TY - JOUR A1 - Jablonka, Kevin Maik A1 - Ai, Qianxiang A1 - Al-Feghali, Alexander A1 - Badhwar, Shruti A1 - Bocarsly, Joshua D. A1 - Bran, Andres M. A1 - Bringuier, Stefan A1 - Brinson, L. Catherine A1 - Choudhary, Kamal A1 - Circi, Defne A1 - Cox, Sam A1 - de Jong, Wibe A. A1 - Evans, Matthew L. A1 - Gastellu, Nicolas A1 - Genzling, Jerome A1 - Gil, María Victoria A1 - Gupta, Ankur K. A1 - Hong, Zhi A1 - Imran, Alishba A1 - Kruschwitz, Sabine A1 - Labarre, Anne A1 - Lála, Jakub A1 - Liu, Tao A1 - Ma, Steven A1 - Majumdar, Sauradeep A1 - Merz, Garrett W. A1 - Moitessier, Nicolas A1 - Moubarak, Elias A1 - Mouriño, Beatriz A1 - Pelkie, Brenden A1 - Pieler, Michael A1 - Ramos, Mayk Caldas A1 - Ranković, Bojana A1 - Rodriques, Samuel G. A1 - Sanders, Jacob N. A1 - Schwaller, Philippe A1 - Schwarting, Marcus A1 - Shi, Jiale A1 - Smit, Berend A1 - Smith, Ben E. A1 - Van Herck, Joren A1 - Völker, Christoph A1 - Ward, Logan A1 - Warren, Sean A1 - Weiser, Benjamin A1 - Zhang, Sylvester A1 - Zhang, Xiaoqi A1 - Zia, Ghezal Ahmad Jan A1 - Scourtas, Aristana A1 - Schmidt, K. J. A1 - Foster, Ian A1 - White, Andrew D. A1 - Blaiszik, Ben T1 - 14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon N2 - Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines. KW - Large Language model KW - Hackathon KW - Concrete KW - Prediction KW - Inverse Design KW - Orchestration PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-589961 DO - https://doi.org/10.1039/d3dd00113j VL - 2 IS - 5 SP - 1233 EP - 1250 PB - Royal Society of Chemistry (RSC) AN - OPUS4-58996 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Munsch, Sarah Mandy A1 - Telong, Melissa A1 - Unger, Jörg F. A1 - Andrés Arcones, Daniel A1 - Pirskawetz, Stephan T1 - 63. DAfStb-Forschungskolloquium in der BAM - Themenblock 4: Digitalisierung im Bauwesen N2 - Die Digitalisierung hat sich in vielen Bereichen des Bauwesens durchgesetzt. So sind Planung und Entwurf selbst kleinerer Bauvorhaben heute vollständig digitalisiert. Auch das Monitoring von Bestandsbauwerken ist ohne digitale Datenerfassung, -verarbeitung und -speicherung nicht denkbar. Trotzdem sind Fragen hinsichtlich der strukturierten Speicherung und künftigen Nutzung von Daten noch offen. Einige Aspekte der Digitalisierung wurden im Rahmen des 63. DAfStb-Forschungskolloquiums (Tagungsband: DOI 10.26272/opus4-61338) in Vorträgen und Veröffentlichungen aufgegriffen und werden im Folgenden zusammengefasst. T2 - 11. Jahrestagung des DAfStb mit 63. Forschungskolloquium der BAM Green Intelligent Building CY - Berlin, Germany DA - 16.10.2024 KW - Digitalisierung KW - Infrastruktur KW - Structural Health Monitoring KW - Digitaler Zwilling PY - 2025 SN - 0005-9846 VL - 75 IS - 4 SP - 136 EP - 138 PB - concrete content UG CY - Schermbeck AN - OPUS4-63070 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bayerlein, Bernd A1 - Hanke, T. A1 - Muth, Thilo A1 - Riedel, Jens A1 - Schilling, Markus A1 - Schweizer, C. A1 - Skrotzki, Birgit A1 - Todor, A. A1 - Moreno Torres, Benjami A1 - Unger, Jörg F. A1 - Völker, Christoph A1 - Olbricht, Jürgen T1 - A Perspective on Digital Knowledge Representation in Materials Science and Engineering N2 - The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples. In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge. KW - Data infrastructures KW - Digital representations KW - Digital workflows KW - Knowledge graphs KW - Materials informatics KW - Ontologies KW - Vocabulary providers PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-546729 DO - https://doi.org/10.1002/adem.202101176 SN - 1438-1656 SP - 1 EP - 14 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-54672 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Tobias A1 - Blaschke, Jil A1 - Lierenfeld, Matthias A1 - Wilsch, Gerd A1 - Dalichow, Dirk A1 - Truffer, Philipp A1 - Kruschwitz, Sabine T1 - Aktuelle Anwendungsbeispiele der laserinduzierten Plasmaspektroskopie in der Bauwerksdiagnostik N2 - Die Zustandsbewertung und Instandhaltung von Betonbauwerken erfordert zuverlässige und effiziente Analysemethoden, um komplexe Schadensmechanismen frühzeitig erkennen und fundiert bewerten zu können. Klassische chemisch-analytische Verfahren in der Betonanalytik liefern zwar präzise Ergebnisse bezogen auf die Probenmasse, sind jedoch mit erheblichem Laboraufwand verbunden, in ihrer räumlichen Auflösung durch die Probenahme begrenzt und hinsichtlich der Ergebnisinterpretation mit Unsicherheiten behaftet. Die laserinduzierte Plasmaspektroskopie (LIBS) bietet hier ein hohes Potenzial als schnelle, bildgebende und weitgehend zerstörungsarme Alternative. In den vergangenen Jahren hat sich das Verfahren zunehmend in der Bauwerksdiagnostik etabliert und wird heute für ein breites Spektrum an Anwendungen eingesetzt. Der vorliegende Beitrag gibt einen Überblick über den aktuellen Stand der LIBS-Anwendungen und zeigt anhand ausgewählter Praxisbeispiele die Leistungsfähigkeit, den Mehrwert, die Grenzen und die zukünftigen Entwicklungsperspektiven des Verfahrens auf. KW - LIBS KW - Spektroskopie KW - Chemische Analyse KW - Infrastruktur KW - Bauwerksdiagnostik PY - 2026 DO - https://doi.org/10.1002/best.70078 SN - 1437-1006 SP - 1 EP - 13 AN - OPUS4-65445 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moreno Torres, Benjami A1 - Völker, Christoph A1 - Munsch, Sarah Mandy A1 - Hanke, T. A1 - Kruschwitz, Sabine ED - Tosti, F. T1 - An Ontology-Based Approach to Enable Data-Driven Research in the Field of NDT in Civil Engineering N2 - Although measurement data from the civil engineering sector are an important basis for scientific analyses in the field of non-destructive testing (NDT), there is still no uniform representation of these data. An analysis of data sets across different test objects or test types is therefore associated with a high manual effort. Ontologies and the semantic web are technologies already used in numerous intelligent systems such as material cyberinfrastructures or research databases. This contribution demonstrates the application of these technologies to the case of the 1H nuclear magnetic resonance relaxometry, which is commonly used to characterize water content and porosity distri-bution in solids. The methodology implemented for this purpose was developed specifically to be applied to materials science (MS) tests. The aim of this paper is to analyze such a methodology from the perspective of data interoperability using ontologies. Three benefits are expected from this ap-proach to the study of the implementation of interoperability in the NDT domain: First, expanding knowledge of how the intrinsic characteristics of the NDT domain determine the application of semantic technologies. Second, to determine which aspects of such an implementation can be improved and in what ways. Finally, the baselines of future research in the field of data integration for NDT are drawn. KW - Ontology Engineering KW - Interoperability KW - Data-integration KW - NMR relaxometry KW - materials informatics PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-529716 DO - https://doi.org/10.3390/rs13122426 SN - 2072-4292 N1 - Geburtsname von Munsch, Sarah Mandy: Nagel, S. M. - Birth name of Munsch, Sarah Mandy: Nagel, S. M. VL - 13 IS - 12 SP - 2426 PB - Multidisciplinary Digital Publishing Institute (MDPI) CY - Basel, Switzerland AN - OPUS4-52971 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Silva, W. A1 - Zscherpel, Uwe A1 - Ewert, U. A1 - Lopes, R. T1 - Analysis of angular dependent spatial frequency response of Digital Coplanar Translational Laminography N2 - Digital Coplanar Translational Laminography (CTL) is a radiographic imaging technique that permits the visualization of structural details and discontinuities in the object of interest after 3D reconstruction from multiple projections. This technique becomes quite competitive regarding to computed tomography in situations of arrangements in which no complete rotation of the X-ray source - detector system around the object of interest is accessible or in cases where the part to be inspected has a high geometric asymmetry. The literature does not show many studies about image quality for different laminographic reconstructions and scan geometries. Different methodologies for measuring the Modulation Transfer Function (MTF) as a key image quality parameter for the aforementioned technique are applied. The MTF was measured using different approaches, presampled MTF or sampled MTF, both based on the Fourier Transform-Magnitude Spectrum or the square wave MTF using line pattern gauges. A sample known as Siemens Star with a converging line pattern was used to measure the circular square wave MTF. This circular MTF provides information on the direction dependent contrast transfer related to the measurement conditions, the reconstruction algorithms and the translational scan direction. For this purpose, several MTF measurements were performed in multiple angular directions. Beyond it, reconstructions were performed using different algorithms (Filtered Shifted Average) and an iterative one (MART – Multiplicative Algebraic Reconstruction Technique). Image quality analysis were done for both reconstruction methods. MART showed an image quality improvement for challenging conditions for laminographic arrangements, such as for a low number of projections (down to 25 for this study, considered as limited view, limited angle reconstruction). Additionally, a Gadolinium gauge with parallel line patterns within a range from 10 μm to 1000 μm was used to compare the square wave MTF with the sine MTFs, measured by the different techniques mentioned above. The results show that the MTF techniques presented are equivalent in this study. The results obtained for this Gadolinium plate showed a good agreement between MTF10% and SRb image measurements. The methodology presented here is used for the characterization of the frequency dependent spatial resolution of measurements obtained from different laminographic reconstruction techniques and scan geometries. Finally, from the acquisitions and reconstructions obtained with the Siemens Star, cross laminographic images were calculated in order to improve the direction dependent sensitivity. The results showed a better detectability for cross laminographic images in comparison to unidirectional coplanar translational laminographic images covering dead zones. KW - Laminography KW - Image quality KW - Modulation transfer function KW - Cross laminography KW - Reconstruction algorithms PY - 2021 DO - https://doi.org/10.1016/j.ndteint.2021.102546 SN - 0963-8695 VL - 124 SP - 1 EP - 13 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-53845 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Munsch, Sarah Mandy A1 - Strangfeld, Christoph A1 - Kruschwitz, Sabine T1 - Application of 1H proton NMR relaxometry to building materials - A review N2 - Since nuclear magnetic resonance with focus on 1H protons is highly sensitive to pore filling fluids, it is nowadays often applied for the investigation of porous media. Mainly in materials research and especially in the field of non-destructive testing in civil engineering it is increasingly used. Scientific questions about and based on NMR meanwhile cover a broad spectrum. To give an overview, we have reviewed various studies dealing with the determination of moisture contents and parameters such as the pore-size distribution, surface relaxivity, porosity, etc. In some papers, the monitoring of moisture transport in connection with degradation processes or admixtures was the main objective. In other papers, NMR was used for pore space analysis or even applied on site to assess the state of conservation of cultural heritage. Building materials that have been investigated in the presented studies are for example cement, concrete, woods, sandstones etc. In this paper, short descriptions and the significant results of the reviewed articles are summarized and their measurement problems and discrepancies are pointed out. A special feature of this review article is the concise tabular compilation of determined 𝑇1 and 𝑇2 relaxation times, as well as of surface relaxivity values for various materials and components. Finally, relevant aspects are summed up and conclusions about the increasing potential of NMR relaxometry for investigations of porous building materials are drawn, followed by an outlook about future applications and the need for technical development. KW - NMR relaxometry KW - Building materials KW - Natural stones KW - Relaxation times KW - Surface relaxivities KW - Moisture KW - Pore space characterization PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-521888 DO - https://doi.org/10.1016/j.jmro.2021.100012 N1 - Geburtsname von Munsch, Sarah Mandy: Nagel, S. M. - Birth name of Munsch, Sarah Mandy: Nagel, S. M. VL - 6-7 SP - 100012 PB - Elsevier Inc. CY - Amsterdam AN - OPUS4-52188 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Fricke, F. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Meyer, Klas A1 - Kowarik, Stefan A1 - Hierzegger, R. A1 - Westerdick, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy Using a Novel Data Augmentation Method N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are valuable analytical and quality control methods for most industrial chemical processes as they provide information on the concentrations of individual compounds and by-products. These processes are traditionally carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been realized to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra, to train an ANN with better prediction performance and speed than state-of-the-art analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. KW - Industry 4.0 KW - Cyber-Physical Systems KW - Artificial Neural Networks KW - Mass Spectrometry KW - Nuclear Magnetic Resonance Spectroscopy KW - Modular Production PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-539412 UR - https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9638378 DO - https://doi.org/10.1109/TETC.2021.3131371 SN - 2168-6750 VL - 10 IS - 1 SP - 87 EP - 98 PB - IEEE AN - OPUS4-53941 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kern, Simon A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Müller, S. A1 - Maiwald, Michael A1 - Kowarik, Stefan T1 - Artificial neural networks for quantitative online NMR spectroscopy N2 - Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data. KW - Online NMR spectroscopy KW - Real-time process monitoring KW - Artificial neural networks KW - Automation KW - Process industry PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-507508 DO - https://doi.org/10.1007/s00216-020-02687-5 SN - 1618-2642 VL - 412 IS - 18 SP - 4447 EP - 4459 PB - Springer CY - Berlin AN - OPUS4-50750 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kling e Silva, L. A1 - Almeida, G. A1 - Kadoke, Daniel A1 - Daum, Werner A1 - Ribeiro Pereira, G. T1 - Automation of pipe defect detection and characterization by structured light N2 - High quality tubular products are essential to the oil and gas industry. Quality control during their production focuses on the non-destructive detection of surface defects. The structured light technique is a candidate for the challenge to detect, monitor and evaluate such defects in real-time. In the present study the automatic processing of structured light measurements is performed and validated. The algorithm for the automatic Analysis of inspection data has an advantage over current data evaluation methods based on individual assessments of operators. KW - Non-destructive testing KW - Data processing KW - Defect evaluation KW - Materials evaluation KW - Structured light scanning (SLS) PY - 2021 DO - https://doi.org/10.1515/mt-2020-0008 SN - 0033-8230 VL - 63 IS - 1 SP - 55 EP - 61 PB - Walter de Gruyter GmbH CY - Berlin/ Boston AN - OPUS4-52124 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -