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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.
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).
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).
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).
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).
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.
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).
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 "
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.
Test artifact for fs-LDW
(2023)