Forschungsdatensätze der BAM
Filtern
Erscheinungsjahr
Dokumenttyp
- Forschungsdatensatz (153)
Referierte Publikation
- nein (153)
Schlagworte
- SEM (23)
- XPS (23)
- HAXPES (22)
- Automation (20)
- NanoSolveIT (15)
- SAXS (15)
- X-ray scattering (15)
- Bonding analysis (14)
- Computational Chemistry (10)
- Database (10)
Organisationseinheit der BAM
- 6 Materialchemie (88)
- 6.1 Oberflächen- und Dünnschichtanalyse (31)
- 6.5 Synthese und Streuverfahren nanostrukturierter Materialien (31)
- 5 Werkstofftechnik (27)
- 5.2 Metallische Hochtemperaturwerkstoffe (21)
- 6.0 Abteilungsleitung und andere (19)
- 8 Zerstörungsfreie Prüfung (18)
- 1 Analytische Chemie; Referenzmaterialien (12)
- VP Vizepräsident (12)
- VP.1 eScience (12)
The RILEM TC 304-ADC has set up a large interlaboratory study on the mechanical properties of 3D printed concrete (ILS-mech). The study was prepared in 2022 by a preparation group leading to a Study Plan which the TC approved on 29 November 2022 (https://doi.org/10.14459/2023mp1705940). The ILS-mech was performed in 2023. The data was collected using a pre-prepared spreadsheet template. For data management, a database was derived and set-up in openBIS. The underlying Postgres database of openBIS was exported to the here-published SQLite database for sharing without maintaining a server. The structure of the database is described in (doi). The results are discussed in three associated papers focusing on the overall outcomes and evaluation of the procedures (doi), the compressive test results (doi), and the tensile test results (doi).
These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.
The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.
It is recommended to use the following requirements for the molecular cross-sectional area:
Nitrogen: 0.1620 nm²
Argon: 0.1420 nm²
Expected specific surface area for nitrogen (BET): 140 to 154 m²/g
Expected specific surface area for argon (BET): 129 to 135 m²/g
Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.
The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.
These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.
These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.
The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.
It is recommended to use the following requirements for the molecular cross-sectional area:
Nitrogen: 0.1620 nm²
Argon: 0.1420 nm²
Expected specific surface area for nitrogen (BET): 24 to 25 m²/g
Expected specific surface area for argon (BET): 20 m²/g
Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.
The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.
These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.
This dataset accompanies the following publication:
Hülagü, D., Tobias, C., Dao, R., Komarov, P., Rurack, K., Hodoroaba, V.-D., Towards 3D determination of the surface roughness of core-shell microparticles as a routine quality control procedure by scanning electron microscopy. Sci.Rep, 14, 17936 (2024), https://doi.org/10.1038/s41598-024-68797-7.
It contains SEM and AFM-in-SEM images of polystyrene (PS) core particles, polystyrene-iron oxide (PS/Fe3O4) core-shell particles, and polystyrene-iron oxide-silica (PS/Fe3O4/SiO2) core-shell-shell particles. Please refer to the publication and its supporting information for more details on the acquisition and contents of the dataset, as well as the GitHub repository at https://github.Com/denizhulagu/roughness-analysis-by-electron-microscopy.
The investigated particles were produced at BAM laboratories as previously described in:
Hülagü, D. et al. Generalized analysis approach of the profile roughness by electron microscopy with the example of hierarchically grown polystyrene–iron oxide–silica core–shell–shell particles. Adv. Eng. Mater. 24, 2101344, https://doi.org/10.1002/adem.202101344 (2022).
Tobias, C., Climent, E., Gawlitza, K. & Rurack, K. Polystyrene microparticles with convergently grown mesoporous silica shells as a promising tool for multiplexed bioanalytical assays. ACS Appl. Mater. Interfaces 13, 207, https://dx.doi.org/10.1021/acsami.0c17940 (2020).
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.
The DACHS (Database for Automation, Characterization and Holistic Synthesis) project aims to create completely traceable experimental data, covering syntheses, measurements, analyses, and interpretations. DACHS_MOFs focuses on the synthesis and characterisation of metal-organic frameworks, across multiple, automation-assisted experimental series (AutoMOFs), with the overall goal of producing reproducible MOF samples through tracking of the synthesis parameters.
DACHS_MOFs is simultaneously used to test the DACHS principles.
This upload contain synthesis data from AutoMOFs_3 in HDF5 format (.h5). Each .h5 file contains detailed information on the chemical, experimenal, and synthesis parameters used during the synthesis of a single AutoMOF sample.
The DACHS (Database for Automation, Characterization and Holistic Synthesis) project aims to create completely traceable experimental data, covering syntheses, measurements, analyses, and interpretations. DACHS_MOFs focuses on the synthesis and characterisation of metal-organic frameworks, across multiple, automation-assisted experimental series (AutoMOFs), with the overall goal of producing reproducible MOF samples through tracking of the synthesis parameters.
DACHS_MOFs is simultaneously used to test the DACHS principles.
