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 -