Forschungsdatensätze der BAM
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- Automation (3)
- Bonding analysis (3)
- High-throughput computations (3)
- Software (3)
- Aging (2)
- Aluminium alloy (2)
- Concrete (2)
- Creep (2)
- Nondestructive testing (2)
- SAXS (2)
Organisationseinheit der BAM
- 6 Materialchemie (9)
- 8 Zerstörungsfreie Prüfung (6)
- 5 Werkstofftechnik (4)
- 5.2 Metallische Hochtemperaturwerkstoffe (4)
- 6.0 Abteilungsleitung und andere (4)
- 1 Analytische Chemie; Referenzmaterialien (3)
- 1.7 Organische Spuren- und Lebensmittelanalytik (3)
- 6.5 Synthese und Streuverfahren nanostrukturierter Materialien (3)
- 8.0 Abteilungsleitung und andere (3)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (2)
Data for the publication "The role of extracellular polymeric substances of fungal biofilms in mineral attachment and weathering" (https://doi.org/10.1038/s41529-022-00253-1). It includes:
- The Summary of the EPS concentration, EPS sugar components and EPS linkages.
- The Summary of the XPS analysis of freeze-dried biofilm samples of all strains.
- The Summary of the pH, Mg, SI and Fe concentration, biomass and olivine dissolution rate for each time point of all dissolution experiments.
This dataset contains raw data resulting from Impact-Echo measurements at the reference concrete block "IE Platte", located at BAM (German Federal Institute for Materials Research and Testing).
The specimen contains three polystyrene slabs and one polyethylene foil to act as reflectors. The specimen was produced in a three-step process. First, the base plate was cast. Second, the reflectors were taped to the base plate. Finally, the upper layer was cast on top of base plate and reflectors. A drawing is contained in the dataset.
The Impact-Echo method is based on the excitation of the zero-group-velocity frequency of the first symmetric Lamb mode of a plate-like structure, in order to assess its thickness. Numerous publications elaborate on Impact-Echo theory, examples are (Gibson and Popovics 2005, Schubert and Köhler 2008 , Abraham and Popovics 2010).
The measurements have been conducted using a setup that contains only commercially available components. The setup consists of an Olson CTG-2 concrete thickness gauge (Olsen Instruments, USA) for actuation and sensing and an 8-bit NI USB-5132 digital storage oscilloscope (National Instruments, USA) combined with the Echolyst software (Schweizerischer Verein für technische Inspektionen (SVTI), Switzerland) for data acquisition.
Measurements were conducted using a grid of 29x29 points with a spacing of 50 mm. At each point 8192 samples were recorded at a sampling rate of 1 MS/s.
The dataset contains the (X,Y) location in mm of the individual measurement points as well as the raw measurement data at those points.
The data is provided in the formats *.mir/*.mhdr (Echolyst), *.npy (Python) and *.mat (Matlab) and *.csv to ease the import in various post-processing tools.
Models for TOPAS/Geant4 to estimate the microscopic dose received by biomolecules during bioSAXS experiments.
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).
ABID
(2022)
In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
IsoCor
(2022)
Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis.
A tool for merging and/or rebinning single or multiple datasets to achieve a lower point density with best possible statistics. highly scriptable, CLI, no GUI
Version 0.1: works but could do with a cleanup. Weighting by uncertainty currently always on, but should be optional for use as an azimuthal or radial averager
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).
The dataset provided in this repository comprises data obtained from a series of characterization tests performed to a sheet of typical S355 (material number: 1.0577) structural steel (designation of steel according to DIN EN 10025-2:2019). The tests include methods for the determination of mechanical properties such as, e.g., tensile test, Charpy test and sonic resonance test. This dataset is intended to be extended by the inclusion of data obtained from further test methods. Therefore, the entire dataset (concept DOI) comprises several parts (versions), each of which is addressed by a unique version DOI.
The data were generated in the frame of the digitization project Innovationplatform MaterialDigital (PMD) which, amongst other activities, aims to store data in a semantically and machine understandable way. Therefore, data structuring and data formats are focused in addition to aspects in the field of material science and engineering (MSE). Hence, this data is supposed to provide reference data as basis for experimental data inclusion, conversion and structuring (data management and processing) that leads to semantical expressivity as well as for MSE experts being generally interested in the material properties and knowledge.
This sequence of X-Ray images shows how one of the most common Italian moka pots actually work! The sequence starts with a completely prepared moka pot (water in the bottom part, coffee in the middle and hot plate on). During the process the water starts to boil and the steam pressure pushes the hot water through the coffee into the bassin at the top of the pot.
This video sequence and additional explanations can also be found on Wikipedia.
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].
The dataset contains experimental mechanical data from complex service-like creep-fatigue experiments performed isothermally at 620 °C and a low strain amplitude of 0.2 % on tempered martensite-ferritic grade P92 steel. The data sets in text file format provide cyclic deformation (min. and max. stresses) and the total (hysteresis) data of all recorded fatigue cycles for three different creep-fatigue experiments: 1) a standard relaxation fatigue (RF) test with symmetrical dwell times of three minutes introduced at minimum and maximum strain, 2) a fully strain-controlled service-like relaxation (SLR) test combining these three-minute peak strain dwells with a 30-minute dwell in between at zero strain, and 3) a partly stress-controlled service-like creep (SLC) test combining the three-minute peak strain dwells with 30-minute dwells at constant stress.
Further information on data and data acquisition, analysis, and experimental details are given in “Experimental Data from Service-Like Creep-Fatigue Experiments on Grade P92 Steel”, submitted to Data in Brief. Additional analyses of these datasets, as well as experimental findings and discussions are presented in “Creep-Fatigue of P92 in Service-Like Tests with Combined Stress- and Strain-Controlled Dwell Times”, submitted to International Journal of Fatigue.
WEBSLAMD
(2022)
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.
SLAMD-FIB-Case-Study
(2022)
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.
SI Files for "Towards automation of the polyol process for the synthesis of silver nanoparticles"
(2022)
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