This upload contain synthesis data from AutoMOFs_2 in HDF5 format (.h5). Each .h5 file contains detailed information on the chemical, experimenal, and synthesis parameters used during the synthesis of a single AutoMOF sample.
Fatigue test ontology (FTO)
(2024)
Fatigue Test Ontology (FTO) has developed for representing the fatigue testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 12106 standard.
Versions info:
V2 developed using PROVO+PMDco top-level ontologies.
V3 developed using BFO+IOF top-level ontologies.
Repositories:
GitLab: https://gitlab.com/kupferdigital/process-graphs/lcf-test
GitHub: https://github.com/HosseinBeygiNasrabadi/Fatigue-Test-Ontology-FTO-
MatPortal: https://matportal.org/ontologies/FTO
IndustryPortal: https://industryportal.enit.fr/ontologies/FTO
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
Tensile test ontology (TTO)
(2024)
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
Vickers test ontology (VTO)
(2024)
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
Brinell test ontology (BTO)
(2024)
Brinell Test Ontology (BTO) has developed for representing the Brinell testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6506-1 standard.
Versions info:
V2 developed using BFO+CCO top-level ontologies.
V3 developed using EMMO+CHAMEO top-level ontologies.
V4 developed using PROVO+PMDco top-level ontologies.
V5 developed using BFO+IOF top-level ontologies.
Repositories:
GitLab: https://gitlab.com/kupferdigital/process-graphs/brinell-hardness-test
GitHub: https://github.com/HosseinBeygiNasrabadi/Brinell-Test-Ontology-BTO-
MatPortal: https://matportal.org/ontologies/BTO
IndustryPortal: https://industryportal.enit.fr/ontologies/BTO
The DACHS (Database for Automation, Characterization and Holistic Synthesis) project aims to create completely traceable experimental data, covering syntheses, measurements, analyses, and interpretations. DACHS_MOFs focuses on the synthesis and characterisation of metal-organic frameworks, across multiple, automation-assisted experimental series (AutoMOFs), with the overall goal of producing reproducible MOF samples through tracking of the synthesis parameters.
DACHS_MOFs is simultaneously used to test the DACHS principles.
This upload contain synthesis data from AutoMOFs_1 in HDF5 format (.h5). Each .h5 file contains detailed information on the chemical, experimenal, and synthesis parameters used during the synthesis of a single AutoMOF sample.
This is the stable version of the full-notch creep test ontology (OntoFNCT) that ontologically represents the full-notch creep test. OntoFNCT has been developed in accordance with the corresponding test standard ISO 16770:2019-09 Plastics - Determination of environmental stress cracking (ESC) of polyethylene - Full-notch creep test (FNCT).
The OntoFNCT provides conceptualizations that are supposed to be valid for the description of full-notch creep tests and associated data in accordance with the corresponding test standard. By using OntoFNCT for storing full-notch creep test data, all data will be well structured and based on a common vocabulary agreed on by an expert group (generation of FAIR data) which is meant to lead to enhanced data interoperability. This comprises several data categories such as primary data, secondary data and metadata. Data will be human and machine readable. The usage of OntoFNCT facilitates data retrieval and downstream usage. Due to a close connection to the mid-level PMD core ontology (PMDco), the interoperability of full-notch creep test data is enhanced and querying in combination with other aspects and data within the broad field of materials science and engineering (MSE) is facilitated.
The class structure of OntoFNCT forms a comprehensible and semantic layer for unified storage of data generated in a full-notch creep test including the possibility to record data from analysis and re-evaluation. Furthermore, extensive metadata allows to assess data quality and reliability. Following the open world assumption, object properties are deliberately low restrictive and sparse.
In the field of computational science and engineering, workflows often entail the application of various software, for instance, for simulation or pre- and postprocessing. Typically, these components have to be combined in arbitrarily complex workflows to address a specific research question. In order for peer researchers to understand, reproduce and (re)use the findings of a scientific publication, several challenges have to be addressed. For instance, the employed workflow has to be automated and information on all used software must be available for a reproduction of the results. Moreover, the results must be traceable and the workflow documented and readable to allow for external verification and greater trust. In this paper, existing workflow management systems (WfMSs) are discussed regarding their suitability for describing, reproducing and reusing scientific workflows. To this end, a set of general requirements for WfMSswere deduced from user stories that we deem relevant in the domain of computational science and engineering. On the basis of an exemplary workflow implementation, publicly hosted at GitHub (https:// this http URL), a selection of different WfMSs is compared with respect to these requirements, to support fellow scientists in identifying the WfMSs that best suit their requirements.
Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction
(2024)
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
This is a set of use examples for the HDF5Translator framework. This framework lets you translate measurement files into a different (e.g. NeXus-compatible) structure, with some optional checks and conversions on the way. For an in-depth look at what it does, there is a blog post here.
The use examples provided herein are each accompanied by the measurement data necessary to test and replicate the conversion. The README.md files in each example show the steps necessary to do the conversion for each.
We encourage those who have used or adapted one or more of these exampes to create their own conversion, to get in touch with us so we may add your example to the set.
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