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 -