TY - GEN A1 - Schoonjans, Tom A1 - Brunetti, A. A1 - Golosio, B. A1 - Sanchez del Rio, M. A1 - Solé, V. A. A1 - Ferrero, C. A1 - Vincze, L. T1 - xraylib 3.1.0 N2 - Quantitative estimate of elemental composition by spectroscopic and imaging techniques using X-ray fluorescence requires the availability of accurate data of X-ray interaction with matter. Although a wide number of computer codes and data sets are reported in literature, none of them is presented in the form of freely available library functions which can be easily included in software applications for X-ray fluorescence. This work presents a compilation of data sets from different published works and an xraylib interface in the form of callable functions. Although the target applications are on X-ray fluorescence, cross sections of interactions like photoionization, coherent scattering and Compton scattering, as well as form factors and anomalous scattering functions, are also available. xraylib provides access to some of the most respected databases of physical data in the field of x-rays. The core of xraylib is a library, written in ANSI C, containing over 40 functions to be used to retrieve data from these databases. This C library can be directly linked with any program written in C, C++ or Objective-C. Furthermore, the xraylib package contains bindings to several popular programming languages: Fortran 2003, Perl, Python, Java, IDL, Lua, Ruby, PHP and .NET, as well as a command-line utility which can be used as a pocket-calculator. Although not officially supported, xraylib has been reported to be useable from within Matlab and LabView. The source code is known to compile and run on the following platforms: Linux, Mac OS X, Solaris, FreeBSD and Windows. Development occurs on Github: http://github.com/tschoonj/xraylib Downloads are hosted by the X-ray Micro-spectroscopy and Imaging research group of Ghent University: http://lvserver.ugent.be/xraylib Version 3.1.0 release notes: - Database of commonly used radionuclides for X-ray sources added (new API: GetRadioNuclideDataByName, GetRadioNuclideDataByIndex, GetRadioNuclideDataList and FreeRadioNuclideData) - numpy Python bindings added, generated with Cython. Performance basically the same as the core C library. (suggested by Matt Newville) - docstring support added to Python bindings (suggested by Matt Newville) - Windows SDKs now have support for Python 3.4. - Windows 64-bit SDK now comes with IDL bindings - Confirmed support for LabView (thanks to Dariush Hampai!) - Universal Intel 32/64 bit Framework built for Mac OS X - Perl support for Debian/Ubuntu - Several bugfixes: thanks to those that reported them! KW - Quantitative estimation KW - Elemental composition KW - Spectroscopic techniques KW - Imaging techniques PY - 2014 DO - https://doi.org/10.5281/zenodo.12378 PB - Zenodo CY - Geneva AN - OPUS4-51924 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Radnik, Jörg A1 - Chemello, Giovanni A1 - Knigge, Xenia A1 - Al-Sabbgh, Dominik A1 - Hodoroaba, Vasile-Dan T1 - XPS, HAXPES, XRD and SEM datasets of functionalized graphene nanoplateletes N2 - The datasets from (Hard Energy) X-ray photoelectron spectroscopy, X-ray diffraction and Scanning Electron Microsopy are related to the publication G. Chemello, X. Knigge, D. Ciornii, B.P. Reed, A.J. Pollard, C.A. Clifford, T. Howe, N. Vyas, V.-D. Hodoroaba, J. Radnik "Influence of the morphology on the functionalization of graphene nanoplatelets analyzed by comparative photoelectron spectroscopy with soft and hard X-rays" Advanced Materials Interfaces (2023), DOI: 10.1002/admi.202300116. KW - Graphene related 2D materials KW - X-ray photoelectron spectroscopy KW - Hard-energy X-ray photoelectron spectroscopy KW - Scanning electron microscopy KW - Powder X-ray diffraction PY - 2023 DO - https://doi.org/10.5281/zenodo.7956497 PB - Zenodo CY - Geneva AN - OPUS4-57898 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schoonjans, Tom A1 - Vincze, L. A1 - Solé, V. A. A1 - Sanchez del Rio, M. A1 - Brondeel, P. A1 - Silversmit, G. A1 - Appel, K. A1 - Ferrero, C. T1 - XMI-MSIM 5.0 N2 - XMI-MSIM is an open source tool designed for predicting the spectral response of energy-dispersive X-ray fluorescence spectrometers using Monte-Carlo simulations. It comes with a fully functional graphical user interface in order to make it as user friendly as possible. Considerable effort has been taken to ensure easy installation on all major platforms. Development of this package was part of my PhD thesis. The algorithms were inspired by the work of my promotor Prof. Laszlo Vincze of Ghent University. Links to his and my own publications can be found in our manual. A manuscript has been published in Spectrochimica Acta Part B that covers the algorithms that power XMI-MSIM. Please include a reference to this publication in your own work if you decide to use XMI-MSIM for academic purposes. A second manuscript was published that covers our XMI-MSIM based quantification plug-in for PyMca. Soon information on using this plug-in will be added to the manual. XMI-MSIM is released under the terms of the GPLv3. Development occurs at Github: http://github.com/tschoonj/xmimsim Downloads are hosted by the X-ray Micro-spectroscopy and Imaging research group of Ghent University: http://lvserver.ugent.be/xmi-msim Version 5.0 release notes: Changes: 1. Custom detector response function: build a own plug-in containing your own detector response function and load it at run-time to override the builtin routines. Instructions can be found in the manual. 2. Escape peak improvements: new algorithm is used to calculate the escape peak ratios based on a combined brute-force and variance-reduction approach. Ensures high accuracy even at high incoming photon energies and thin detector crystals. Downside: it's slower… 3. Removed maximum convolution energy option. Was a bit confusing anyway. 4. Number of channels: moved from simulation controls into input-file 5. Radionuclide support added: Now you can select one or more commonly used radionuclide sources from the X-ray sources widget. 6. Advanced Compton scattering simulation: a new alternative implementation of the Compton scattering has been implemented based on the work of Fernandez and Scot (http://dx.doi.org/10.1016/j.nimb.2007.04.203), which takes into account unpopulated atomic orbitals. Provides an improved simulation of the Compton profile, as well as fluorescence contributions due to Compton effect (extremely low!), but slows the code down considerably. Advanced users only. Default: OFF 7. Plot spectra before convolution in results 8. Windows: new Inno Setup installers. Contains the headers and import libraries 9. Windows: compilers changed to GCC 4.8.1 (TDM-GCC) 10. Windows: rand_s used to generate seeds on 64-bit version (requires Vista or later) 11. Windows: new gtk runtime for the 64-bit version (see also https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer) 12. Mac OS X: compilers changed to clang 5.1 (Xcode) and gfortran 4.9.1 (MacPorts) 13. Original input-files from our 2012 publication (http://dx.doi.org/10.1016/j.sab.2012.03.011) added to examples 14. Updater performs checksum verification after download 15. X-ray sources last used values stored in preferences.ini 16. xmimsimdata.h5 modified: even bigger now... Bugfixes: 1. Windows: support for usernames with unicode characters. Fixed using customized builds of HDF5. Thanks to Takashi Omori of Techno-X for the report! 2. Spectrum import from file fixes. Was never properly tested apparently Note: For those that compiled XMI-MSIM from source: you will need to regenerate the xmimsimdata.h5 file with xmimsim-db. Old versions of this file will not work with XMI-MSIM 5.0. KW - Spectral response KW - Energy-dispersive X-ray fluorescence spectrometers KW - Monte-Carlo simulations PY - 2014 DO - https://doi.org/10.5281/zenodo.12381 PB - Zenodo CY - Geneva AN - OPUS4-51925 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schumacher, David A1 - Waske, Anja T1 - XCT data of metallic feedstock powder with pore size analysis N2 - X-Ray computed tomography (XCT) scan of 11 individual metallic powder particles, made of (Mn,Fe)2(P,Si) alloy. The data set consists of 4 single XCT scans which have been stitched together [3] after reconstruction. The powder material is an (Mn,Fe)2(P,Si) alloy with an average density of 6.4 g/cm³. The particle size range is about 100 - 150 µm with equivalent pore diameters up to 75 µm. The powder and the metallic alloy are described in detail in [1, 2]. KW - Additive Manufacturing KW - Feedstock powder KW - Powder Characterization KW - X-Ray Computed Tomography PY - 2022 DO - https://doi.org/10.5281/zenodo.5796487 PB - Zenodo CY - Geneva AN - OPUS4-55556 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob T1 - X-ray scattering Datasets of gold and silver nanoparticle composites, relating to the publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup" N2 - Wide-range X-ray scattering datasets and analyses for all samples described in the 2020 publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup". These datasets are composed by combining multiple small-angle x-ray scattering and wide-angle x-ray scattering curves into a single dataset. They have been analyzed using McSAS to extract polydispersities and volume fractions. They have been collected using the MOUSE project (instrument and methodology). KW - X-ray scattering KW - MOUSE KW - Saxs KW - Waxs KW - Analyses KW - Datasets PY - 2022 DO - https://doi.org/10.5281/zenodo.7193859 PB - Zenodo CY - Geneva AN - OPUS4-55979 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard A1 - Kolmangadi, Mohamed Aejaz T1 - X-ray scattering datasets associated with the publication "Side chain length dependent dynamics and conductivity in self assembled ion channels" N2 - X-ray scattering datasets for samples described in the 2022 publication "Side chain length dependent dynamics and conductivity in self assembled ion channels". This dataset includes both raw and processed X-ray scattering data for samples ILC8, ILC10, ILC12, ILC14 and ILC16 alongside background measurement files (BKG). KW - X-ray scattering KW - SAXS KW - MOUSE KW - Columnar ionic liquid crystals KW - Liquid crystals PY - 2023 DO - https://doi.org/10.5281/zenodo.7621358 PB - Zenodo CY - Geneva AN - OPUS4-56973 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard A1 - Kolmangadi, Mohamed Aejaz T1 - X-ray scattering datasets associated with the publication "Molecular Mobility of Polynorbornenes with Trimethylsiloxysilyl side groups: Influence of the Polymerization Mechanism" N2 - X-ray scattering datasets for samples described in the 2022 publication "Molecular Mobility of Polynorbornenes with Trimethylsiloxysilyl side groups: Influence of the Polymerization Mechanism". This dataset includes both raw and processed X-ray scattering data for samples APTCN and MPTCN, alongside background measurements files (BKG). KW - X-ray scattering KW - SAXS KW - MOUSE KW - Membrane polymers KW - Microporous polymers PY - 2023 DO - https://doi.org/10.5281/zenodo.7621204 PB - Zenodo CY - Geneva AN - OPUS4-56972 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard A1 - Kolmangadi, Mohamed Aejaz T1 - X-ray scattering datasets associated with the publication "Molecular Dynamics of Janus Polynorbornenes: Glass Transitions and Nanophase Separation" N2 - X-ray scattering datasets for samples described in the 2020 publication "Molecular Dynamics of Janus Polynorbornenes: Glass Transitions and Nanophase Separation". This dataset includes both raw and processed X-ray scattering data for samples PTCHSiO-Pr, Bu, Hx, Oc and De, alongside background measurements files (BKG). This data was collected using the MOUSE project (instrument and methodology). KW - X-ray scattering KW - SAXS KW - MOUSE KW - Alkyls KW - Polymers PY - 2023 DO - https://doi.org/10.5281/zenodo.7614835 PB - Zenodo CY - Geneva AN - OPUS4-56971 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Hahn, Marc Benjamin A1 - Hallier, Dorothea C. A1 - Seitz, H. T1 - X-ray scattering datasets and simulations associated with the publication "Bio-SAXS of single-stranded DNA-binding proteins: Radiation protection by the compatible solute ectoine" N2 - This dataset contains the processed and analysed small-angle X-ray scattering data associated with all samples from the publications "Bio-SAXS of Single-Stranded DNA-Binding Proteins: Radiation Protection by the Compatible Solute Ectoine" (https://doi.org/10.1039/D2CP05053F). Files associated with McSAS3 analyses are included, alongside the relevant SAXS data, with datasets labelled in accordance to the protein (G5P), its concentration (1, 2 or 4 mg/mL), and if Ectoine is present (Ect) or absent (Pure). PEPSIsaxs simulations of the GVP monomer (PDB structure: 1GV5 ) and dimer are also included. TOPAS-bioSAXS-dosimetry extension for TOPAS-nBio based particle scattering simulations can be obtained from https://github.com/MarcBHahn/TOPAS-bioSAXS-dosimetry which is further described in https://doi.org/10.26272/opus4-55751. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under grant number 442240902 (HA 8528/2-1 and SE 2999/2-1). We acknowledge Diamond Light Source for time on Beamline B21 under Proposal SM29806. This work has been supported by iNEXT-Discovery, grant number 871037, funded by the Horizon 2020 program of the European Commission. KW - SAXS KW - Radiation protection KW - Microdosimetry KW - G5P KW - Ectoine KW - DNA-Binding protein PY - 2023 DO - https://doi.org/10.5281/zenodo.7515394 PB - Zenodo CY - Geneva AN - OPUS4-56811 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 A1 - Hirthammer, Volker A1 - Scherer, Martin K. T1 - weldx - welding data exchange format N2 - Scientific welding data covers a wide range of physical domains and timescales and are measured using various different sensors. Complex and highly specialized experimental setups at different welding institutes complicate the exchange of welding research data further. The WelDX research project aims to foster the exchange of scientific data inside the welding community by developing and establishing a new open source file format suitable for the documentation of experimental welding data and upholding associated quality standards. In addition to fostering scientific collaboration inside the national and international welding community an associated advisory committee will be established to oversee the future development of the file format. The proposed file format will be developed with regard to current needs of the community regarding interoperability, data quality and performance and will be published under an appropriate open source license. By using the file format objectivity, comparability and reproducibility across different experimental setups can be improved. KW - Welding KW - Research data management KW - Open science KW - Open Data KW - WelDX PY - 2021 DO - https://doi.org/10.5281/zenodo.6563282 PB - Zenodo CY - Geneva AN - OPUS4-55226 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Völker, Christoph T1 - WEBSLAMD N2 - The objective of SLAMD is to accelerate materials research in the wet lab through AI. Currently, the focus is on sustainable concrete and binder formulations, but it can be extended to other material classes in the future. 