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 -