eData: the STFC Research Data Repository
Not a member yet
948 research outputs found
Sort by
Dataset supporting the publication: "Computational and spectroscopic characterisation of thianthrene" in Royal Society Open Science 2024.
No full textThis dataset supports the publication: Computational and spectroscopic characterisation of thianthrene, (Rachel H. Rushworth, Matei Pascariu, Mona Sarter and Stewart F. Parker, Royal Society Open Science (2024)).
The dataset consists of a README file (README_Parker_Thianthrene_dataset.txt), two zip files: "A-Experimental_spectra", "B-CASTEP". and an image file: Thianthrene_Mode_at_862cm.jpg.
The README describes the contents of the archive.
A-Experimental_spectra.zip contains the DSC data and the infrared, Raman and inelastic neutron scattering spectra.
B-CASTEP.zip contains the input and output files for the calculation of the complete unit cell and the C2v symmetry isolated molecule
Experimental and simulation dataset for a Multi-modal imaging detector proof of concept and associated paper
No full textDataset associated with the Review of Scientific Instruments article titled "Simultaneous co-axial multi-modal inspection using a laser driven x-ray and neutron source" published in 2024. Dataset includes all relevant raw data, a detailed shotsheet providing necessary metadata for the experimental work, python files to generate each figure in the manuscript, and simulation input decks used in the manuscript.
The directory "./data/" contains image files (.tif) generated with a Hamamatsu Image Intensifier system and neutron time-of-flight traces (.csv) generated with a PMT and Teledyne Lecroy oscilloscope, and the shotsheet (.xlsx) with pertinent experimental information. Each figure (excluding figure 3, which is an experimental layout diagram) is generated using python (version 3.8.5) and associated standard scientific libraries (numpy, matplotlib, PIL, pandas, scipy), the files to generate each figure have been included in the DOI.
Figure 6 includes simulation data generated with G4 Beamlines version 3.08, the necessary input deck is included (./simulation/TAW_bimodal_detector.g4bl) as well a directory for the neutron simulation (./simulation/3MeV_neutrons/) and x-rays (./simulation/200keV_x-rays/), within each directory is the necessary "trackFile.txt" which defines the spectral content of the each simulated beam and "totalEnergy.txt" which is the output file from the simulation. The totalEnergy.txt for each simulation is read by the fig6_generate.py and contains two columns with the detector volume (world, pixels 1-3250, etc.) and the energy deposited in each. Installation instructions for G4 Beamlines can be found at the website: https://www.muonsinc.com/Website1/G4beamline .LLNL - Contract DE-AC52-07NA27344
LLNL - 20-ERD-048
LLNL - 21-ERD-015
DOE - SCW172
Comparison of PRNGs to QRNGs using Monte Carlo Pi estimation
No full textThis collection contains the source code and processed data used to investigate effects of the random number source on the outcomes of simple Monte Carlo simulations. Investigation was carried out using Quantum Dice's quantum random number generator (QRNG) and various sequential and parallel pseudo-random number generators (PRNG). PRNGs include: "minimum standard" linear congruential generator (minstd_rand0), Mersenne Twister generator (mt19937), multiplicative recursive generator (Tina's random number generator library mrg5s), "yet another random number generator" (Tina's random number generator library yarn5s) in parallel and sequential executions.
The C++ code is used to generate pi estimates through sampling of [0,1]x[0,1] or using Buffon's needle experiment utilising various RNGs. Additional code is used to generate and store point distributions on [0,1]x[0,1] to asess their homogeneity and uniformity as means to explain observations made when analysing distributions of the pi data.
Raw data was collected using Snakemake workflows provided in the dataset. Accumulation of raw data into provided CSV files was done using an accompanying jupyter notebook.
Distributions of the estimated pi-values were analysed using a simple sign-test, t-test, distribution fitting and likelihood-based hypothesis testing incorporated in the SciPaperVisualisation notebook. Additionally correlations within the pi-datasets and effects of rounding errors were analysed and the results are included in the same notebook.
Further the homogeneity of the point-distribution on the unit square obtianed with QRNGs and PRNGs was analysed to explain the differences observed in the pi-data.Project No. 1003183
Dataset supporting the publication: "Pagodane – Solution and Solid-state Vibrational Spectra" published in Physchem (2024).
No full textThis dataset supports the publication: Pagodane – Solution and Solid-state Vibrational Spectra, (Stewart F. Parker, Hannah E. Mason and Campbell T. Wilson, Physchem (2024)). The dataset consists of a README file (README_Parker_Pagodane_dataset.txt), two zip files: "A-Experimental_spectra", "B-CASTEP". and an image file: Pagodane.jpg. The README describes the contents of the archive. A-Experimental_spectra.zip contains the solution and solid-state infrared, Raman and inelastic neutron scattering spectra. B-CASTEP.zip contains the input and output files for the CASTEP calculation of the complete unit cell at the experimental lattice parameters, with optimised lattice parameters and the D2h symmetry isolated molecule
Data supporting the publication: "A multi-wavelength Raman study of some oligothiophenes and polythiophene."
No full textThis dataset supports the publication: A multi-wavelength Raman study of some oligothiophenes and polythiophene", (S.F. Parker et al, Physchem (2023)).
The dataset consists of a README file (README_Parker-Thiophenes_Raman_dataset.txt), six zip files: 1-Raman-325nm-spectra.zip, 2-Raman-405nm-spectra.zip, 3-Raman-532nm-spectra.zip, 4-Raman-633nm-spectra.zip, 5-Raman-785nm-spectra.zip and 6-Raman-1064nm-spectra.zip and an image file: Oligothiophenes.jpg
1-Raman-325nm-spectra.zip contains the files: Bithiophene_325nm.dat, Octithiophene_325nm.dat, Polythiophene_325nm.dat.
2-Raman-405nm-spectra.zip contains the files: Bithiophene_405nm.dat, Octithiophene_40nm.dat, Polythiophene_405nm.dat, Quartithiophene_405nm.dat, Sexithiophene_405nm.dat.
3-Raman-532nm-spectra.zip contains the files: Bithiophene_532nm.dat, Octithiophene_532nm.dat, Polythiophene_532nm.dat, Sexithiophene_532nm.dat, Terthiophene_325nm.dat. Note that there is an approximately 11 cm-1 calibration error in the 532 nm data.
4-Raman-633nm-spectra.zip contains the file: Polythiophene_633nm.dat.
5-Raman-785nm-spectra.zip contains the files: Bithiophene_785nm.dat, Octithiophene_785nm.dat, Polythiophene_785nm.dat, Sexithiophene_785nm.dat, Terthiophene_785nm.dat.
6-Raman-1064nm-spectra.zip contains the files: Bithiophene_1064nm.dat, Octithiophene_1064nm.dat, Polythiophene_1064nm.dat, Quartithiophene_1064nm.dat, Sexithiophene_1064nm.dat, Terthiophene_1064nm.dat.
All of the Raman spectra are present as two column (wavenumber and intensity) ASCII data and may be viewed with any text reader or can be loaded into programs such as Excel or Origin to display the spectra.RB172005
Datasets and figures exploring x-ray imaging performance analytically for manuscript titled: "X-ray detector requirements for laser-plasma accelerators"
No full textData used in each figure for the manuscript titled: "X-ray detector requirements for laser-plasma accelerators". Figure files are each self contained .py scripts requiring Python version 3.8.5+, and standard scientific libraries Numpy, Matplotlib and Scipy to execute the scripts. Relevant cross-section/spectral data is included for persistent plotting as well as analytical functions described in the manuscript.EP/ V049232/
Data Supporting Publication in Frontiers in Soft Matter - Simulating micelle self-assembly to assess potential for viscosity build in surfactant formulations
No full textData relating to the publication of the publication entitled "Simulating micelle self-assembly to assess potential for viscosity build in surfactant formulations"
Summary of data available:
[1] Nagg_data_repository.zip - contains the raw data for aggregation behaviour over time.
[2] .agr files corresponding to figures 4, 5, 6, 7 and 8 in the published article. These .agr files can be used to plot the observed behaviours in Xmgrace. Each .agr file contains the raw data in the plots and this can be extracted for use in other plotting algorithms.
[3] Example input files for DL_MESO required to complete simulations in the article
[4] shape.zip - contains the raw data obtained for average shape metric
V2_3D dataset of the X-ray Computed Tomography and plugin graph results
No full textV2: This dataset is an updated version of the previous Part 2/2 (http://dx.doi.org/10.5286/edata/901). This version includes updated Part 2.c graph outputs.
Part 1/2: The first half of the dataset is composed of the Avizo plugin, which can be found in the DOI http://dx.doi.org/10.5286/edata/900
Part 2/2: This second half of the dataset is composed of the X-ray computed tomography data used in the study and their outputs. 2.a is composed of the XCT region of interest (ROI) showing the individual micro drilled holes, previously measured in the SEM. 2.b contains the isolated cube ROI used in the porosity analysis. 2.c contains the plugin graph outputs for each hole, when using the Avizo plugin.
The XCT data in 2.a and 2.b is a subvolume of the full scan of an additive manufactured flexure containing a reference pin with micro drilled holes, measured in the scanning electron microscope (SEM). The scan settings included a voltage of 145 kV, filament current of 41 µA, number of projections of 1650 and a voxel size of 8.5 µm × 8.5 µm × 8.5 µm. After reconstruction, the scan was converted from 32 bit to 8-bit, aligned to the CAD and resampled, resulting in a voxel size change to 9.4 µm × 9.4 µm × 8.8 µm. Detailed use of the XCT scan dataset and resulting plugin graphs can be found in the study titled "Development of a modular system to provide confidence in porosity analysis of additively manufactured components using X-ray computed tomography"
SORS spectra of COVID-19 Vaccine
No full textSpatially Offset Raman Spectra of 45 genuine covid-19 vaccines, and surrogates for potential and intercepted falsified vaccines . The Raman spectra were collected using a handheld commercial SORS instrument (Resolve, Agilent Technologies, Oxfordshire, UK)Ref. 2021/1170671-
Microfluidics and Nanofluidics journal article - "Numerical investigation of transmission probability characteristics in the first low-density region of a laser wakefield accelerator"
No full textRelevant data supporting the manuscript "Numerical investigation of transmission probability characteristics in the first low‑density region of a laser wakefield accelerator" submitted to the Microfluidics and Nanofluidics journal (accepted for publication in July 2023)