1. Summary Leverage the Digital Lab and AI optimization to discover exciting new materials Represent resources and processes and their socio-economic impact. Calculate complex compositions and enrich them with detailed material knowledge. Integrate laboratory data and apply it to novel formulations. Tailor materials to the purpose to achieve the best solution. Workflow Digital Lab Specify resources: From base materials to manufacturing processes – "Base" enables a detailed and consistent description of existing resources Combine resources: The combination of base materials and processes offers an almost infinite optimization potential. "Blend" makes it easier to design complex configurations. Digital Formulations: With "Formulations" you can effortlessly convert your resources into the entire spectrum of possible concrete formulations. This automatically generates a detailed set of data for AI optimization. AI-Optimization Materials Discovery: Integrate data from the "Digital Lab" or upload your own material data. Enrich the data with lab results and adopt the knowledge to new recipes via artificial intelligence. Leverage socio-economic metrics to identify recipes tailored to your requirements. KW - Materials informatics KW - Scientific software KW - Sequential learning PY - 2022 UR - https://github.com/BAMresearch/WEBSLAMD DO - https://doi.org/10.26272/opus4-56640 PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-56640 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Vickers test ontology (VTO) N2 - Vickers Test Ontology (VTO) has developed for representing the Vickers testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6507-1 standard. Versions info: V2 developed using BFO+CCO top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/vickers-hardness-test GitHub: https://github.com/HosseinBeygiNasrabadi/Vickers-Test-Ontology-VTO- MatPortal: https://matportal.org/ontologies/VTO IndustryPortal: https://industryportal.enit.fr/ontologies/VTO KW - Ontology KW - Knowledge graph KW - Data mapping KW - Vickers hardness KW - FAIR data. PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/vickers-hardness-test UR - https://github.com/HosseinBeygiNasrabadi/Vickers-Test-Ontology-VTO- UR - https://matportal.org/ontologies/VTO UR - https://industryportal.enit.fr/ontologies/VTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60544 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 - Kern, Simon A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Müller, S. A1 - Maiwald, Michael A1 - Kowarik, Stefan T1 - Training data of quantitative online NMR spectroscopy for artificial neural networks N2 - Data set of low-field NMR spectra of continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). 1H spectra (43 MHz) were recorded as single scans. Two different approaches for the generation of artificial neural networks training data for the prediction of reactant concentrations were used: (i) Training data based on combinations of measured pure component spectra and (ii) Training data based on a spectral model. Synthetic low-field NMR spectra First 4 columns in MAT-files represent component areas of each reactant within the synthetic mixture spectrum. Xi (“pure component spectra dataset”) Xii (“spectral model dataset”) Experimental low-field NMR spectra from MNDPA-Synthesis This data set represents low-field NMR-spectra recorded during continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). Reference values from high-field NMR results are included. KW - NMR spectroscopy KW - Real-time process monitoring KW - Artificial neural networks KW - Online NMR spectroscopy KW - Automation KW - Process industry PY - 2020 DO - https://doi.org/10.5281/zenodo.3677139 PB - Zenodo CY - Geneva AN - OPUS4-50456 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Hahn, Marc Benjamin T1 - TOPAS cell model with nanoparticles N2 - These files contain cell models for TOPAS/Geant4 and the inclusion of nano particles in particle scattering simulations. A simple spherical cell with nanoparticles can be generated in a fast manner. The user has the option to include the following organelles: nucleus, mitochondria, cell membrane. Additionally nanoparticles can be included in the cytosol and at the surface of the nucleus and/or the mitochondria. The C++ classes in this repository extend the functionality of the TOPAS (http://www.topasmc.org/) Monte-Carlo program, which is itself a wrapper of the Geant4 MCS Toolkit (http://geant4.org). The sourcecode together with examples and scorers are provided. "If you use this extension please cite the following literature: Hahn, M.B., Zutta Villate, J.M. "Combined cell and nanoparticle models for TOPAS to study radiation dose enhancement in cell organelles." Sci Rep 11, 6721 (2021). https://doi.org/10.1038/s41598-021-85964-2 " KW - Monte-Carlo simulation KW - MCS KW - Geant4 KW - TOPAS KW - TOPAS-nBio KW - Dosimetry KW - Nanoparticles KW - Nanoparticle KW - AuNP KW - Gold KW - Microdosimetry KW - Targeted nanoparticle KW - Simulation KW - Particle scattering KW - Cell KW - Nucleus KW - Mitochondria KW - Cancer therapy KW - Radiation therapy PY - 2020 UR - https://github.com/BAMresearch/TOPAS-CellModels UR - https://github.com/MarcBHahn/TOPAS-CellModels DO - https://doi.org/10.26272/opus4-51150 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-51150 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 - 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 - Pauw, Brian Richard T1 - The SPONGE v.1.0.0: Modeling scattering of shapes by STL input, with absolute intensities and size distribution. N2 - Simulates X-ray and Neutron scattering patterns from arbitrary shapes defined by STL files. Features: - Uses multithreading to compute a number of independent solutions, then uses the variance of the results to estimate an uncertainty on the output. - Can be launched from the command line using an excel sheet to define settings, or from a jupyter notebook. - Outputs scattering patterns in absolute units if the contrast is set. - A Gaussian size distribution is available, where the relative scaling of objects for each repetion can be varied. Recommended to be used with limited width (max. 10%) to avoid artefacts. - Writes results with settings to an archival HDF5 file. Application examples: This software has been used in several studies to date. For example, it has been used here to simulate a model scattering pattern for a cuboid shape, which was then fed forward into the McSAS3 analysis program for analyzing scattering patterns of polydisperse cuboids. A second use is here, where it was used for the modeling of flattened helices. In this paper, scattering pattern features could be matched with particular morphological changes in the structure. Lastly, this paper has an example where it was used to validate the analytical analysis model, and explore the realistic limits of application of the analytical model. KW - Software KW - Scattering pattern analysis KW - Scattering pattern simulation KW - X-ray KW - Neutron KW - Command-line interface KW - Scattering pattern KW - STL file input KW - Python KW - Arbitrary shapes PY - 2023 DO - https://doi.org/10.6084/m9.figshare.21857130.v1 PB - Digital Science CY - Cambridge, MA, USA AN - OPUS4-56815 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Fritzsche, Sven A1 - Pauw, Brian Richard A1 - Weimann, Christiane A1 - Sturm, Heinz T1 - Test artifact for fs-LDW N2 - Data to generate the given graphs in the publication as well as raw images of the shown images. KW - stl code KW - Images KW - Graphs KW - Data PY - 2023 DO - https://doi.org/10.5281/zenodo.7671945 PB - Zenodo CY - Geneva AN - OPUS4-58096 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schilling, Markus T1 - Tensile Test Ontology (TTO) N2 - This is the stable version 2.0.1 of the PMD ontology module of the tensile test (Tensile Test Ontology - TTO) as developed on the basis of the 2019 standard ISO 6892-1: Metallic materials - Tensile Testing - Part 1: Method of test at room temperature. The TTO was developed in the frame of the PMD project. The TTO provides conceptualizations valid for the description of tensile test and corresponding data in accordance with the respective standard. By using TTO for storing tensile 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 will 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 TTO facilitates data retrieval and downstream usage. Due to a close connection to the mid-level PMD core ontology (PMDco), the interoperability of tensile test data is enhanced and data querying in combination with other aspects and data within the broad field of material science and engineering (MSE) is facilitated. The TTO class structure forms a comprehensible and