EP - 974 AN - OPUS4-52276 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Semantic integration of diverse data in materials science: Assessing Orowan strengthening N2 - This study applies Semantic Web technologies to advance Materials Science and Engineering (MSE) through the integration of diverse datasets. Focusing on a 2000 series age-hardenable aluminum alloy, we correlate mechanical and microstructural properties derived from tensile tests and darkfield transmission electron microscopy across varied aging times. An expandable knowledge graph, constructed using the Tensile Test and Precipitate Geometry Ontologies aligned with the PMD Core Ontology [1], facilitates this integration. This approach adheres to FAIR principles and enables sophisticated analysis via SPARQL queries, revealing correlations consistent with the Orowan mechanism (see Fig.1). The study highlights the potential of semantic data integration in MSE, offering a new approach for data-centric research and enhanced analytical capabilities [2]. T2 - MSE Congress 2024 - Materials Science and Engineering CY - Darmstadt, Germany DA - 24.09.2024 KW - Semantic Representation KW - Age-Hardenable Aluminium Alloy KW - Digtial Representation KW - Knowledge graph and ontologies KW - PMD Core Ontology PY - 2024 AN - OPUS4-61139 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schilling, Markus A1 - Marschall, Niklas A1 - Niebergall, Ute A1 - Böhning, Martin T1 - Dataset of comprehensive Full-notch creep tests (FNCT) of selected high-density polyethylene (PE-HD) materials N2 - The dataset provided in this repository comprises data obtained from a series of full-notch creep tests (FNCT) performed on selected high-density polyethylene (PE-HD) materials (for further details, see section 1 Materials in this document) in accordance with the corresponding standard ISO 16770. The FNCT is one of the mechanical testing procedures used to characterize polymer materials with respect to their environmental stress cracking (ESC) behavior. It is widely applied for PE-HD materials, that are predominantly used for pipe and container applications. It is based on the determination of the time to failure for a test specimen under constant mechanical load in a well-defined and temperature controlled liquid environment. The test device used here also allows for continuous monitoring of applied force, specimen elongation and temperature. KW - Polyethylene KW - Environmental Stress Cracking KW - Full-notch creep test KW - PE-HD KW - Crack growth PY - 2023 DO - https://doi.org/10.5281/zenodo.10143351 PB - Zenodo CY - Geneva AN - OPUS4-58835 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Plattform MaterialDigital (PMD): Konsortium, Zielsetzung, Core Ontology N2 - Die Materialwissenschaft und Werkstofftechnik (MSE) durchläuft derzeit eine digitale Transformation, die ein strukturiertes und interoperables Datenmanagement erfordert. Die Plattform MaterialDigital (PMD) adressiert diese Herausforderungen mit der PMD Core Ontology (PMDco), die inzwischen in Version 3.0 vorliegt. Diese mittlere Ontologieebene schafft eine Brücke zwischen abstrakten Top-Level-Ontologien wie der ISO/IEC 21838-2 standardisierten Basic Formal Ontology (BFO) und spezifischen domänenspezifischen Vokabularen. Ziel ist die Förderung semantischer Interoperabilität sowie die Nachvollziehbarkeit und Wiederverwendbarkeit von Daten entlang der gesamten Wertschöpfungskette in der MSE. Die Präsentation gibt einen Überblick über die Zielsetzung des PMD-Konsortiums, die Community-getriebene Entwicklung der PMDco sowie ihre Rolle in digitalen Workflows und Demonstratoren. Praxisbeispiele beinhalten die semantische Modellierung von Zugversuchen gemäß ISO 6892-1:2019-11 mithilfe der darauf aufbauenden Zugversuch-Ontologie (TTO) sowie die Umwandlung experimenteller Daten von Studierenden in maschinenlesbare Wissensgraphen über eine elektronische Laborbuch-Pipeline. Zudem wird die Ontologieentwicklung durch NLP-gestützte Ansätze (z. B. für Mikroskopie) sowie die Harmonisierung heterogener Datenquellen (z. B. im Orowan-Demonstrator) vorgestellt. Damit leistet PMDco einen entscheidenden Beitrag zur digitalen Zukunft der Materialforschung. T2 - Abschlusskolloquium LeBeDigital CY - Berlin, Germany DA - 04.06.2025 KW - Semantic Data KW - Data Integration KW - Digitalisierung KW - Digitale Transformation KW - Plattform MaterialDigital PY - 2025 AN - OPUS4-63295 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schilling, Markus A1 - Marschall, Niklas A1 - Niebergall, Ute A1 - Wachtendorf, Volker A1 - Böhning, Martin T1 - Characteristics of environmental stress cracking of PE-HD induced by biodiesel and diesel fuels N2 - In the context of the increasing effect of carbon dioxide emissions on the global climate biodiesel produced from renewable sources has emerged as a promising contender replacing fossil fuels, especially in long-range transport vehicles, using existing engines and infrastructure. High-density polyethylene is one of the prevailing materials for pipe and container applications for storage and transport of such fuels, both, from fossil and renewable resources. The contact with the respective fuels raises questions concerning material compatibility as biodiesel exhibits significant differences compared to conventional diesel fuel affecting its sorption and plasticization behavior in polyethylene. In this study, its behavior with respect to environmental stress cracking, considered one of the most frequent damage mechanisms leading to failure of polymer parts and packaging, was evaluated using the well-established Full Notch Creep Test. This approach allows for a detailed fracture surface analysis using imaging techniques, such as optical and laser scanning microscopy, as well as infrared spectroscopy. Comparing the environmental stress cracking behavior in standard surfactant solutions with that in biodiesel and diesel, respective crack propagation rates, showing different levels of acceleration, were determined and details of the underlying mechanisms could be revealed. Furthermore, the specific infrared absorption of the biodiesel’s ester functionality allows its semi-quantitative determination on the fracture surface of the tested specimens after failure. Thus, a preferred uptake of sorptive fluids in the fracture zone due to local morphological changes of the polyethylene could be directly evidenced by infrared spectroscopy. KW - Environmental stress cracking (ESC) KW - Full notch creep test (FNCT) KW - Confocal laser scanning microscopy (LSM) KW - Biodiesel KW - Diesel PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-608591 DO - https://doi.org/10.1016/j.polymertesting.2024.108547 SN - 0142-9418 VL - 138 SP - 1 EP - 16 PB - Elsevier Ltd. AN - OPUS4-60859 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schilling, Markus A1 - Marschall, Niklas A1 - Niebergall, Ute A1 - Böhning, Martin T1 - Modernizing FNCT data handling in polymer labs: Towards efficient management N2 - A streamlined Python-based workflow for transforming Full-Notch Creep Test (FNCT) data into organized, machine-actionable formats is presented. The workflow automates the conversion of raw FNCT data from classic CSV and Excel files into structured outputs that facilitate future semantic integration. Emphasizing practical data handling, the approach includes automation scripts for efficient data extraction, transformation, and storage, which culminate in well-ordered files. This transformation paves the way for potential semantic data integration and facilitates access for users with varying levels of digital experience to enhanced data management in polymer research and testing. KW - PE-HD KW - Full-Notch Creep Test (FNCT) KW - Environmental Stress Cracking (ESC) KW - Data Interoperability KW - FAIR Data KW - Semantic Data PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-637826 DO - https://doi.org/10.1016/j.commatsci.2025.114085 SN - 0927-0256 VL - 259 SP - 1 EP - 5 PB - Elsevier B.V. AN - OPUS4-63782 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Semantic Technologies for Digital Transformation in Materials Science: From PMDco to Prototypical Applications N2 - The digital transformation of Materials Science and Engineering (MSE) is accelerating the adoption of structured, interoperable, and FAIR data practices, in particular with respect to an advanced research data management. Semantic technologies play a pivotal role in this transformation, as the enable the integration, contextualization, and automation of diverse data sources across experimental, computational, and simulation domains. Central to these efforts is the Platform MaterialDigital Core Ontology (PMDco), now in version 3.0, which provides a robust mid-level semantic framework tailored for MSE. PMDco bridges abstract high-level ontologies, such as the Basic Formal Ontology (BFO) standardized in ISO/IEC 21838-2, with domain-specific terminologies to ensure consistency and interoperability across applications. This presentation explores the application of PMDco and its integration into workflows within the Platform MaterialDigital (PMD) initiative. Through its deployment in electronic laboratory notebooks (ELNs), PMDco enables semantic representation of experimental data, such as tensile test results compliant with ISO 6892-1:2019-11, transforming them into machine-actionable knowledge graphs. Prototypical implementations demonstrate how semantic technologies enhance laboratory processes, improve data reuse, and streamline documentation which offers opportunities for automation and education. Further extending its versatility, PMDco serves as a linking point for semantically representing simulation data, enabling comprehensive integration of experimental and computational datasets. This creates structured data spaces that support advanced digital workflows. Beyond PMDco, the presentation highlights the design of graph patterns and semantic shapes, showcasing generalizable methods for managing diverse data in MSE being based on data structuring and formatting. By presenting best practices in ontology development, data acquisition, and knowledge graph generation, this talk underscores the transformative potential of semantic technologies in MSE. It offers a forward-looking perspective on the role of structured data spaces as a driver for innovation, ensuring that materials science continues to advance through rigorous, interoperable, and automated digital methodologies. T2 - FEMS Euromat 2025 CY - Granada, Spanien DA - 14.09.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology KW - Graph Patterns PY - 2025 AN - OPUS4-64165 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Transforming Materials Science with Concepts for a Semantically Accessible Data Space N2 - The digital transformation in materials science enables more efficient and sustainable processes. Through technological adaptations and a commitment to the FAIR principles, materials and processes are holistically addressed across entire value chains. The Platform MaterialDigital (PMD) and related initiatives are developing innovative solutions to the challenges of digitalization. The focus is on the interoperable integration of heterogeneous materials and processes data in semantically accessible data spaces. An ontological framework, based on the PMD Core Ontology and application-specific ontologies, promotes semantic interoperability of cross-domain and multi-scale (meta)data. This framework can be extended through natural language processing in a script-supported manner, as demonstrated with the Microscopy Ontology. The presentation further highlights how freely available mechanical and microstructural datasets of various aging stages of an aluminum alloy can be semantically integrated and flexibly searched. Graph-based operations enable links between processing and microstructural properties to be established, facilitating enhanced correlation analysis and pattern recognition. T2 - TMS Specialty Congress 2025 CY - Anaheim, CA, USA DA - 15.06.2025 KW - FAIR Data KW - Semanitc Interoperability KW - Community KW - Reproducibility PY - 2025 AN - OPUS4-63474 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Data-Driven Materials Science Supported by Community, Reproducibility, and Standardization N2 - Reproducible research in materials science demands a strong community and shared semantic standards. The interdisciplinary nature of the field has led to fragmented data practices, hampering collaboration and integration. Digitalisation initatives such as the German MaterialDigital Initiative addresses this by fostering a community-driven approach to FAIR data management, using ontologies to build consensus and semantic interoperability. Through interactive events like the Ontology Playground, a unified data culture that accelerates innovation and ensures reproducibility across materials research is supported. T2 - Seminar of the Person Group CY - Berkeley, CA, USA DA - 23.06.2025 KW - FAIR Data KW - Semantic Interoperability KW - Community KW - Reproducibility PY - 2025 AN - OPUS4-63475 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ruehle, Bastian T1 - Workflow generation, management, and semantic description for Self-Driving Labs N2 - The software backend that controls the robotic hardware and runs the synthesis workflows is a very important component of any Self-Driving Lab (SDL). On the one hand, it has to deal with orchestrating and managing complex and task-specific hardware through low-level communication protocols and plan and use the available resources as efficiently as possible while executing (parallelized) workflows, on the other hand, it is the interface the users use to communicate with this highly complex platform, and as such, it needs to be as helpful and user-friendly as possible. This includes the AI-aided experimental design in which the system helps the user to decide which experiment to run next, providing automated data analysis from characterization measurements, and offering easy to understand tools and graphical user interfaces for generating the workflows that are executed on the platform. Lastly, the specificity of the workflows and their dependence on the hardware and software of the SDLs necessitates a common description or ontology for making them easily interchangeable and interoperable between different platforms and labs. In this contribution, we present several key aspects of “Minerva-OS”, the central backend that orchestrates the syntheses workflows of our SDL for Nano- and Advanced Materials Syntheses [1]. One key feature is the resource management or “traffic control” for scheduling and executing parallel reactions in a multi-threaded environment. Another is the interface with data analysis algorithms from in-line, at-line, and off-line measurements. Here, we will give examples of how automatic image segmentation of electron microscopy images with the help of AI [2] can be used for reducing the “data analysis bottleneck” from an off-line measurement. We will also discuss, compare, and show benchmarks of various machine learning (ML) algorithms that are currently implemented in the backend and can be used for ML-guided, closed-loop material optimization in our SDL. Lastly, we will show our recent efforts [3] in making the workflow generation on SDLs more user-friendly by using large language models to generate executable workflows automatically from synthesis procedures given in natural language and user-friendly graphical user interfaces based on node editors that also allow for knowledge graph extraction from the workflows. In this context, we are currently also working on an ontology for representing the process steps of the workflows, which will greatly facilitate the semantic description and interoperability of workflows between different SDL hardware and software platforms. T2 - Accelerate 2025 CY - Toronto, Canada DA - 11.08.2025 KW - Nanomaterials KW - Advanced Materials KW - Workflows KW - Machine Learning KW - SDL PY - 2025 AN - OPUS4-63936 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schilling, Markus A1 - Niebergall, Ute A1 - Marschall, Niklas A1 - Meinel, Dietmar A1 - Böhning, Martin T1 - Relation of craze to crack length during slow crack growth phenomena in high‐density polyethylene N2 - The craze‐crack mechanism occurring in high‐density polyethylene (HDPE) causing slow crack growth and environmental stress cracking is investigated in detail with respect to the relation of crack length and the related craze zone. This is essential for the understanding of the resulting features of the formed fracture surface and their interpretation in the context of the transition from crack propagation to ductile shear deformation. It turns out that an already formed craze zone does not inevitably result in formation of a propagating crack, but could also undergo ductile failure. For the examination, the full notch creep test (FNCT) was employed with a subsequent advanced fracture surface analysis that was performed using various imaging techniques: light microscopy, laser scanning microscopy, scanning electron microscopy, and X‐ray micro computed tomography scan. FNCT specimens were progressively damaged for increasing durations under standard test conditions applying Arkopal, the standard surfactant solution, and biodiesel as test media were used to analyze the stepwise growth of cracks and crazes. From considerations based on well‐established fracture mechanics approaches, a theoretical correlation between the length of the actual crack and the length of the preceding craze zone was established that could be evidenced and affirmed by FNCT fracture surface analysis. Moreover, the yield strength of a HDPE material exposed to a certain medium as detected by a classic tensile test was found to be the crucial value of true stress to induce the transition from crack propagation due to the craze‐crack mechanism to shear deformation during FNCT measurements. Highlights - Progress of crack formation in high‐density polyethylene is analyzed by different imaging techniques - Determined growth rates depend on distinction between craze zone and crack - The ratio of the present crack to the anteceding craze zone is validated theoretically - The transition from crack propagation to ductile shear deformation is identified - An already formed craze zone may still fail by ductile mechanisms KW - Craze-crack mechanism KW - Environmental stress cracking (ESC) KW - Full notch creep test (FNCT) KW - Laser scanning microscopy (LSM) KW - Slow crack growth (SCG) KW - X-ray computed tomography (CT) PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-601831 DO - https://doi.org/10.1002/pen.26698 SN - 1548-2634 VL - 64 IS - 6 SP - 2387 EP - 2403 PB - Wiley AN - OPUS4-60183 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Liu, M. A1 - Diercks, P. A1 - Manzoni, Anna Maria A1 - Čížek, J. A1 - Ramamurty, U. A1 - Banhart, J. T1 - Positron annihilation investigation of thermal cycling induced martensitic transformation in NiTi shape memory alloy N2 - Thermal cycling of a Ni-excess NiTi alloy was conducted between 50 °C and liquid nitrogen temperature to induce martensitic transformations and to reverse them after. The starting point was an annealed and slowly cooled state, the end point a sample thermally cycled 1500 times. Positron annihilation lifetime spectra and Coincidence Doppler Broadening profiles were obtained in various states and at various tem- peratures. It was found that the initial state was low in defects with positron lifetimes close to that of bulk NiTi. Cycling lead to a continuous build-up of a defect structure up to 20 0 −50 0 cycles after which saturation was reached. Two types of defects created during cycling were identified, namely pure dislo- cations and vacancies attached to dislocations. KW - Shape memory alloy KW - Thermal Cycling KW - Defects KW - Positron annihilation spectroscopy KW - Austenite-to-martensite phase transformation PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-533641 DO - https://doi.org/10.1016/j.actamat.2021.117298 VL - 220 SP - 117298 PB - Elsevier Ltd. AN - OPUS4-53364 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -