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xraylib 3.1.0
(2014)
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!
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.
XMI-MSIM 5.0
(2014)
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.
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].
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.
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.