semantic layer for unified storage of data generated in a tensile test including the possibility to record data from analysis, re-evaluation and re-use. Furthermore, extensive metadata allows to assess data quality and reproduce experiments. Following the open world assumption, object properties are deliberately low restrictive and sparse. KW - Ontology KW - Tensile Test KW - Digitalization KW - Plattform MaterialDigital KW - Structured Data PY - 2023 UR - https://github.com/MarkusSchilling/application-ontologies/blob/479311832819af695a2c64fa8eb772f2da398061/tensile_test_ontology_TTO/pmd_tto.ttl UR - https://github.com/materialdigital/core-ontology/blob/59f5727b0437ceea5e3d9fcb8fcd0ac211e92cc3/pmd_tto.ttl PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-57935 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Tensile test ontology (TTO) N2 - Tensile Test Ontology (TTO) has developed for representing the Tensile testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6892-1 standard. Versions info: V2 developed using BFO+CCO top-level ontologies. V3 developed using PROVO+PMDco top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/tensile-test GitHub: https://github.com/HosseinBeygiNasrabadi/Tensile-Test-Ontology-TTO- MatPortal: https://matportal.org/ontologies/TTO IndustryPortal: https://industryportal.enit.fr/ontologies/TTO KW - Ontology KW - Tensile testing PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/tensile-test UR - https://github.com/HosseinBeygiNasrabadi/Tensile-Test-Ontology-TTO- UR - https://matportal.org/ontologies/TTO UR - https://industryportal.enit.fr/ontologies/TTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60545 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Tensile stress relaxation test ontology (TSRTO) N2 - Tensile Stress Relaxation Test Ontology (TSRTO) has developed for representing the tensile stress relaxation testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 10319-1 standard. Versions info: V1 developed using BFO+CCO top-level ontologies. V3 developed using PROV+PMDco top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/relaxation-test GitHub: https://github.com/HosseinBeygiNasrabadi/Tensile-Stress-Relaxation-Test-Ontology-TSRTO MatPortal: https://matportal.org/ontologies/TSRTO IndustryPortal: https://industryportal.enit.fr/ontologies/TSRTO KW - Ontology KW - Tensile stress relaxation testing KW - FAIR data PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/relaxation-test UR - https://github.com/HosseinBeygiNasrabadi/Tensile-Stress-Relaxation-Test-Ontology-TSRTO UR - https://matportal.org/ontologies/TSRTO UR - https://industryportal.enit.fr/ontologies/TSRTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60546 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Hahn, Marc Benjamin T1 - Temperature effects in the Object Oriented Micromagnetic Framework (OOMMF) - OOMMF input parameter files for Tc determination N2 - To simulate the movement of the macroscopic magnetic moment in ferromagnetic systems under the influence of elevated temperatures, the stochastic version of the Landau-Lifshitz (LL) or the Landau-Lifshitz-Gilbert equation with a spin density of one per unit cell has to be used. To apply the stochastic LL to micromagnetic simulations, where the spin density per unit cell is generally higher, a conversion has to be performed. OOMMF sample files MIF) are provided which can be used to determine the Curie temperature for the classical bulk magnets, iron, nickel and cobalt. KW - OOMMF KW - Temperature KW - Micromagnetism KW - Thetaevolve KW - Ferromagnetism KW - Exchange interaction KW - LLG KW - Landau Lifshitz equation KW - Magnetic moment KW - Magnetic nanoparticles KW - Object oriented micromagnetic framework KW - Stochastic Landau Lifshitz Gilbert equation KW - Temperature scaling PY - 2020 DO - https://doi.org/10.26272/opus4-51169 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-51169 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - Technical Drawings for The MOUSE Modular Sample Holder: Solid Sample Rack/Plate N2 - OpenSCAD, STL and technical drawings for the solid sample rack designed primarily for use with The MOUSE instruments. This solid sample rack can be used in conjunction with: - Laser-cut sample holder (10.5281/zenodo.7499437) - Modular sample holder (10.5281/zenodo.7499416) - Capillary flow-cell for liquid samples (10.5281/zenodo.7499421) KW - X-ray scattering KW - SAXS KW - Sample holder KW - MOUSE PY - 2023 DO - https://doi.org/10.5281/zenodo.7499424 PB - Zenodo CY - Geneva AN - OPUS4-56778 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - Technical Drawings for The MOUSE Modular Sample Holder: Laser-cut Sample Holder N2 - PDF file for the laser-cut sample holder designed primarily for use with The MOUSE instruments. This sample holder can be used in conjunction with: - Solid sample rack/plate (10.5281/zenodo.7499424) - Modular sample holder (10.5281/zenodo.7499416) - Capillary flow-cell for liquid samples (10.5281/zenodo.7499421) KW - X-ray scattering KW - SAXS KW - Sample holder KW - MOUSE PY - 2023 DO - https://doi.org/10.5281/zenodo.7499437 PB - Zenodo CY - Geneva AN - OPUS4-56779 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - Technical Drawings for The MOUSE Modular Sample Holder: Capillary Flow-through Cell N2 - OpenSCAD, STL and technical drawings for the capillary flow-through cell designed primarily for use with The MOUSE instruments. This flow-through cell can be used in conjunction with: - Modular sample holder (10.5281/zenodo.7499416) - Solid sample rack/plate (10.5281/zenodo.7499424) - Laser-cut sample holder (10.5281/zenodo.7499437) KW - X-ray scattering KW - SAXS KW - Sample holder KW - MOUSE PY - 2023 DO - https://doi.org/10.5281/zenodo.7499421 PB - Zenodo CY - Geneva AN - OPUS4-56776 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - Technical Drawings for The MOUSE Modular Sample Holder N2 - OpenSCAD, STL and technical drawings for the Modular sample holder designed primarily for use with The MOUSE instruments. This modular sample holder can be used in conjunction with the following: - Capillary flow-cell for liquid samples (10.5281/zenodo.7499421) - Solid sample rack/plate (10.5281/zenodo.7499424) - Laser-cut sample holder (10.5281/zenodo.7499437) KW - X-ray scattering KW - SAXS KW - Sample holder KW - MOUSE PY - 2023 DO - https://doi.org/10.5281/zenodo.7499416 PB - Zenodo CY - Geneva AN - OPUS4-56775 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 - 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 - Miliūtė, Aistė T1 - Synthesis and phase purity of the negative thermal expansion material ZrV2O7 N2 - This repository contains computational and experimental data for the manuscript titled “Synthesis and phase purity of the negative thermal expansion material ZrV2O7”. KW - NTE KW - Sol-gel KW - Solid-state KW - Ab-initio KW - XRD KW - Raman PY - 2024 DO - https://doi.org/10.5281/zenodo.12688634 PB - Zenodo CY - Geneva AN - OPUS4-61360 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Stawski, Tomasz A1 - Smales, Glen Jacob A1 - Scoppola, E. A1 - Jha, D. A1 - Morales, L. F. G. A1 - Moya, A. A1 - Wirth, R. A1 - Pauw, Brian Richard A1 - Emmerling, Franziska A1 - Van Driessche, A. E. S. T1 - Supplementary data set for "Seeds of imperfection rule the mesocrystalline disorder in natural anhydrite single crystals" N2 - In recent years, we have come to appreciate the astounding intricacy of the formation process of minerals from ions in aqueous solutions. In this context, a number of studies have revealed that nucleation in the calcium sulfate system is non-classical, involving the aggregation and reorganization of nanosized prenucleation particles. In a recent work we have shown that this particle-mediated nucleation pathway is actually imprinted in the resultant single micron-sized CaSO4 crystals. This property of CaSO4 minerals provides us with an unique opportunity to search for evidence of non-classical nucleation pathways in geological environments. In particular, we focused on the quintessential single crystals of anhydrite extracted from the Naica mine in Mexico. We elucidated the growth history from this mineral sample by mapping growth defects at different length scales. Based on these data we argue that the nano-scale misalignment of the structural sub-units observed in the initial calcium sulfate crystal seed propagate through different length-scales both in morphological, as well as strictly crystallographic aspects, eventually causing the formation of large mesostructured single crystals of anhydrite. Hence, the nanoparticle mediated nucleation mechanism introduces a 'seed of imperfection', which leads to a macroscopic single crystal, in which its fragments do not fit together at different length-scales in a self-similar manner. Consequently, anisotropic voids of various sizes are formed with very well-defined walls/edges. But, at the same time the material retains its essential single crystal nature. These findings shed new light on the longstanding concept of crystal structure. KW - Calcium sulfate KW - Mesocrystal KW - Anhydrite PY - 2021 DO - https://doi.org/10.5281/zenodo.4943234 PB - Zenodo CY - Geneva AN - OPUS4-53765 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 - 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 - Kuchenbecker, Petra A1 - Lindemann, Franziska T1 - SOP and reference data for determination of the Volume-specific Surface Area (VSSA) of a commercially available CeO2 nano powder N2 - Detailed SOP and reference data for the determination of the VSSA of a commercially available CeO2 nano powder: specific (BET-) Surface Area by gas adsorption (Ar and N2) skeletal (true solid state) density by gas pycnometry. Estimation of the particle size by VSSA screening method. KW - Nano powder KW - VSSA KW - Volume specific surface area KW - Screening method KW - Ceria KW - CeO2 PY - 2023 DO - https://doi.org/10.5281/zenodo.10061235 PB - Zenodo CY - Geneva AN - OPUS4-58786 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 - Pauw, Brian Richard A1 - Smales, Glen Jacob T1 - Small-angle scattering data analysis round robin dataset - Original for participants N2 - These are four datasets that were made available to the participants of the Small-angle Scattering data analysis round robin. The intent was to find out how comparable results from different researchers are, who analyse exactly the same processed, corrected dataset. In this repository, there are: 1) a PDF document with more details for the study, 2) the datasets for people to try and fit, 3) an Excel spreadsheet to document the results. Datasets 1 and 2 were modified from: Deumer, Jerome, & Gollwitzer, Christian. (2022). npSize_SAXS_data_PTB (Version 5) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5886834 Datasets 3 and 4 were collected in-house on the MOUSE instrument. KW - Round robin KW - SAXS KW - Small angle scattering KW - SANS KW - X-ray KW - Neutron KW - Human factor KW - Data analysis KW - Data fitting KW - Human influence PY - 2023 DO - https://doi.org/10.5281/zenodo.7506365 PB - Zenodo CY - Geneva AN - OPUS4-56799 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob A1 - Rosalie, Julian T1 - Small-angle scattering data analysis round robin - Anonymized results, figures and Jupyter notebook N2 - The intent of this round robin was to find out how comparable results from different researchers are, who analyse exactly the same processed, corrected dataset. This zip file contains the anonymized results and the jupyter notebook used to do the data processing, analysis and visualisation. Additionally, TEM images of the samples are included. KW - Round robin KW - Small-angle scattering KW - Data analysis PY - 2023 DO - https://doi.org/10.5281/zenodo.7509710 PB - Zenodo CY - Geneva AN - OPUS4-56803 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Völker, Christoph A1 - Moreno Torres, Benjami T1 - SLAMD-FIB-Case-Study N2 - With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders part of the energy-intensive clinker production process can be dispensed with. However, because numerous chemicals are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced cement formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of cement formulations can significantly accelerate research. The „Sequential Learning App for Materials Discovery“ (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings. Our material database already includes more than 120,000 data points of alternative cements and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials. Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient. KW - Alkali activated concrete KW - Concrete PY - 2022 UR - https://github.com/BAMcvoelker/SLAMD-FIB-Case-Study#slamd-fib-case-study PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-56637 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 - Wolf, Jako A1 - Stawski, Tomasz A1 - Smales, Glen Jacob A1 - Thünemann, Andreas A1 - Emmerling, Franziska T1 - SI Files for "Towards automation of the polyol process for the synthesis of silver nanoparticles" N2 - The graphml file: reaction_graph_AgNP.graphml is included. It contains topological information (Fig. 1 in the main text) about the reaction setup and metadata with reaction condtions. It used by the Python API used to control the Chemputer. SAXS reports. The complete report sheets generated by McSAS are included. They contain extended information characterising the size distributions and the fitting parameters. NP3_I: saxs_report_NP3_I.pdf NP3_II: saxs_report_NP3_II.pdf NP3_III: saxs_report_NP3_III.pdf NP3_IV: saxs_report_NP3_IV.pdf NP5_I: saxs_report_NP5_I.pdf NP5_II: saxs_report_NP5_II.pdf NP5_III: saxs_report_NP5_III.pdf KW - Automated synthesis KW - Silver KW - Nanoparticles PY - 2022 DO - https://doi.org/10.5281/zenodo.5910614 PB - Zenodo CY - Geneva AN - OPUS4-55197 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pauw, Brian Richard T1 - Set of technical drawings, associated with manuscript entitled: "Extending Synchrotron SAXS instrument ranges through addition of a portable, inexpensive USAXS module with vertical rotation axes" N2 - This is a set of drawings accompanying the submitted paper entitled "Extending Synchrotron SAXS instrument ranges through addition of a portable, inexpensive USAXS module with vertical rotation axes". The parts described herein will combine with commercial off-the-shelf components to build a high precision pair of rotation stages for accurate measurement of scattering angles with a sub-microradian precision. KW - X-ray scattering KW - USAXS KW - ultra-small-angle X-ray scattering KW - technical drawings KW - module KW - extension PY - 2021 DO - https://doi.org/10.5281/zenodo.4604703 PB - Zenodo CY - Geneva AN - OPUS4-52547 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 - 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 - Han, Ying T1 - Segmented primary phases of Al-alloy EN AW-2618A in the T61 state using synchrotron computed tomography N2 - The video file contains data from a synchrotron computed tomography measurement of the primary phases of the Al-alloy EN AW-2618A in the T61 state. The volume fraction of the primary phases was determined. KW - Aluminum alloy KW - EN AW-2618A KW - Computed tomography KW - Primary phases PY - 2024 DO - https://doi.org/10.5281/zenodo.12730717 PB - Zenodo CY - Geneva AN - OPUS4-60657 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - George, Janine A1 - Naik, Aakash A1 - Jackson, A. J. A1 - Baird, S. T1 - Scripts to reproduce "Automated bonding analysis with crystal orbital Hamilton populations" N2 - This repo allows to recreate our publication: https://doi.org/10.1002/cplu.202200123 In contrast to 0.2.2, we fixed an issue with absolute path. KW - Automation KW - High-throughput computations KW - Bonding analysis PY - 2022 UR - https://github.com/JaGeo/LobsterAutomation UR - https://doi.org/10.5281/zenodo.6421928 UR - https://doi.org/10.5281/zenodo.6595062 UR - https://doi.org/10.5281/zenodo.6599556 UR - https://doi.org/10.5281/zenodo.6674670 UR - https://doi.org/10.5281/zenodo.6704163 DO - https://doi.org/10.5281/zenodo.6421927 PB - Zenodo CY - Geneva AN - OPUS4-55177 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Deumer, J. A1 - Andresen, Elina T1 - SAXS data of bipyramidal LiYF4 nanoparticles N2 - SAXS data of bipyramidal LiYF4 nanoparticles synthesized by the Federal Institute for Materials Research and Testing (BAM) and measured by the Physikalisch-Technische Bundesanstalt (PTB) at the synchrotron facility Bessy II, Berlin, Germany. KW - Reference data set KW - Simulation KW - Reference material KW - Upconversion nanoparticles KW - Particle number concentration KW - SAXS PY - 2024 DO - https://doi.org/10.5281/zenodo.13691409 PB - Zenodo CY - Geneva AN - OPUS4-62134 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kohlbrecher, J. A1 - Breßler, Ingo T1 - SASfit 0.94.12 N2 - Small-angle scattering is an increasingly common method for characterizing particle ensembles in a wide variety of sample types and for diverse areas of application. SASfit has been one of the most comprehensive and flexible curve-fitting programs for decades, with many specialized tools for various fields. KW - Small-angle scattering KW - SAXS KW - SANS KW - Scattering pattern analysis PY - 2023 UR - https://doi.org/10.5281/zenodo.7530357 DO - https://doi.org/10.5281/zenodo.7530356 PB - Zenodo CY - Geneva AN - OPUS4-57913 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - von Hartrott, Philipp A1 - Skrotzki, Birgit T1 - Room temperature and elevated temperature tensile test and elastic properties data of Al-alloy EN AW-2618A after different aging times and temperatures N2 - The dataset contains two types of data: elastic properties (Young's and shear modulus, Poisson's ratio) between room temperature and 250 °C and a set of tensile tests at different aging times, aging temperatures, and test temperatures. KW - Aluminium alloy KW - Young's modulus KW - Shear modulus KW - Aging KW - Tensile test KW - Strength PY - 2023 UR - https://doi.org/10.5281/zenodo.10377164 DO - https://doi.org/10.5281/zenodo.10377163 PB - Zenodo CY - Geneva AN - OPUS4-59161 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Rosenbusch, Sjard Mathis A1 - Balzani, Daniel A1 - Unger, Jörg F. T1 - Regularization of softening plasticity models for explicit dynamics using a gradient-enhanced modified Johnson-Holmquist model N2 - The behavior of concrete under high strain rates is often described by plasticity models with softening, which is modeled by a reduction of the yield surface as a function of the local equivalent plastic strain. Among these are the RHT model, the K\&C model and the Johnson-Holmquist concrete model. These models are however local and therefore produce mesh-dependent results. In this contribution, the gradient-enhancement of such models is investigated. First, the mesh-dependency of these local formulations based on the analysis with a modified JH2 model as a representative for these constitutive formulations is demonstrated using a one-dimensional benchmark example. The central difference method is used as solver with a diagonal mass matrix obtained from a Gauß-Lobatto integration. In the benchmark, the width of the damaged zone decreases upon mesh-refinement and the dissipated plastic energy tends to zero. It is further shown that a significantly small safety factor for the critical time step is needed in order to achieve accurate results for the benchmark example. Next, two gradient-enhancement approaches are investigated. The enhancement is based on the inclusion of inertia and damping to the additional Helmholtz equation which enables the use of the central difference method as an explicit solver. In the first formulation, the yield surface and therefore the softening is formulated in terms of a nonlocal equivalent plastic strain. In the second approach, a hardening term which depends on the local equivalent plastic strain is introduced to the modified JH2 model in addition to the nonlocal softening. This approach is inspired by results from gradient plasticity in quasi-static loading scenarios. It is shown that the approach without hardening can still lead to mesh-dependent results while the model that includes hardening successfully inhibits strain localization and leads to a converging dissipated plastic energy. This is further confirmed in a two-dimensional wedge-splitting experiment where the damage pattern produced by the local model is mesh-dependent as well and the dissipated plastic energy tends to zero with mesh-refinement. The proposed nonlocal model with hardening results in a consistent damage pattern and the dissipated plastic energy converges. Furthermore, the nonlocal model with hardening is less sensitive to time step refinement, such that computational efficiency can be improved compared to the local model. The numerical experiments are implemented using the free and open-source tool FEniCSx. KW - Concrete modeling KW - Explicit Dynamics KW - FEniCS KW - Gradient plasticity KW - JH2 model KW - Mesh convergence PY - 2024 DO - https://doi.org/10.5281/zenodo.13983859 PB - Zenodo CY - Geneva AN - OPUS4-65083 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kern, Simon A1 - Wander, Lukas A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gottu Mukkula, A. R. A1 - Holtkamp, M. A1 - Salge, M. A1 - Fleischer, C. A1 - Weber, N. A1 - Engell, S. A1 - Paul, Andrea A1 - King, R. A1 - Maiwald, Michael T1 - Raw data of pilot plant runs for CONSENS project (Case study 1) N2 - In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and o-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum. The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17. In the following the contents of the files are explained. KW - Process Analytical Technology KW - Multivariate Data Analysis KW - Nuclear Magnetic Resonance KW - Near Infrared Spectroscopy KW - Continuous Manufacturing KW - CONSENS PY - 2018 DO - https://doi.org/10.5281/zenodo.1438233 PB - Zenodo CY - Geneva AN - OPUS4-48063 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - George, Janine T1 - Raw data for "Automated bonding analysis with crystal orbital Hamilton populations" N2 - Raw data corresponding to the following paper: 10.1002/cplu.202200123. KW - Automation KW - High-throughput computations KW - Bonding analysis PY - 2022 UR - https://doi.org/10.5281/zenodo.6373369 DO - https://doi.org/10.5281/zenodo.6373368 PB - Zenodo CY - Geneva AN - OPUS4-55175 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob T1 - Raw and processed X-ray scattering datasets for: "Entering a new dimension in powder processing for advanced ceramics shaping" N2 - This dataset is a complete set of raw, processed and analyzed data, associated with the manuscript mentioned in the title. All associated metadata and processing history has been added. Particle size distribution analyses using McSAS are included as well. The samples consisted of a 4.2 mass% dispersion of yttria-stabilized zirconia nanoparticles in a cross-linked matrix. The measurements show a good dispersion with minimal agglomeration. The wide-angle region shows diffraction information consistent with zirconia. KW - X-ray scattering KW - Nanocomposite KW - Ceramic microprinting KW - Yttria-stabilized zirconia KW - SAXS KW - Nanomaterials KW - Two-photon polymerization KW - Transparency KW - Mechanical testing PY - 2023 DO - https://doi.org/10.5281/zenodo.7498647 PB - Zenodo CY - Geneva AN - OPUS4-56766 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Skrotzki, Birgit T1 - Radii of S-phase Al2CuMg in Al-alloy EN AW 2618A after different aging times at 190°C N2 - The dataset contains data from quantitative microstructural analysis of transmission electron microscopy (TEM) studies of the S-phase (Al2CuMg) radii in Al-alloy EN AW 2618A. The investigated material and the applied methods were described in detail in two publications. KW - Aluminium alloy KW - EN AW 2618A a KW - S-phase KW - Al2CuMg KW - Aging KW - Creep KW - Radii distribution KW - TEM PY - 2022 UR - https://doi.org/10.5281/zenodo.6659461 UR - https://doi.org/10.5281/zenodo.7625259 DO - https://doi.org/10.5281/zenodo.6659460 PB - Zenodo CY - Geneva AN - OPUS4-55067 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 8) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852823 PB - Zenodo CY - Geneva AN - OPUS4-57448 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 7) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852820 PB - Zenodo CY - Geneva AN - OPUS4-57447 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 6) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852808 PB - Zenodo CY - Geneva AN - OPUS4-57446 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 5) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852806 PB - Zenodo CY - Geneva AN - OPUS4-57445 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 4) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852798 PB - Zenodo CY - Geneva AN - OPUS4-57444 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 3) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852791 PB - Zenodo CY - Geneva AN - OPUS4-57443 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 2) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852107 PB - Zenodo CY - Geneva AN - OPUS4-57442 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 1) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) Refer to README.md file instructions to reproduce the data. KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852082 PB - Zenodo CY - Geneva AN - OPUS4-57441 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 - Schilling, Markus A1 - Bayerlein, Bernd A1 - Birkholz, H. A1 - Fliegener, S. A1 - Grundmann, J. A1 - Hanke, T. A1 - von Hartrott, P. A1 - Waitelonis, J. T1 - PMD Core Ontology (PMDco) N2 - The PMD Core Ontology (PMDco) is a comprehensive framework for representing knowledge that encompasses fundamental concepts from the domains of materials science and engineering (MSE). The PMDco has been designed as a mid-level ontology to establish a connection between specific MSE application ontologies and the domain neutral concepts found in established top-level ontologies. The primary goal of the PMDco is to promote interoperability between diverse domains. PMDco's class structure is both understandable and extensible, making it an efficient tool for organizing MSE knowledge. It serves as a semantic intermediate layer that unifies MSE knowledge representations, enabling data and metadata to be systematically integrated on key terms within the MSE domain. With PMDco, it is possible to seamlessly trace data generation. The design of PMDco is based on the W3C Provenance Ontology (PROV-O), which provides a standard framework for capturing the generation, derivation, and attribution of resources. By building on this foundation, PMDco facilitates the integration of data from various sources and the creation of complex workflows. In summary, PMDco is a valuable tool for researchers and practitioners in the MSE domains. It provides a common language for representing and sharing knowledge, allowing for efficient collaboration and promoting interoperability between diverse domains. Its design allows for the systematic integration of data and metadata, enabling seamless traceability of data generation. Overall, PMDco is a crucial step towards a unified and comprehensive understanding of the MSE domain. PMDco at GitHub: https://github.com/materialdigital/core-ontology KW - Ontology KW - Semantic Web technologies KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology PY - 2023 UR - https://github.com/materialdigital/core-ontology/blob/f2bd420348b276583fad6fa0fb4225f17b893c78/pmd_core.ttl PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-59352 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized ZrO2 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized ZrO2 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - ZrO2 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7965536 PB - Zenodo CY - Geneva AN - OPUS4-57671 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized ZnO nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized ZnO nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - ZnO nanoparticles KW - NanoSolveIT PY - 2023 DO - https://doi.org/10.5281/zenodo.7990301 PB - Zenodo CY - Geneva AN - OPUS4-57661 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized TiO2 PVP nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized TiO2 PVP nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - HAXPES KW - XPS KW - SEM KW - Nanoparticles KW - TiO2 PVP PY - 2023 DO - https://doi.org/10.5281/zenodo.7966354 PB - Zenodo CY - Geneva AN - OPUS4-57761 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized TiO2 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized TiO2 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - TiO2 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7941566 PB - Zenodo CY - Geneva AN - OPUS4-57668 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized TiO2 D540 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized TiO2 D540 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - TiO2 D540 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7961317 PB - Zenodo CY - Geneva AN - OPUS4-57669 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Fe2O3 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Fe2O3 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Fe2O3 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7941001 PB - Zenodo CY - Geneva AN - OPUS4-57665 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Co3O4 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Co3O4 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Co3O4 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7941248 PB - Zenodo CY - Geneva AN - OPUS4-57666 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Co2.25Fe0.75O4 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Co2.25Fe0.75O4 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Co2.25Fe0.75O4 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7940538 PB - Zenodo CY - Geneva AN - OPUS4-57663 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Co1.5Fe1.5O4 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Co1.5Fe1.5O4 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Co1.5Fe1.5O4 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7940271 PB - Zenodo CY - Geneva AN - OPUS4-57662 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Co0.75Fe2.25O4 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Co0.75Fe2.25O4 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Co0.75Fe2.25O4 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7940769 PB - Zenodo CY - Geneva AN - OPUS4-57664 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized CeO2 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized CeO2 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - CeO2 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7941461 PB - Zenodo CY - Geneva AN - OPUS4-57667 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Ce0.75Zr0.25O2 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Ce0.75Zr0.25O2 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Ce0.75Zr0.25O2 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7966133 PB - Zenodo CY - Geneva AN - OPUS4-57673 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Ce0.5Zr0.5O2 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Ce0.5Zr0.5O2 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Ce0.5Zr0.5O2 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7965445 PB - Zenodo CY - Geneva AN - OPUS4-57670 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Ce0.25Zr0.75O2 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Ce0.25Zr0.75O2 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Ce0.25Zr0.75O2 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7966165 PB - Zenodo CY - Geneva AN - OPUS4-57674 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized Ce0.1Zr0.9O2 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized Ce0.1Zr0.9O2 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - XPS KW - HAXPES KW - SEM KW - NanoSolveIT KW - Ce0.1Zr0.9O2 nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7965602 PB - Zenodo CY - Geneva AN - OPUS4-57672 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterilized AlOOH nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterilized AlOOH nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - HAXPES KW - XPS KW - SEM KW - AlOOH KW - Nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7966245 PB - Zenodo CY - Geneva AN - OPUS4-57757 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterile ZnO nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of ZnO nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - HAXPES KW - XPS KW - SEM KW - Nanoparticles KW - ZnO PY - 2023 DO - https://doi.org/10.5281/zenodo.7990213 PB - Zenodo CY - Geneva AN - OPUS4-57762 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterile Fe3O4 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of sterile Fe3O4 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - HAXPES KW - XPS KW - SEM KW - Fe3O4 KW - Nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7990301 PB - Zenodo CY - Geneva AN - OPUS4-57764 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of sterile citrated stabilized Au nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of Au nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - HAXPES KW - XPS KW - SEM KW - Au Nanoparticles KW - NanoSolveIT PY - 2023 DO - https://doi.org/10.5281/zenodo.7990250 PB - Zenodo CY - Geneva AN - OPUS4-57763 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of Fe3O4 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of Fe3O4 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - HAXPES KW - XPS KW - SEM KW - Fe3O4 KW - Nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7990085 PB - Zenodo CY - Geneva AN - OPUS4-57759 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of CeO2/Co3O4 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of CeO2/Co3O4 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - HAXPES KW - XPS KW - SEM KW - Nanoparticles KW - CeO2/Co3O4 PY - 2023 DO - https://doi.org/10.5281/zenodo.7989698 PB - Zenodo CY - Geneva AN - OPUS4-57760 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Knigge, Xenia A1 - Radnik, Jörg T1 - Physico-chemical characterization of Ce0.9Zr0.1O2 nanoparticles by XPS / HAXPES / SEM N2 - Here a dataset of XPS, HAXPES and SEM measurements for the physico-chemical characterization of Ce0.9Zr0.1O2 nanoparticles is presented. The measurements are part of the H2020 project “NanoSolveIT”. KW - HAXPES KW - XPS KW - SEM KW - Ce0.9Zr0.1O2 KW - Nanoparticles PY - 2023 DO - https://doi.org/10.5281/zenodo.7986672 PB - Zenodo CY - Geneva AN - OPUS4-57758 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Robens-Radermacher, Annika A1 - Strobl, Dominic T1 - PGDrome N2 - A FEniCS based python module of the Proper Generalized Decomposition (PGD) method. KW - Reduced Order Model KW - Proper Generalized Decomposition KW - Fenics PY - 2023 DO - https://doi.org/10.5281/zenodo.10075334 PB - Zenodo CY - Geneva AN - OPUS4-59134 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 - Kuchenbecker, Petra A1 - Lindemann, Franziska T1 - Particle size determination of a commercially available CeO2 nano powder - SOPs and reference data N2 - Compilation of detailed SOPs for characterization of a commercially available CeO2 nano powder including - suspension preparation (indirect and direct sonication), - particle size determination (Dynamic Light Scattering DLS and Centrifugal Liquid Sedimentation CLS) with reference data, respectively. For sample preparation and analysis by Scanning Electron Microscopy (SEM) of this powder see related works (submitted, coming soon). KW - Wet dispersion KW - Nano powder KW - Particle size KW - CeO2 KW - Ceria KW - DLS KW - CLS PY - 2023 DO - https://doi.org/10.5281/zenodo.10061079 PB - Zenodo CY - Geneva AN - OPUS4-58785 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Léonard, Fabien T1 - Overview of XCT data processing workflow for ammonium nitrate prills quantitative analysis N2 - This video presents the data processing workflow that was developed to perform the quantitative structural and morphological analysis of ammonium nitrate prills by x-ray computed tomography. KW - ANFO KW - Data processing KW - Explosives KW - Porosity KW - Surface area KW - XCT PY - 2020 DO - https://doi.org/10.5281/zenodo.3611339 PB - Zenodo CY - Geneva AN - OPUS4-51897 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 - 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 - 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 - Riechers, Birte A1 - Maaß, Robert T1 - nanoindentation data associated with the publication "On the elastic microstructure of bulk metallic glasses" in Materials&Design 2023 N2 - This dataset consists of indentation data measured with a conospherical tip in a Hysitron-Bruker TI980 Nanoindenter on the surface of a <100> Silicon wafer and a polished cross-sectional cut of a Zr65Cu25Al10 bulk metallic glass. It is associated with the following publication: Birte Riechers, Catherine Ott, Saurabh Mohan Das, Christian H. Liebscher, Konrad Samwer, Peter M. Derlet and Robert Maass "On the elastic microstructure of bulk metallic glasses" Materials and Design xxx, (2023) 111929. https://doi.org/10.1016/j.matdes.2023.111929 All experimental information can be found in this paper and in the accompanying supplementary information. This electronic version of the data was published on the "Zenodo Data repository" found at http://zenodo.org/deposit in the community "Bundesanstalt fuer Materialforschung und -pruefung (BAM)". The authors have copyright to these data. You are welcome to use the data for further analysis, but are requested to cite the original publication whenever use is made of the data in publications, presentations, etc. Any questions regarding the data can be addressed to birte.riechers@bam.de who would also appreciate a note if you find the data useful. KW - Metallic glasses KW - Nanoindentation KW - Elastic microstructure PY - 2023 DO - https://doi.org/10.5281/zenodo.7818224 PB - Zenodo CY - Geneva AN - OPUS4-57352 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 - 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 - 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 - Lisec, Jan T1 - MetabolomicsBasics (R package to process and analyze metabolomics datasets) N2 - Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification. KW - Software KW - Mass Spectrometry KW - R package KW - Data processing PY - 2018 UR - https://github.com/cran/MetabolomicsBasics/ PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-57854 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit A1 - Hanke, Thomas A1 - Eisenbart, Miriam T1 - Mechanical testing ontology (MTO) N2 - The materials mechanical testing ontology (MTO) was developed by collecting the mechanical testing vocabulary from ISO 23718 standard, as well as the standardized testing processes described for various mechanical testing of materials like tensile testing, Brinell hardness test, Vickers hardness test, stress relaxation test, and fatigue testing. Versions info: V2 developed using BFO+CCO top-level ontologies. V3 developed using PROVO+PMDco top-level ontologies. V4 developed using BFO+IOF top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/ontologies/mechanical-testing-ontology GitHub: https://github.com/HosseinBeygiNasrabadi/Mechanical-Testing-Ontology MatPortal: https://matportal.org/ontologies/MTO IndustryPortal: https://industryportal.enit.fr/ontologies/MTO KW - Ontology KW - Mechanical testing KW - FAIR data PY - 2023 UR - https://gitlab.com/kupferdigital/ontologies/mechanical-testing-ontology/ PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-58271 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -