TY - GEN A1 - Pedersen, Angus T1 - Mg-Templated Porosity as a Descriptor of Activity and Durability in ZIF-Derived Fe–N–C O2 Reduction Catalysts - Dataset N2 - Atomically dispersed Fe in N-doped carbon (Fe-N-C) catalysts are leading platinum-group-metal-free candidates for the O2 reduction reaction in proton exchange membrane fuel cells (PEMFCs). Zeolitic imidazolate framework (ZIF-8) derived Fe-N-C present the most promising performance; however, they possess a narrow distribution of small micropores, which limits active site accessibility. Here, to induce hierarchical porosity in Fe-N-C, we report a systematic study on MgCl₂·6H₂O-templated ZIF-8-derived Fe-N-C catalysts for the O2 reduction reaction. MgCl₂·6H₂O addition induced complete Zn removal, collapse of the ZIF-8 framework, and formation of large micro- and mesopores, with graphene-like structures. N content was markedly reduced, with conversion from pyridinic to pyrrolic N species. Rotating disc electrode tests showed a progressive increase in O2 reduction activity with MgCl₂·6H₂O, which is strongly correlated (R2 = 0.98) to the formation of large micropores and small mesopores (1-4 nm). This introduces a clear structure-activity design principle for Fe-N-Cs. The enhanced Fe-N-C porosity also leads to increased degradation rates under accelerated stress test conditions, which we attributed to the oxidation of disordered carbon domains and active Fe loss. This study highlights a key trade-off between porosity-driven O2 reduction activity and durability in Fe-N-C catalysts. KW - Single atom KW - Zeolitic imidazolate framework KW - Oxygen reduction PY - 2026 DO - https://doi.org/10.26272/opus4-65228 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-65228 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Klewe, Tim T1 - Synthetic Dataset for Sequential Learning-Based Optimisation of Bio-Ash Binder Formulations under Seasonal Availability Constraints N2 - This dataset accompanies the study on sequential learning–based optimisation of bio-ash–cement binder formulations under seasonally varying material availability. It provides a fully synthetic but chemically inspired benchmark design space for evaluating data-driven optimisation strategies in cementitious materials research. The dataset comprises 5,006 unique binder formulations, each defined by the mass fractions of cement and five bio-based ash components (A1–A5). Ash components represent generic bio-ash types derived from agricultural residues (e.g. rice husk ash, cassava peel ash), and their internal proportions are systematically varied under mass-balance constraints. Cement content ranges from 0 to 100 wt% in discrete steps. To reflect dynamic supply conditions, the dataset includes season-specific ash usage metrics for four seasons (S1–S4), expressing the fraction of available ash resources consumed by each formulation. A synthetic compressive strength value is assigned to every formulation using a nonlinear scoring function based on chemically inspired descriptors, with added noise to generate a structured yet non-trivial optimisation landscape. These strength values do not represent calibrated physical predictions and are intended solely as a hidden objective function for benchmarking sequential learning algorithms. The dataset is designed for in silico benchmarking, reproducibility studies, and methodological comparisons of optimisation and active learning strategies. It enables systematic evaluation of algorithmic performance without the need for physical experiments. KW - Sequential learning KW - Bio-based ashes KW - Low-clinker cement KW - Mixture optimisation KW - Supplementary cementitious materials PY - 2026 DO - https://doi.org/10.5281/zenodo.18389681 PB - Zenodo CY - Geneva AN - OPUS4-65420 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kozachynskyi, Volodymyr A1 - Staubach, Dario T1 - Monte Carlo analysis of esterification reaction model with disappearing second liquid phase N2 - This research item is associated with the publication: Parameter estimation in dynamic multiphase liquid-liquid equilibrium systems (submitted after 2025-02-15) The software used to generate and analyze the experimental data is stored with the research data. KW - Parameter Estimation KW - NRTL KW - LLE KW - Phase Detection PY - 2025 DO - https://doi.org/10.14279/depositonce-21232 PB - Technische Universität Berlin CY - Berlin AN - OPUS4-62670 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Grandel, Jonas A1 - George, Janine T1 - Mace-mp-03b Phonon Benchmark N2 - This repository contains phonon calculations and evaluations for the MACE MP-0b3 model. First release of the scripts used for the phonon benchmark in the paper benchmarking the MACE-MP-03b model. See https://arxiv.org/abs/2401.00096 for a previous version of the paper. Full Changelog: https://github.com/JaGeo/mace-mp-03b-phonon-benchmark/commits/v0.0.1 KW - Machine Learned Interatomic Potentials KW - Phonons KW - Thermal Conductivity KW - Materials Searches KW - Foundation Model PY - 2025 DO - https://doi.org/10.5281/zenodo.15462975 PB - Zenodo CY - Geneva AN - OPUS4-63174 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Grohmann, Maria T1 - Low-frequency ultrasound data (pulse-echo technique) of shear horizontal and longitudinal waves acquired on the concrete step specimen “Pk401” with embedded polystyrene foam cuboids N2 - This dataset includes raw pulse-echo ultrasound measurements of a stepped concrete specimen (ID “Pk401”) from BAM, Berlin. The specimen (2000 × 800 mm) has four thicknesses—573.8, 453.4, 333.1, 210.4 mm—and contains polystyrene cuboids (120 × 120 × 60 mm) centered at depths of 270, 210, 150, and 90 mm. Measurements utilized both shear (M2502) and longitudinal (M2503) probes, combining commercial and in-house BAM equipment. KW - Reference data KW - Non destructive testing and evaluation KW - Validation KW - Ultrasonic PY - 2025 DO - https://doi.org/10.7910/DVN/0HHJFF PB - Harvard College CY - Cambridge, MA, USA AN - OPUS4-63912 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Liepold, Philipp A1 - Kromm, Arne A1 - Kannengießer, Thomas T1 - Semantic Segmentation for Hot Cracking N2 - The images in this dataset are light microscope images of the surfaces of modified Varestraint-Transvarestraint test samples. The training images show the surface of a tungsten inert gas weld with possible hot cracks. The dataset is intended for use in training crack segmentation networks. This database consists of images in .png format. The training images were taken in 24-bit, 3-color channels with an optical light microscope (Keyence). The corresponding mask images are 8-bit grayscale images, where 255-valued pixels (white) denote crack areas and 0-valued pixels (black) denote non-cracked areas. This dataset was created manually with the help of a self-written segmentation program based on OpenCV. I used it to train networks based on ViT, ConvNeXt, U-Net, and EfficientNet architectures. The images were taken at magnifications of 50x and 100x. The dataset is structured as follows: Wire → Magnification (50, 100) → Data (train, mask = label) → Numbered images (1, 2, 3, …) (There may be missing numbers. The reasons are: 1) I did not take images of all surfaces if they were not cracked, and 2) the 100x magnification images were taken at a later point, by which time some samples had already been prepared for further evaluation, so no images could be taken.) For every image number in train, there is an equivalent number in mask with the same image size (but a different channel size, since train is 3-channel color and mask is single-channel). There is no fixed image size (h × w). If you want to train a network, I recommend either rescaling or taking sub-images for both the training and mask sets, or using architectures that can handle varying input sizes. The research project " Evaluation of design-induced solidification cracks during welding of high-strength fine-grained structural steels" is funded by the Federal Ministry of Economics and Climate Protection as part of the "Industrial Collective Research" programme on the basis of a resolution of the German Bundestag. This project IGF 01IF21837N FE 1 / P 1516 from the Research Association for steel Application (FOSTA), Düsseldorf, is carried out at Bundesanstalt für Materialforschung und -prüfung. KW - CNN KW - Segmentation KW - Hot cracking KW - AI PY - 2025 DO - https://doi.org/10.5281/zenodo.16919144 PB - Zenodo CY - Geneva AN - OPUS4-64031 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lisec, Jan T1 - fioRa N2 - R package providing a wrapper for the python module 'FIORA' as well as a 'shiny'-App to facilitate data processing and visualization. 'FIORA' allows to predict Mass-Spectra based on the SMILES code of chemical compounds. It is described in the Nature Communications article by Nowatzky et al. (2025). KW - Mass Spectrometry PY - 2025 UR - https://github.com/cran/fiora/ PB - GitHub CY - San Francisco AN - OPUS4-64663 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Bustamante, Joana A1 - Naik, Aakash A1 - Ueltzen, Katharina A1 - George, Janine A1 - Ertural, Christina T1 - Thermal Transport in Ag8TS6 (T= Si, Ge, Sn) Argyrodites: An Integrated Experimental, Quantum-Chemical, and Computational Modelling Study. DFT-part N2 - This repository contains computational data supporting the manuscript titled *“Thermal Transport in Ag8TS6 (T= Si, Ge, Sn) Argyrodites: An Integrated Experimental, Quantum-Chemical, and Computational Modelling Study”* It includes raw data for vibrational properties, elastic properties and Bonding analysis. KW - DFT KW - QHA KW - Lattice thermal conductivity KW - Grüneisen parameter PY - 2025 DO - https://doi.org/10.5281/zenodo.17399975 PB - Zenodo CY - Geneva AN - OPUS4-64671 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Bustamante, Joana A1 - Naik, Aakash A1 - Ueltzen, Katharina A1 - Ertural, Christina A1 - George, Janine T1 - Thermal Transport in Ag8TS6 (T= Si, Ge, Sn) Argyrodites: An Integrated Experimental, Quantum-Chemical, and Computational Modelling Study. N2 - This repository includes raw data for bonding analysis and lattice thermal conductivity using MLIP-MACE-MP03b, supporting the manuscript “Thermal Transport in Ag8TS6 (T= Si, Ge, Sn) Argyrodites: An Integrated Experimental, Quantum-Chemical, and Computational Modelling Study” KW - DFT KW - LOBSTER KW - Lattice thermal conductivity KW - MLIP PY - 2025 DO - https://doi.org/10.5281/zenodo.17397456 PB - Zenodo CY - Geneva AN - OPUS4-64674 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Stawski, Tomasz A1 - Miliute, Aiste T1 - Structural Refinement of ZrV₂O₇ with Negative Thermal Expansion Using Pair Distribution Function Analysis N2 - This repository contains Python scripts specifically developed for structural refinement of Zirconium Vanadate (ZrV₂O₇), a material known for its negative thermal expansion (NTE). The scripts implement Pair Distribution Function (PDF) analysis to refine crystal structures directly from experimental X-ray diffraction (XRD) data. The refinement workflow is built around the DiffPy-CMI library, enhanced with custom functionalities tailored for ZrV₂O₇ and similar oxide materials. KW - Zirconium vandate KW - Total scattering KW - Pair distribution function KW - Structure refinement PY - 2025 DO - https://doi.org/10.5281/zenodo.15395752 PB - Zenodo CY - Geneva AN - OPUS4-64750 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Grandel, Jonas T1 - Harmonic phonon dataset N2 - Phonon Dataset calculated with DFT PBE and the foundational MACE-MP-0b3 model. The data are presented and discussed in the following publication: https://doi.org/10.1063/5.0297006 KW - Phonon KW - MACE KW - DFT PY - 2025 UR - https://github.com/ACEsuit/mace-foundations PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-64747 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Nowatzky, Yannek T1 - Fiora: Source Data for Training and Testing N2 - This repository contains source data for training and testing the Fiora model (see GitHub and DOI: 10.5281/zenodo.14651774). As part of the Fiora study (Nowatzky et al., 2025), which introduces a GNN-based fragmentation algorithm for simulating MS/MS spectra, this dataset enables the reproduction of the study’s findings and the training of new spectral prediction models. KW - Bioinformatics KW - Mass spectrometry KW - Machine Learning PY - 2025 DO - https://doi.org/10.5281/zenodo.14782249 PB - Zenodo CY - Geneva AN - OPUS4-64587 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Li, Yong A1 - Hu, Kaixiong A1 - Lilleodden, Erica T. A1 - Huber, Norbert T1 - Datasets for structural and mechanical properties of nanoporous networks from FIB reconstruction N2 - This dataset includes 3D tomographic reconstruction image files, volume mesh files for finite element simulations, and data on the structural and mechanical properties of nanoporous gold (NPG) structures. It serves as a supplement to a dataset paper, with the corresponding DOI provided in the “Related Identifiers” section. Detailed descriptions of the data, as well as the procedures for their preparation and curation, are presented in that paper. The base material, nanoporous gold, was fabricated via a dealloying process and has a solid fraction of approximately 0.30. NPG samples with ligament sizes ranging from 20 nm to 400 nm were prepared through dealloying and subsequent thermal annealing. Tomographic TIFF files were obtained via Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) 3D reconstruction, with the procedure detailed in Philosophical Magazine (2016, 96(32–34), 3322–3335). Based on the 3D image data, new simulations and analyses were performed. The resulting structural and mechanical property data of nanoporous gold are reported for the first time in the dataset paper and are archived here. This dataset provides a valuable database for the study of nanoporous network materials and can be reused for numerical simulations, additive manufacturing, and machine learning applications within the materials science community. KW - Nanoporous gold KW - Dealloying KW - Coarsening KW - FIB/SEM tomography KW - Connectivity KW - Finite element KW - Volume mesh KW - Young’s modulus KW - Yield stress KW - Poisson’s ratio PY - 2025 DO - https://doi.org/10.15480/882.15230 PB - Technische Universität Hamburg Open Research CY - Hamburg AN - OPUS4-64534 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lecompagnon, Julien T1 - Thermographic Reference Dataset: Experimentally simulated Gaussian-shaped internal defects in GFRP N2 - We introduce a thermographic reference dataset consisting of 100 experimentally recorded temperature fields that replicate defect-like heat signatures in glass fiber reinforced polymer (GFRP) composites. Instead of relying on the fabrication of numerous damaged specimens, the dataset was generated by directly imprinting defect signatures onto an intact laminate using a near-infrared laser projector with spatial light modulation. The projected patterns are derived from parameterized Gaussian distributions, enabling systematic variation in defect size, shape, and orientation. The resulting steady-state thermal responses were captured with infrared thermography, providing high-resolution temperature distribution measurements for each case. This novel approach ensures that the heat transfer physics are preserved experimentally, while no special samples with different defects need to be manufactured to acquire datasets for different defect parameters. The dataset is ultimately designed as a resource for the benchmarking of thermographic non-destructive testing techniques, the validation of numerical heat transfer simulations, and the training of data-driven algorithms for defect detection in composite materials. KW - Thermography KW - Temperature KW - Composites KW - GFRP KW - Reference Data KW - Laser Projector KW - Nondestructive Testing PY - 2025 DO - https://doi.org/10.5281/zenodo.17378681 PB - Zenodo CY - Geneva AN - OPUS4-64472 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lisec, Jan A1 - Sommerfeld, Thomas A1 - Riedel, Juliane A1 - Mauch, Tatjana A1 - Koch, Matthias T1 - CRM BAM-B003 eCerto data file N2 - Data file (RData) containing measurement data recorded during the production process of the Certified Reference Material BAM-B003 containing per- and polyfluoroalkyl substances (PFAS) in textiles. The data can be most conveniently openend using the Shiny-App eCerto which is accessible at https://www.bam.de/eCerto. KW - Certified reference material KW - Mass spectrometry KW - PFAS PY - 2025 DO - https://doi.org/10.5281/zenodo.15907581 PB - Zenodo CY - Geneva AN - OPUS4-64544 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Fabry, Çağtay A1 - Hirthammer, Volker A1 - Scherer, Martin K. T1 - weldx-widgets: advanced visualisation and jupyter widgets for weldx N2 - This package provides advanced visualisation and interactive widgets for the weldx core package. KW - Weldx KW - Welding KW - Research data KW - Visualisation PY - 2025 DO - https://doi.org/10.5281/zenodo.17790485 PB - Zenodo CY - Geneva AN - OPUS4-64973 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Fabry, Çağtay T1 - pytcs: a TwinCAT Scope text export file reader N2 - A Python package for reading exported TwinCAT Scope Files. Export your TwinCAT Scope .svdx files to .txt/.csv and read them into Python. KW - Python KW - TwinCAT Scope KW - File reader KW - File format KW - Measurement data PY - 2025 DO - https://doi.org/10.5281/zenodo.17791125 PB - Zenodo CY - Geneva AN - OPUS4-64975 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Döring, Sarah T1 - Sequence of Mus Musculus monoclonal IgG2c anti-CCMV Immunoglobulin N2 - We report the full-length nucleotide and amino acid sequences of the light (κ) and heavy chain of the IgG2c anti-CCMV monoclonal antibody (hybridoma clone BAM-CCMV-29-81), generated against Cowpea Chlorotic Mottle Virus (CCMV). Sequencing of hybridoma clone was performed using a cost-effective Sanger-based workflow that includes DNA-level subclass determination and peptide mass fingerprint confirmation. The κ-chain sequence was assigned to IGKV4-6101 / IGKJ101, while the heavy chain was assigned to IGHV2-601 / IGHD1-101 / IGHJ3*01 with IgG2c constant regions from the NOD strain. Both chains were validated against RNA Illumina sequencing, confirming 100% identity. The sequences are available in GenBank under accession numbers PX123807 (κ-chain) and PX123808 (heavy chain). KW - Antibody Sequencing KW - BAM-CCMV-29-81 KW - anti-CCMV-antibody PY - 2025 UR - https://www.ncbi.nlm.nih.gov/nuccore/PX123807 UR - https://www.ncbi.nlm.nih.gov/nuccore/PX123808 PB - National Library of Medicine CY - Bethesda AN - OPUS4-63968 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Müller, Simon T1 - FireSpread_MedEU N2 - Wildfires are becoming more frequent and severe under the influence of climate change, posing increasing risks to ecosystems, human health, and infrastructure. Accurate spatiotemporal data on wildfire propagation is essential for advancing fire behavior modeling, improving management strategies, and mitigating future impacts. However, existing datasets with both high spatial and temporal resolution are rare, costly, and time-consuming to produce. To address this gap, we present FireSpread_MedEU, a dataset comprising 313 consecutive burned area maps from 102 wildfire events across the Mediterranean and Europe between 2017 and 2023. Burned areas were derived from high-resolution Planet optical satellite imagery (~3 m spatial, mostly daily temporal resolution) using a semi-automated workflow, followed by manual refinement to ensure highest accuracy. Each dataset entry is enriched with detailed metadata and a subjective quality assessment. With its high level of spatiotemporal precision, FireSpread_MedEU provides essential data for the development and validation of machine learning models or wildfire simulation models. It opens new research opportunities in wildfire behavior analysis, risk assessment, and predictive modeling. KW - Wildfire KW - Spread KW - Machine Learning PY - 2025 DO - https://doi.org/10.5281/zenodo.16813435 PB - Zenodo CY - Geneva AN - OPUS4-64768 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Ueltzen, Katharina A1 - Naik, Aakash A1 - Ertural, Christina A1 - Benner, Philipp A1 - George, Janine T1 - Software and data repository: Can simple exchange heuristics guide us in predicting magnetic properties of solids? N2 - Software and data for the publication "Can simple exchange heuristics guide us in predicting magnetic properties of solids?" Release that corresponds to the first preprint version of the article. Full Changelog: https://github.com/DigiMatChem/paper-exchange-heuristics-in-magnetic-materials/commits/v1.0.0 KW - Magnetism KW - Machine Learning KW - Materials Design KW - Chemically Complex Materials KW - Sustainable Materials Design PY - 2025 DO - https://doi.org/10.5281/zenodo.16811104 PB - Zenodo CY - Geneva AN - OPUS4-64672 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schreiber, Frank A1 - Kanaris, Orestis A1 - Nordholt, Niclas T1 - Consequences of benzalkonium chloride tolerance for selection dynamics and de novode novo resistance evolution driven by antibiotics N2 - Biocides are used in large amounts in industrial, medical, and domestic settings. Benzalkonium chloride (BAC) is a commonly used biocide, for which previous research revealed that Escherichia coli can rapidly adapt to tolerate BAC-disinfection, with consequences for antibiotic susceptibility. However, the consequences of BAC- tolerance for selection dynamics and resistance evolution to antibiotics remain unknown. Here, we investigated the effect of BAC -tolerance in E. coli on its response upon challenge with different antibiotics. Competition assays showed that subinhibitory concentrations of ciprofloxacin—but not ampicillin, colistin and gentamicin—select for the BAC-tolerant strain over the BAC-sensitive ancestor at a minimal selective concentration of 0.0013–0.0022 µg∙mL−1. In contrast, the BAC-sensitive ancestor was more likely to evolve resistance to ciprofloxacin, colistin and gentamicin than the BAC-tolerant strain when adapted to higher concentrations of antibiotics in a serial transfer laboratory evolution experiment. The observed difference in the evolvability of resistance to ciprofloxacin was partly explained by an epistatic interaction between the mutations conferring BAC -tolerance and a knockout mutation in ompF encoding for the outer membrane porin F. Taken together, these findings suggest that BAC -tolerance can be stabilized in environments containing low concentrations of ciprofloxacin, while it also constrains evolutionary pathways towards antibiotic resistance. KW - Antimicrobial surfaces KW - Biocides KW - Antimicrobial resistance KW - Antibiotics PY - 2025 UR - https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1282584 PB - National Library of Medicine CY - Bethesda AN - OPUS4-65221 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Chaurasia, Prashant Kumar A1 - Fabry, Çağtay A1 - Pittner, Andreas A1 - Rethmeier, Michael T1 - Tandem-GMAW: advanced pulsed and short cicuiting process mode experimental data N2 - This dataset consists of raw recordings for 5 Tandem gas metal arc welding experiments (Tandem-GMAW / T-GMAW). KW - T-GMAW KW - High power welding KW - Deposition efficiency KW - Life Cycle Assessment PY - 2025 DO - https://doi.org/10.5281/zenodo.17951724 PB - Zenodo CY - Geneva AN - OPUS4-65206 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Jafari, Abbas T1 - A python library for finite element (FE) modelling of static/quasi-static structural mechanics problems with legacy FEniCS N2 - This is a python library for finite element (FE) modelling of static/quasi-static structural mechanics problems with legacy FEniCS, which contains the following main modules. Module structure: for defining a structural mechanics experiment, including geometry, mesh, boundary conditions (BCs), and time-varying loadings. The time is quasi-static, i.e. no dynamic (inertia) effects will be accounted for in the problem module as follows. Module material: for handling constitutive laws such as elasticity, gradient damage, plasticity, etc. Module problem: for establishing structural mechanics problems for desired structures and material laws coming from the two above modules, and solving the problems built up. These can be performed for two main cases: static (no time-evolution) that also includes homogenization, and quasi-static (QS). KW - Finite element (FE) KW - Static/quasi-static structural mechanics KW - FEniCS PY - 2025 DO - https://doi.org/10.5281/zenodo.17805724 PB - Zenodo CY - Geneva AN - OPUS4-65269 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Jafari, Abbas A1 - Titscher, Thomas A1 - Robens-Radermacher, Annika T1 - Bayem: Implementation and derivation of “variational Bayesian inference for a nonlinear forward model [Chappell et al 2008]“ for arbitrary, user-defined model errors N2 - A python implementation of an analytical variational Bayes algorithm of "Variational Bayesian inference for a nonlinear forward model", Chappell, Michael A., Adrian R. Groves, Brandon Whitcher, and Mark W. Woolrich, IEEE Transactions on Signal Processing 57, no. 1 (2008): 223-236, with an updated free energy equation to correctly capture the log evidence. The algorithm requires a user-defined model error allowing an arbitrary combination of custom forward models and measured data. KW - Implementation KW - Variational Bayesian inference KW - Nonlinear forward model PY - 2025 DO - https://doi.org/10.5281/zenodo.17804665 PB - Zenodo CY - Geneva AN - OPUS4-65268 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Ávila Calderón, Luis A1 - Han, Ying A1 - Matzak, Kathrin A1 - Olbricht, Jürgen A1 - Skrotzki, Birgit T1 - NFDI-MatWerk/IUC02 data schema for elevated temperature tensile data of Ni-based superalloys N2 - Strength characteristics, such as proof strength and tensile strength, of metallic materials are usually measured at room temperature. However, for high-temperature materials, the values at operational temperatures are equally important for analyzing the mechanical behavior of components or for designing purposes. Elevated temperature tensile tests (often referred to as hot tensile tests) generally enable the measurement of the same material parameters as those obtained at room temperature. Typically, tensile and proof strength, elongation after fracture, and reduction of area are analyzed, with the focus often being on proof strength. The attached data schema for elevated temperature tensile tests was developed within the German NFDI-MatWerk initiative (https://nfdi-matwerk.de/). It builds on a previously published creep data schema and follows a reference data methodology that has also been previously outlined. The presented schema constitutes a structured approach for collecting all relevant information on an elevated temperature tensile test experiment. Overall, this development, as defined in the previously published data schema for creep data, aims to provide a comprehensive hierarchical data description that can be implemented in data management platforms (such as electronic laboratory notebooks), facilitate consistent quality assessment across different users and data providers, and promote the alignment of datasets to the FAIR principles by providing easy interoperability and full reusability. The presented schema was initially developed for datasets of Ni-based high-temperature alloys. However, thanks to its modular structure, it can also be applied to tensile tests of various metallic and other materials. Although the focus is on elevated temperature tensile testing, the data schema also offers a solid foundation for documenting room temperature tensile tests. In such cases, an adjustment of the requirement profile might be necessary, and categories or entries specific to mechanical testing at elevated temperatures, such as “temperature-measuring system”, “specified temperature”, or “soaking time”, become irrelevant. Overall, a detailed approach was followed to ensure the collection of all relevant information, including both metadata and test results. This includes, for example, comprehensive descriptions of the material’s manufacturing history and of the laboratory equipment, and basic strength and deformation characteristic values. The resulting data schema aims to support the description and identification of high-quality datasets, which may qualify as reference data of materials. Our current definition of reference data of materials has been published elsewhere. It should be noted, however, that not all research datasets —depending on their origin and purpose— require this full level of detail. Nevertheless, the presented data schema can support data providers in evaluating the completeness and value of their datasets. This version of the data schema covers elevated temperature tensile tests on both single- and polycrystalline specimen materials. The terminology is aligned with DIN EN ISO 6892-1 and DIN EN ISO 6892-2. It is designed to record the use of temperature measurement using thermocouples and the use of contacting extensometer systems. The requirement profile refers to the highest quality class of reference data, taken from calibrated instruments, and which shall enable the following usages: 1. Checking one's own elevated temperature tensile test results on nominally similar material 2. Verification of own testing set-up (e.g., by testing the same or a similar material) 3. Using the data as input data for simulations in the context of design or alloy development KW - NFDI MatWerk KW - Referenzdaten KW - Zugversuch KW - CMSX-6 KW - Datenschema KW - NFDI MatWerk KW - CMSX-6 KW - Data schema KW - Reference data KW - Tensile test PY - 2025 UR - https://doi.org/10.5281/zenodo.17846436 DO - https://doi.org/10.5281/zenodo.17846435 PB - Zenodo CY - Geneva AN - OPUS4-65190 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Jentzsch, Stefan A1 - Stock, Daniel A1 - Häcker, Ralf A1 - Skrotzki, Birgit A1 - Darvishi Kamachali, Reza A1 - Klingbeil, Dietmar A1 - Kindrachuk, Vitaliy T1 - Split Hopkinson Pressure Bar (SHPB) investigations of steel S355 specimens and complementary characterization methods N2 - The workbook SHPB_S355.xlsx contains in the main spreadsheet S355_TestOverview an overview on the S355 specimens, which were tested in Split Hopkinson Pressure Bar (SHPB) and complementary quasi-static (QS) tests. The tests were conducted with notched hat-shaped specimens without a notch offset (S355_TestOverview/column geometry: “no offset”) and a small notch offset of x=0.35 mm (S355_TestOverview/column geometry: “offset”), cf. Fig. 1 [1]. Furthermore, for selected specimens, links are provided to DIC and bar strain measurement files as well as to evaluations from further characterization methods (microhardness, EBSD). For the boundary conditions at the SHPB projectile impact, the pressures of the compressor p, driving the projectile, and the associated projectile impact velocities are provided in SHPB_S355.xlsx. The DIC displacement measurements are provided in FurtherMeasurements/DIC with frame output times in the file labels, which are associated with an imaginary trigger at the left end of the shortened incident bar (length 300 mm), which is considered within the SHPB simulation setup, see [1]. Furthermore, the DIC reference coordinate systems are provided as COS.jpg files in the respective DIC folders. Starting from the strain signals at the bars, captured by strain gauges at the incident (file name BC_Inc) and transmission bar (BC_Trans), displacement boundary conditions (which are provided for the tests in FurtherMeasurements/BarDisplBCs) are calculated by eq. (12) in [1], incorporating the acoustic velocity equal to 4639 m/s at the bars and a correction factor. Fig. 1 shows the shear specimen geometry (lengths in mm) with the offset of the notches x. For the quasi-static tests force(displacements)-values are directly provided in FurtherMeasurements/Fu_curves, which are considered from the relative displacements of the specimens, evaluated by DIC. The Vickers microhardness (HV 0.01) distribution across the shear localization zone was assessed by QNESS 60A+ EVO (DIN EN ISO 6507-1) for quasi-statically and dynamically tested specimens, applying the small notch offset, such that the specimens did not fail in the localization region. Therefore, raw data is provided in FurtherMeasurements/Microhardness. For fitting the microhardness distribution perpendicularly to the shear bands (as i.e. provided for the SHPB specimen in [1]), representative microhardness profiles were considered. Similarly for specimens with the small notch offset, EBSD data on dynamic and quasi-static tests is provided in FurtherMeasurements/EBSD. The grain size distributions for positions at the notch and the undeformed region are included in the subdirectory ./GrainLists_Shortened and EBSD images in the PowerPoint Presentations. Further information as the sizes and misorientations of the single grains, is incorporated in the subfolders ./GrainLists_FurtherInf. KW - Adiabatic shear bands KW - Split Hopkinson pressure bar KW - Digital image correlation PY - 2025 DO - https://doi.org/10.5281/zenodo.17591439 PB - Zenodo CY - Geneva AN - OPUS4-64842 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Habibimarkani, Heydar A1 - Prinz, Carsten A1 - Sahre, Mario A1 - Hodoroaba, Vasile-Dan A1 - Radnik, Jörg T1 - CV, TEM, XRD and XPS/HAXPES datasets of FeNi-based nanoparticles for the oxygen evolution reaction N2 - The datasets from Cyclic Voltammetry, Transmision Electron Microscopy, X-ray Diffraction, and (Hard Energy) X-ray Photoelectron Spectroscopy are related to the publication H. Habibimarkani, S.-L. Abram, A. Guilherme Buzanich, C. Prinz, M. Sahre, V.-D. Hodoroaba and J. Radnik "In-depth analysis of FeNi-based nanoparticles for the oxygen evolution reaction" Scientific Reports (2025), https://doi.org/10.1038/s41598-025-92720-3 Details of the materials and the experimental procedures are described in this publications. KW - Oxygen evolution reaction KW - Fe-Ni nanopartices KW - Comprehensive analysis PY - 2025 DO - https://doi.org/10.5281/zenodo.14975964 PB - Zenodo CY - Geneva AN - OPUS4-63335 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Han, Ying A1 - Schriever, Sina A1 - von Hartrott, Philipp A1 - Rockenhäuser, Christian A1 - Skrotzki, Birgit T1 - Dataset on the Creep Properties of EN AW-2618A Aluminum Alloy in the T61 and an overaged condition N2 - This publication contains comprehensive metadata and test results of constant force creep tests according to DIN EN ISO 204 on the aluminum alloy EN AW-2618A in the T61 condition (8 h/530 °C/quenching in boiling water followed by 28 h/195 °C/air cooling) and in an overaged condition (T61 + 1.000 h/190 °C). The test temperatures cover 160 °C, 180 °C, 190 °C, and 230 °C, and the initial stresses range between 40 MPa and 290 MPa. KW - Creep KW - Aging KW - Overaging KW - Aluminum alloy KW - EN AW-2618A KW - High temperature PY - 2025 DO - https://doi.org/10.5281/zenodo.15744297 PB - Zenodo CY - Geneva AN - OPUS4-63572 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Ávila Calderón, Luis Alexander A1 - Matzak, Kathrin A1 - Olbricht, Jürgen A1 - Dolabella Portella, Pedro A1 - Skrotzki, Birgit T1 - BAM Reference Data: High Temperature Tensile Data of Single-Crystal Ni-Based Superalloy CMSX-6 N2 - This publication provides comprehensive metadata and test results of tensile tests at elevated temperature according to DIN EN ISO 6892-2:2018-09 on the single crystal Ni-based superalloy CMSX-6 at T = 980 °C. The tests were performed in an ISO 17025-accredited test laboratory. The calibrations of measuring equipment are documented, meet the requirements of the measurement standard, and are metrologically traceable. The provided data were audited and are BAM reference data. KW - Digitalisierung KW - Referenzdaten KW - CMSX-6 KW - Zugversuch KW - NFDI-MatWerk KW - Ni-Basis-Superlegierung PY - 2025 DO - https://doi.org/10.5281/zenodo.17846616 PB - Zenodo CY - Geneva AN - OPUS4-65338 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Janssen, Jan A1 - George, Janine A1 - Geiger, Julian A1 - Bercx, Marnik A1 - Wang, Xing A1 - Ertural, Christina A1 - Schaarschmidt, Joerg A1 - Ganose, Alex M. A1 - Pizzi, Giovanni A1 - Hickel, Tilmann A1 - Neugebauer, Joerg T1 - A Python workflow definition for computational materials design N2 - Numerous Workflow Management Systems (WfMS) have been developed in the field of computational materials science with different workflow formats, hindering interoperability and reproducibility of workflows in the field. To address this challenge, we introduce here the Python Workflow Definition (PWD) as a workflow exchange format to share workflows between Python-based WfMS, currently AiiDA, jobflow, and pyiron. This development is motivated by the similarity of these three Python-based WfMS, that represent the different workflow steps and data transferred between them as nodes and edges in a graph. With the PWD, we aim at fostering the interoperability and reproducibility between the different WfMS in the context of Findable, Accessible, Interoperable, Reusable (FAIR) workflows. To separate the scientific from the technical complexity, the PWD consists of three components: (1) a conda environment that specifies the software dependencies, (2) a Python module that contains the Python functions represented as nodes in the workflow graph, and (3) a workflow graph stored in the JavaScript Object Notation (JSON). The first version of the PWD supports directed acyclic graph (DAG)-based workflows. Thus, any DAG-based workflow defined in one of the three WfMS can be exported to the PWD and afterwards imported from the PWD to one of the other WfMS. After the import, the input parameters of the workflow can be adjusted and computing resources can be assigned to the workflow, before it is executed with the selected WfMS. This import from and export to the PWD is enabled by the PWD Python library that implements the PWD in AiiDA, jobflow, and pyiron. KW - Automation KW - Workflows KW - Materials Design KW - Multi-scale simulation KW - Digitalization PY - 2025 DO - https://doi.org/10.5281/zenodo.15516179 PB - Zenodo CY - Geneva AN - OPUS4-63233 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Robens-Radermacher, Annika T1 - Dataset for publication: Characterization of temperature influence on the structural built-up of 3D concrete N2 - Implementation, data, and results for the generation of the study "Characterization of temperature influence on the structural built-up of 3D concrete". In this study, the influence of temperature on structural build-up is investigated. A significant temperature influence is demonstrated for three experimental setups (small amplitude oscillatory shear, constant shear rate, and small amplitude oscillatory extensional tests) using different materials. A common modeling framework capturing the time- and temperature evolution is derived based on the maturity approach. Two alternative formulations for the time evolution were proposed. Both models were calibrated using a probabilistic approach, allowing for uncertainty quantification. The calibrated models successfully predict the structural build-up under different ambient temperature conditions. KW - Structural build-up KW - 3D concrete printing KW - Modeling KW - Parameter identification KW - Temperature influence PY - 2025 DO - https://doi.org/10.5281/zenodo.15845818 PB - Zenodo CY - Geneva AN - OPUS4-64982 LA - eng 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 - GEN A1 - Pauw, Brian Richard T1 - Trinamic TMCL IOC for exposing Trinamics motor controllers to EPICS CA N2 - Trinamic TMCL IOC is a Python package designed for controlling stepper motors connected to a Trinamic board using the TMCL language (all boards supported by PyTrinamic should now work, has been tested on the TMCM 6110 and the TMCM 6214). Since it is implementing the TMCL protocol, it should be easy to adapt to other Trinamic motor controller boards. This package assumes the motor controller is connected over a machine network via a network-to-serial converter, but the underlying PyTrinamic package allows for other connections too. This allows the control of attached motors via the EPICS Channel-Access virtual communications bus. If EPICS is not desired, plain Pythonic control via motion_control should also be possible. An example for this will be provided in the example.ipynb Jupyter notebook. This package leverages Caproto for EPICS IOCs and a modified PyTrinamic library for the motor board control, and interfaces between the two via an internal set of dataclasses. Configuration for the motors and boards are loaded from YAML files (see tests/testdata/example_config.yaml). The modifications to PyTrinamic involved extending their library with a socket interface. This was a minor modification that should eventually find its way into the official package (a pull request has been submitted). KW - Instrumentation KW - Motor controller KW - EPICS KW - Channel access KW - Instrument control KW - Laboratory automation PY - 2024 DO - https://doi.org/10.5281/zenodo.10792593 PB - Zenodo CY - Geneva AN - OPUS4-59624 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Chaudhuri, Somsubhro A1 - Stamm, Michael T1 - Infrared thermography of turbulence patterns of operational wind turbine rotor blades supported with high-resolution photography: KI-VISIR Dataset N2 - With increasing wind energy capacity and installation of wind turbines, new inspection techniques are being explored to examine wind turbine rotor blades, especially during operation. A common result of surface damage phenomena (such as leading-edge erosion) is the premature transition of laminar to turbulent flow on the surface of rotor blades. In the KI-VISIR (Künstliche Intelligenz Visuell und Infrarot Thermografie – Artificial Intelligence-Visual and Infrared Thermography) project, infrared thermography is used as an inspection tool to capture so-called thermal turbulence patterns (TTP) that result from such surface contamination or damage. To compliment the thermographic inspections, high-resolution photography is performed to visualise, in detail, the sites where these turbulence patterns initiate. A convolutional neural network (CNN) was developed and used to detect and localise the turbulence patterns. A unique dataset combining the thermograms and visual images of operational wind turbine rotor blades has been provided, along with the simplified annotations for the turbulence patterns. Additional tools are available to allow users to use the data requiring only basic Python programming skills. KW - Reference Data KW - Infrared Thermography KW - Wind energy KW - Dataset PY - 2024 DO - https://doi.org/10.5281/zenodo.13771899 PB - Zenodo CY - Geneva AN - OPUS4-61102 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Friedrich, Alexander T1 - Simulation data for eddy current rail testing - simulation accuracy and evaluation uncertainty quantification N2 - This dataset serve to quantify the simulation error and the evaluation uncertainties in the context of eddy current rail testing. It was obtained during the AIFRI project (Artificial Intelligence for Rail Inspection) with the Faraday software by INTEGRATED Engineering Software, using its BEM Solver. KW - Non-destructive testing KW - Eddy current testing KW - Eddy current simulstion PY - 2024 DO - https://doi.org/10.5281/zenodo.13970374 PB - Zenodo CY - Geneva AN - OPUS4-61470 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Völker, Tobias A1 - Mensing, Friedrich A1 - Kruschwitz, Sabine T1 - Estimation of cement content in concrete by spatially resolved laser induced breakdown spectroscopy – Dataset N2 - This dataset includes both simulated and raw measurement data as detailed in the journal paper [1]. File names follow the format SampleNo_Type, where SampleNo corresponds to the sample identifier listed in Table 1, and Type specifies the data type: either syn (synthetic) or exp (experimental). For experimental data, a slice index is appended to the file name in the format SampleNo_Type_Slice, identifying the specific subsample. [1] https://doi.org/10.1016/j.cemconres.2024.107714 KW - LIBS KW - Spectroscopy KW - Cement content KW - Elemental mapping PY - 2024 DO - https://doi.org/10.5281/zenodo.14246581 PB - Zenodo CY - Geneva AN - OPUS4-62394 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Diercks, Philipp A1 - Robens-Radermacher, Annika A1 - Rosenbusch, Sjard Mathis A1 - Unger, Jörg F. A1 - Saif-Ur-Rehman, Saif-Ur-Rehman T1 - fenics-constitutive N2 - This software enables the use of nonlinear constitutive models with FEniCSx. KW - Constitutive models KW - FEniCSx KW - Fenics-constitutive PY - 2024 DO - https://doi.org/10.5281/zenodo.13364955 PB - Zenodo CY - Geneva AN - OPUS4-62114 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN 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, using the example of UMATs for viscoplastic models, we demonstrate how available user subroutines can be incorporated into the interface while maintaining computational performance of FEniCSx comparable to that of Abaqus. KW - Finite element method KW - Constitutive models KW - FEniCSx KW - UMAT KW - Rust KW - Python KW - C++ PY - 2024 DO - https://doi.org/10.5281/zenodo.13980988 PB - Zenodo CY - Geneva AN - OPUS4-62112 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Klewe, Tim A1 - Strangfeld, Christoph A1 - Ritzer, Tobias A1 - Kruschwitz, Sabine T1 - GPR Dataset of Moisture Measurements on Building Floors in Laboratory and On-Site N2 - Related work Laboratory Study: Combining Signal Features of Ground-Penetrating Radar to Classify Moisture Damage in Layered Building Floors https://doi.org/10.3390/app11198820 On-Site Study: TBA Doctoral Thesis: Non-destructive classification of moisture deterioration in layered building floors using ground penetrating radar https://doi.org/10.14279/depositonce-19306 Measurement Parameters The GPR measurements were carried out with the SIR 20 from GSSI and a 2 GHz antenna pair (bandwidth 1 GHz to 3 GHz) in common-offset configuration. Each B-Scan consists of N A-Scans, each including 512 samples of a 11 ns time window. Survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan No Gains were applied. Folder Description: Lab_dry, Lab_insulDamage, Lab_screedDamage - each contain 168 Measurements (B-Scans) in .csv on 84 dry floors, floors with insulation damage and screed damage. - each floor setup was measured twice on two orthogonal survey lines, indicated by _Line1_ and _Line2_ in the file name. - the file names encode the building floor setup e.g. CT50XP100 describes a 50 mm cement screed with 100 mm extruded polystyrene below - the material codes are CT: cement screed, CA: anhydrite screed, EP: expanded polystyrene, XP: extruded polystyrene, GW: glass wool, PS: perlites further information can be found in the publication https://doi.org/10.3390/app11198820 OnSite_ - 5 folders containing B-Scans on 5 different practical moisture damages - the building floor setup is encoded according to the lab with an additional measurement point numbering at the start and a damage case annotation at the end of the file name with _dry, _insulationDamage and_screedDamage File Description: B-Scans, Measurement files - no header - dimension: 512 x N data point with N beeing the number of A-Scans including 512 samples of a 11 ns time window. - survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan Moisture References - Moist_Reference of On-Site Locations include the columns MeasPoint: Measurement point, wt%Screed: moisture content of screed layer in mass percent; wt%Insul: moisture content of insulation layer in mass percent. References were obtained by drilling cores with 68 mm diameter in the center of each survey line. - Moist_Reference_Screed of Lab data include the columns Screed: Screed material and thickness in mm, wt%Screed moisture content of screed layer in mass percent - Moist Reference_Insul of Lab data include the columns Insulation: Insulation material and thickness in mm, water addition in l: water added to the insulation layer in liters, V%Insulation: water added to the insulation layer in volume percent, RH%: resulting relative humidy in the insulation layer during measurement. These References are only avaible for Lab measurements on insulation damages. KW - GPR KW - Material Moisture KW - Building Floors KW - Laboratory KW - On-Site PY - 2024 DO - https://doi.org/10.5281/zenodo.10776684 PB - Zenodo CY - Geneva AN - OPUS4-59609 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Strobl, Domninic T1 - PGD in thermal transient problems with a moving heat source – a sensitivity study on factors affecting accuracy and efficiency N2 - Thermal transient problems, essential in applications like welding and additive metal manufacturing, are characterized by a dynamic evolution of temperature. Accurately simulating these phenomena is often computationally expensive, thus limiting the application, e. g. for model parameter estimation or online process control. Model order reduction, a solution to preserve accuracy while reducing complexity, is explored. This paper addresses challenges in developing a reduced model using the Proper Generalized Decomposition (PGD) for transient thermal problems with a specific treatment of the moving heat source within the reduced model. Factors affecting accuracy, convergence, and computational cost, such as discretization methods (finite element and finite difference), a dimensionless formulation, the size of the heat source, and the inclusion of material parameters as additional PGD variables are examined across progressively complex examples. The results demonstrate the influence of these factors on the PGD model's performance and emphasize the importance of their consideration when implementing such models. For thermal examples it is demonstrated that a PGD model with a finite difference discretization in time, a dimensionless representation, a mapping for a moving heat source, and a spatial domain non-separation yields the best approximation to the full order model. KW - Additive manufacturing KW - Mapping for unseparable load KW - Model order reduction KW - Proper generalized decomposition KW - Sensitivity analysis KW - Thermal transient problem PY - 2024 DO - https://doi.org/10.5281/zenodo.10102489 PB - Zenodo CY - Geneva AN - OPUS4-62235 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Hertwig, Andreas A1 - Ermilova, Elena T1 - Optical constants of a single AlN layer on Si N2 - Spectroscopic ellipsometry was used to determine the thickness and dielectric function of a Aluminium Nitride (AlN) layer on a Si wafer. The layer was determined to be 170 nm thick. The layer was provided by AIXTRON and manufactured by means of MOVPE. The data was created using a M2000DI spectroscopic ellipsometer from Woollam Co. Inc. Analysis was done using the CompleteEASE software. The model used is a multi-peak oscillator model for the AlN layer. The data resembles common database values for the material AlN. KW - Aluminium nitride KW - Thin solid layers KW - Spectroscopic ellipsometry KW - Compund semiconductors KW - MOVPE PY - 2024 UR - https://zenodo.org/records/12743500 DO - https://doi.org/10.5281/zenodo.12743499 PB - Zenodo CY - Geneva AN - OPUS4-60661 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Diercks, Philipp A1 - Veroy, K. A1 - Robens-Radermacher, Annika A1 - Unger, Jörg F. T1 - Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction N2 - In this paper, a methodology for fine scale modeling of large scale linear elastic structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse scale is modelled by the use of an additive split of the displacement field, addressing applications without a clear scale separation. Local reduced spaces are constructed bysolving an oversampling problem with random boundary conditions. Herein, we inform the boundary conditions by a global reduced problem and compare our approach using physically meaningful correlated samples with existing approaches using uncorrelated samples. The local spaces are designed such that the local contribution of each subdomain can be coupled in a conforming way, which also preserves the sparsity pattern of standard finite element assembly procedures. Several numerical experiments show the accuracy and efficiency of the method, as well as its potential to reduce the size of the local spaces and the number of training samples compared to the uncorrelated sampling KW - Multiscale methods KW - Variational multiscale method KW - Localized model order reduction KW - Proper orthogonal PY - 2024 UR - https://arxiv.org/abs/2201.10374 DO - https://doi.org/10.48550/arXiv.2201.10374 PB - Arxiv; Cornell Tech CY - New York, NY AN - OPUS4-59803 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schiek, Manuela A1 - Minenkov, Alexey A1 - Hollweger, Sophia A1 - Duchoslav, Jiri A1 - Erdene-Ochir, Otgonbayar A1 - Weise, Matthias A1 - Ermilova, Elena A1 - Hertwig, Andreas T1 - Optical constants of In2O3-SnO2 (Indium tin oxide, ITO) N2 - Optical constants of In2O3-SnO2 (Indium tin oxide, ITO) Minenkov et al. 2024: on glass; n,k 0.191–1.69 µm Optical constants of In2O3-SnO2 (Indium tin oxide, ITO) Minenkov et al. 2024: on Si wafer, top; n,k 0.191–1.69 µm Optical constants of In2O3-SnO2 (Indium tin oxide, ITO) Minenkov et al. 2024: on Si wafer, bottom; n,k 0.191–1.69 µm KW - Indium Tin Oxide KW - Optical constants KW - Magnetron Sputtering KW - Electrochemical Degradation KW - Spectroscopic Ellipsometry PY - 2024 UR - https://refractiveindex.info/?shelf=other&book=In2O3-SnO2&page=Minenkov-glass UR - https://refractiveindex.info/?shelf=other&book=In2O3-SnO2&page=Minenkov-wafer-top UR - https://refractiveindex.info/?shelf=other&book=In2O3-SnO2&page=Minenkov-wafer-bottom PB - Refractiveindex.info AN - OPUS4-59766 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Diercks, Philipp A1 - Gläser, D. A1 - Lünsdorf, O. A1 - Selzer, M. A1 - Flemisch, B. A1 - Unger, Jörg F. T1 - Evaluation of tools for describing, reproducing and reusing scientific workflows N2 - In the field of computational science and engineering, workflows often entail the application of various software, for instance, for simulation or pre- and postprocessing. Typically, these components have to be combined in arbitrarily complex workflows to address a specific research question. In order for peer researchers to understand, reproduce and (re)use the findings of a scientific publication, several challenges have to be addressed. For instance, the employed workflow has to be automated and information on all used software must be available for a reproduction of the results. Moreover, the results must be traceable and the workflow documented and readable to allow for external verification and greater trust. In this paper, existing workflow management systems (WfMSs) are discussed regarding their suitability for describing, reproducing and reusing scientific workflows. To this end, a set of general requirements for WfMSswere deduced from user stories that we deem relevant in the domain of computational science and engineering. On the basis of an exemplary workflow implementation, publicly hosted at GitHub (https:// this http URL), a selection of different WfMSs is compared with respect to these requirements, to support fellow scientists in identifying the WfMSs that best suit their requirements. KW - FAIR KW - Reproducibility, scientific workflow KW - Tool comparison KW - Workflow management PY - 2024 UR - https://arxiv.org/abs/2211.06429 DO - https://doi.org/10.48550/arXiv.2211.06429 PB - Arxiv; Cornell Tech CY - New York, NY AN - OPUS4-59804 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Ueltzen, Katharina A1 - George, Janine T1 - Bonding analysis results for "Chemical ordering and magnetism in face-centered cubic CrCoNi alloy" N2 - This repository contains the code and data to produce the results of chapter IIIC. Covalent bonding analysis for L12/L10 type configurations of the publication Chemical ordering and magnetism in face-centered cubic CrCoNi alloy by Sheuly Ghosh et al. KW - Magnetism KW - Bonding Analysis KW - Medium Entropy Alloys PY - 2024 DO - https://doi.org/10.5281/zenodo.11104874 PB - Zenodo CY - Geneva AN - OPUS4-59987 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - DACHS/MOFs/AutoMOFs_2/Synthesis N2 - The DACHS (Database for Automation, Characterization and Holistic Synthesis) project aims to create completely traceable experimental data, covering syntheses, measurements, analyses, and interpretations. DACHS_MOFs focuses on the synthesis and characterisation of metal-organic frameworks, across multiple, automation-assisted experimental series (AutoMOFs), with the overall goal of producing reproducible MOF samples through tracking of the synthesis parameters. DACHS_MOFs is simultaneously used to test the DACHS principles. This upload contain synthesis data from AutoMOFs_2 in HDF5 format (.h5). Each .h5 file contains detailed information on the chemical, experimenal, and synthesis parameters used during the synthesis of a single AutoMOF sample. KW - Automation KW - Procedure KW - Synthesis KW - Traceability PY - 2024 DO - https://doi.org/10.5281/zenodo.11236074 PB - Zenodo CY - Geneva AN - OPUS4-60611 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - DACHS/MOFs/AutoMOFs_3/Synthesis N2 - The DACHS (Database for Automation, Characterization and Holistic Synthesis) project aims to create completely traceable experimental data, covering syntheses, measurements, analyses, and interpretations. DACHS_MOFs focuses on the synthesis and characterisation of metal-organic frameworks, across multiple, automation-assisted experimental series (AutoMOFs), with the overall goal of producing reproducible MOF samples through tracking of the synthesis parameters. DACHS_MOFs is simultaneously used to test the DACHS principles. This upload contain synthesis data from AutoMOFs_3 in HDF5 format (.h5). Each .h5 file contains detailed information on the chemical, experimenal, and synthesis parameters used during the synthesis of a single AutoMOF sample. KW - Synthesis KW - Automation KW - Traceability KW - Procedure PY - 2024 DO - https://doi.org/10.5281/zenodo.11237815 PB - Zenodo CY - Geneva AN - OPUS4-60633 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - DACHS/MOFs/AutoMOFs_1/Synthesis N2 - The DACHS (Database for Automation, Characterization and Holistic Synthesis) project aims to create completely traceable experimental data, covering syntheses, measurements, analyses, and interpretations. DACHS_MOFs focuses on the synthesis and characterisation of metal-organic frameworks, across multiple, automation-assisted experimental series (AutoMOFs), with the overall goal of producing reproducible MOF samples through tracking of the synthesis parameters. DACHS_MOFs is simultaneously used to test the DACHS principles. This upload contain synthesis data from AutoMOFs_1 in HDF5 format (.h5). Each .h5 file contains detailed information on the chemical, experimenal, and synthesis parameters used during the synthesis of a single AutoMOF sample. KW - Synthesis KW - Automation KW - Traceability KW - Procedure PY - 2024 DO - https://doi.org/10.5281/zenodo.11236031 PB - Zenodo CY - Geneva AN - OPUS4-60243 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob A1 - Moeez, A. A1 - Hörmann, Anja A1 - Breßler, Ingo T1 - Example configurations and test cases for the Python HDF5Translator framework. N2 - This is a set of use examples for the HDF5Translator framework. This framework lets you translate measurement files into a different (e.g. NeXus-compatible) structure, with some optional checks and conversions on the way. For an in-depth look at what it does, there is a blog post here. The use examples provided herein are each accompanied by the measurement data necessary to test and replicate the conversion. The README.md files in each example show the steps necessary to do the conversion for each. We encourage those who have used or adapted one or more of these exampes to create their own conversion, to get in touch with us so we may add your example to the set. KW - Measurement data conversion KW - Data conversion KW - HDF5 KW - NeXus KW - NXsas KW - Framework KW - Python PY - 2024 DO - https://doi.org/10.5281/zenodo.10925971 PB - Zenodo CY - Geneva AN - OPUS4-59796 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob A1 - Hörmann, Anja A1 - Moeez, Abdul A1 - Breßler, Ingo T1 - BAMresearch/HDF5Translator: A Framework for translating and transforming data between HDF5 files N2 - HDF5Translator is a Python framework for translating and transforming data between HDF5 files. It supports operations like unit conversion, dimensionality adjustments, and subtree copying, making it suitable for managing and manipulating a wide range of scientific datasets. KW - Measurement data conversion KW - Data conversion KW - HDF5 KW - NeXus KW - NXsas KW - Framework KW - Python KW - Methodology PY - 2024 DO - https://doi.org/10.5281/zenodo.10927639 PB - Zenodo CY - Geneva AN - OPUS4-59797 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -