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4,070 results for “plasma”
Validated TRANSP simulations of Alcator C-Mod Experimental Plasma
<p>This dataset contains the inputs and outputs from TRANSP plasma transport simulations initialized using experimental data from the Alcator C-Mod tokamak plasma experimental device. The simulations include sawtooth instabilities according to the Kadomtsev model and the outputs are time-averaged over these crashes to emulate steady-state plasma scenarios.</p> <p>The data is stored within a NETCDF4 file written using the Python xarray package, which can be opened via the xarray package with the `open_dataset()` function. Only a subset of the output fields deemed relevant for plasma transport simulations are included, in order to reduce data bloat. For more information on the TRANSP code, including its input and output fields, please see https://transp.pppl.gov/.</p>
DATA: As-deposited and dewetted Cu layers on plasma treated glass: adhesion study and its effect on biological response
<p>Dataset contains data related to improving the adhesion of nanosized copper films to a glass substrate. </p>
The impact of 11 May 2024 super geomagnetic storm on the plasma distribution over the Indian equatorial/low latitude ionospheric region
<p>The file contains the data set and the software for the generation the plots used in the manuscript " The impact of 11 May 2024 super geomagnetic storm on the plasma distribution over the Indian equatorial/low latitude ionospheric region".</p>
Nitrite content in powders from plasma-activated egg whites
<p>These are source data collected to determine the effects of three quantitative independent variables—plasma treatment time, the distance of the plasma source from the surface of egg whites, and drying temperature—on the nitrite concentration (mg·kg⁻¹) in powdered plasma-treated egg whites sourced from both hens and ostriches. The experimental ranges for these variables were as follows: plasma treatment time (20-180 minutes), plasma source distance (10-30 cm), and drying temperature (40-50 °C).</p> <p>The analysis of nitrite content in all samples was conducted according to the method of Lee et al. (2018) with some modifications.</p> <p>A design comprising 20 experimental runs was generated using Design Expert (version 11) software (Stat-Ease, Inc., USA).</p>
Magnetic arch plasma expansion in a cluster of two ECR plasma sources (RPA and FC measurements)
<p>- Data from: Magnetic arch plasma expansion in a cluster of two ECR plasma sources (RPA and FC measurements)</p> <p>- Authors: Célian Boyé, Jaume Navarro-Cavallé, Mario Merino</p> <p>- Contact email: <a href="mailto:cboye@ing.uc3m.es" target="_blank" rel="noopener">cboye@ing.uc3m.es</a></p> <p>- Date: 2024-10-24</p> <p>- Version: 1.0</p> <p>- License: This dataset is made available under the <a href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</a></p> <p> </p> <h2>Abstract</h2> <p>This dataset contains the raw experimental data employed in:</p> <p>Célian Boyé, Jaume Navarro-Cavallé, Mario Merino, "Magnetic arch plasma expansion in a cluster of two ECR plasma sources", Journal of Electric Propulsion.</p> <p>Which is currently submitted.</p> <p> </p> <h2>Dataset description</h2> <p>The experimental data is gathered by means of a Retarding Potential Analyzer (RPA) and a Faraday Cup (FC). The probes have been set on a polar probing arm system to scan the central horizontal plane of the setup, aligned with the axis of symmetry of the assembly and pointing toward the origin at the exit plane of the source(s).</p> <p>The RPA data is provided separately for every spatial position inspected for each configuration (S0, S1, D0, DA, DB). It is collected by means of an Impedance-Semion Retarded Potential Analyser, with a mean resolving voltage of 1V. The FC data is provided for the DA configuration to support the RPA measurements. </p> <p>Please refer to the corresponding article for further details regarding the data collection.</p> <p> </p> <h2>Data files</h2> <p>The data files are in standard comma separated values .csv format. Many programming languages provide functionalities to load such fields.</p> <ul> <li> <h3>RPA data</h3> </li> </ul> <p>The RPA data is separated through the different configurations:</p> <ul> <li> <ul> <li>S0: single ECR source without applied magnetic field.</li> <li>S1: single ECR source with applied magnetic field.</li> <li>D0: cluster of ECR sources without applied magnetic field.</li> <li>DA: cluster of ECR sources with opposed polarity.</li> <li>DB: cluster of ECR sources with same polarity.</li> </ul> </li> </ul> <p>The angle steps vary through the different configurations. Each file contains 8 headlines. </p> <ul> <li> <ul> <li>The first column contains the voltage applied to the sweeping grid (V).</li> <li>The second to sixth columns contain the current collected by the collector (A).</li> <li>The eventh to eleventh columns contain the derivative of the collected current by the voltage (A/V).</li> </ul> </li> </ul> <ul> <li> <h3>FC data</h3> </li> </ul> <p>The FC data has been probed for the DA configuration. The file contains 2 headlines.</p> <ul> <li> <ul> <li>The first column contains the angle at which the current has been collected (deg).</li> <li>The second column contains the distance from the origin at the exit plane of the cluster (mm).</li> <li>The third column contains the collected current (A).</li> </ul> </li> </ul> <p> </p> <h2>Citation</h2> <p>Works using this dataset or any part of it in any form shall cite it as follows.</p> <p>The preferred means of citation is to reference the publication associated to this dataset, as soon as it is available.</p> <p>Optionally, the dataset may be cited directly by referencing the corresponding DOI: 10.5281/zenodo.13987138</p> <p> </p> <h2>Acknowledgments</h2> <p>This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (project ERC-STG ZARATHUSTRA, grant agreement No 950466). </p>
Reproduction package for the publication 'New radiative loss curve from updates to collisional excitation in the low-density, optically thin plasmas in SPEX'
<p>The following files can be used to reproduce the Figures and data from the paper <strong>New radiative loss curve from updates to collisional excitation in the low-density, optically thin plasmas in SPEX </strong>by L. Štofanová, J. Kaastra, M. Mehdipour, and J. de Plaa accepted to be publish in Section 12. Atomic, molecular, and nuclear data of Astronomy and Astrophysics (acceptance date - 27/06/2021).</p> <p> </p> <p>Note: version 2 is the most updated version (change in Fig.7).</p>
Data for "On Ohm's law in reduced plasma fluid models"
<p>Simulation data and post-processing scripts to create the figures in the paper "On Ohm's law in reduced plasma fluid models", published in <em>Plasma Physics and Controlled Fusion</em>.</p> <p>To re-produce the figures, install the Python package `xbout` (using pip: `pip install xbout`; or conda: `conda install xbout`), unzip the file from this archive, and run the script `make_paper_figures.py`. Figure 1 is `finite_Ti_plots/compare-sims_baseall/CoM_midplane0.pdf`; figure 2a is `finite_Ti_plots/compare-sims_base/timestep.pdf`; figure 2b is `finite_Ti_plots/compare-sims_base/rhs_evals.pdf`.</p>
Reference dataset of multi-objective and multi-fidelity optimization in laser-plasma acceleration
<p>This repository contains a dataset used for the article "<em>Multi-objective and multi-fidelity Bayesian optimization of laser-plasma acceleration</em>" (<a href="https://arxiv.org/abs/2210.03484">arXiv:2210.03484</a>). The dataset consists of 2443 FBPIC particle-in-cell simulations of a laser wakefield accelerator that were selected using a Bayesian optimizer. The goal of the optimization was to perform multi-objective multi-fidelity optimization of electron beam parameters. The dataset contains simulations of different resolutions, accordingly with differing fidelities. The typical runtime at lowest (highest) resolution is approximately 1 (90) minutes.</p> <p>In the dataset we have <em>train_x </em>and <em>train_obj </em>numpy arrays with dimensions <em>(n,5)</em> and<em> (n,3)</em>, respectively. Here <em>n</em> is the number of FBPIC simulations. The five columns in <em>train_x </em>are [plasma density, upramp length, laser focus, downramp length, fidelity]. The fidelity parameter controls the resolution and hence the runtime of the simulation. The three columns in the <em>train_obj </em>are the [total charge, distance of median to target energy, bandwidth of electron beams]. For the distance, the target energy is fixed to 300 MeV and for the bandwidth is defined by the median absolute deviation around the median. The two columns have negative values since the optimizer assumes a maximization of all objectives while the distance and bandwidth in this study were being minimized.</p> <p>The different folders contain data of different kind of single and multi-objectives that were used to produce figures 2, 3, 5 in the associated paper. For more details please see the referred article. The folder "combined" contains the data of all simulations together and is most suitable for (5D x 3D) surrogate model generation.</p>
Strong collisionless coupling between an unmagnetized driver plasma and a magnetized background plasma
<p>This repository contains some of the simulation data presented in the recent article in plasma physics titled "Strong collisionless coupling between an unmagnetized driver plasma and a magnetized background plasma" (<a href="https://arxiv.org/abs/2302.00149">https://arxiv.org/abs/2302.00149</a>). The data available are for 1D particle-in-cell (PIC) simulations that consider the interaction between a uniform unmagnetized driver plasma flowing against a uniform magnetized background plasma, for multiple values of the driver density and background magnetic field. The simulations were performed with OSIRIS, a massively parallel and fully-relativistic, PIC code.</p> <p>Using the data from the simulations, we studied the coupling between the plasmas and determined the compression ratio and the velocities of the magnetic cavity and magnetic compression that were visible in the simulations. More information on the simulations and on the obtained results are presented in the article.</p> <p>The datasets contain the main data of some of the simulations presented in the paper (.h5 files), the coupling parameters measured in the simulations (coupling_data.csv), and a Jupyter Notebook file to look at the simulation results from the available datasets (read_dataset.ipynb).</p>
Two metabolomics data sets (mouse kidney, mouse plasma), generated for the publication Bignon et al., 2023: "Multiomics reveals multilevel control of renal and systemic metabolism by the renal tubular circadian clock".
<p><strong>Publication: </strong>Bignon Y, Wigger L, Ansermet C, Weger BD, Lagarrigue S, Centeno G, Durussel F, Götz L, Ibberson M, Pradervand S, Quadroni M, Weger M, Amati F, Gachon F, Firsov D. Multiomics reveals multilevel control of renal and systemic metabolism by the renal tubular circadian clock. J Clin Invest. 2023 Mar 2:e167133. doi: 10.1172/JCI167133. Epub ahead of print. PMID: 36862511.</p> <p> </p> <p><strong>Abstract: </strong> Circadian rhythmicity in renal function suggests rhythmic adaptations in renal metabolism. To decipher the role of the circadian clock in renal metabolism, we studied diurnal changes in renal metabolic pathways using integrated transcriptomic, proteomic, and metabolomic analysis performed on control mice and mice with inducible deletion of the circadian clock regulator Bmal1 in the renal tubule (cKOt). With this unique resource, we demonstrated that ~30% RNAs, ~20% proteins and ~20% metabolites are rhythmic in kidneys of control mice. Several key metabolic pathways including NAD+ biosynthesis, fatty acid transport, carnitine shuttle,and b-oxidation displayed impairments in kidneys of cKOt, resulting in a perturbed mitochondrial activity. Carnitine reabsorption from the primary urine was one of the most impacted processes with a ~50% reduction in plasma carnitine levels and a parallel systemic decrease in tissues carnitine content. This suggests that the circadian clock in the renal tubule controls both kidney and systemic physiology.</p> <p> </p> <p><strong>This record contains two separate mass-spectrometry metabolomics data sets associated with this study:</strong></p> <ol> <li>Metabolic profile of renal tubules, MS/MS data, Metabolon, Morrisville, NC (N=60)</li> <li>Metabolic profile of blood plasma, MS/MS data, Biocrates, Innsbruck, Austria (N=60)</li> </ol> <p>For each data set, original data as received from the platforms and processed data as used in the data analysis are provided. Preprocessing of kidney data included removal of metabolites with more than 80% missing data values, median normalization, imputation and glog2 transformation. Preprocessing of plasma data included filtering of metabolites with any missing data and log2 transformation. Details of data processing are available in the STAR*methods of the publication.</p> <p> </p> <p><strong>Data sets in other repositories associated with the same study:</strong></p> <p>Additional data sets (transcriptomics, proteomics) pertaining to the same study have been deposited in public repositories:</p> <ul> <li>Gene Expression Omnibus (NCBI GEO), GSE216252</li> <li>PRIDE Archive (EMBL-EBI), PXD036803</li> </ul> <p> </p>
Polar / Plasma Waves Investigation processed dataset and ephemeris used to produced the Smith et al. (2022) catalogue (doi:10.5281/zenodo.7260994 )
<p>This data set contains Polar / Plasma Waves Investigation processed using the SPACE Labelling Tool (Louis et al., 2022, doi:10.5281/zenodo.6886528). It also contains the Polar ephemeris in the geocentric solar ecliptic (GEO) coordinate system (from https://sscweb.gsfc.nasa.gov/cgi-bin/Locator.cgi)</p> <p>This processed dataset contains Auroral Kilometric Radiation (AKR) observations and was used to produced the Smith et al. (2022) catalogue of AKR (doi:10.5281/zenodo.7260994)</p> <p>This work has been funded by Science Foundation Ireland Grant 18/FRL/6199, and by a 2022 SCOSTEP/PRESTO<br> Grant.</p>
Data-driven plasma modelling: Fluorocarbon ICP data set
<p>This is an open source dataset of optical emission spectra and optical images in fluorocarbon plasmas, along with associated tool logs, captured from a Oxford Intruments Plasma Technology PP100 ICP etcher. The dataset consists of Ar, O<sub>2</sub>, Ar/O<sub>2</sub>, CF<sub>4</sub>/O<sub>2</sub> and SF<sub>6</sub>/O<sub>2</sub> gas mixtures etching Si wafers.</p> <p>The data has been split into chunks for uploading to Zenodo, to reconstruct them:</p> <p>$ cat generative_model-fluorocarbon_data_set.tar.xz* > generative_model-fluorocarbon_data_set.tar.xz </p> <p>$ tar -xvf generative_model-fluorocarbon_data_set.tar.xz </p> <p>You can find the code to train an autoencoder model using the optical emission spectra and optical images at our github repo, https://github.com/gregdaly/generative_modelling_for_optical_plasma_diagnostics </p>
Stability of the Modulator in a Plasma-Modulated Plasma Accelerator
<p>Input decks for the particle-in-cell code WarpX used in a new study to simulate the modulator stage of a recently proposed laser-plasma accelerator scheme [Phys. Rev. Lett. <strong>127</strong>, 184801 (2021)], dubbed the Plasma-Modulated Plasma Accelerator (P-MoPA). </p>
Ionization of sputtered material in high power impulse magnetron sputtering plasmas - comparison of titanium, chromium and aluminum
<p>Experimental data set and modeling results to an upcoming publication titled: "Ionization of sputtered material in high power impulse magnetron sputtering plasmas - comparison of titanium, chromium and aluminum".</p> <p>The dataset contains current and voltage measurements (current-voltage-XX.txt), Langmuir probe measurements (probe-XX.txt) performed 8 mm above the racetrack position (using the method described here https://doi.org/10.1088/1361-6595/ab5e46), model results as explained in the paper and spectroscopic imaging profiles. The spectroscopic imaging profiles are obtained from Abel-inverted images in the radial direction by integrating between z=1mm and z=3mm and in the axial direction between r=12mm and r=15mm.</p>
THE StellaR PAth WP1: Sun-as-a-star plasma Emission Measure Distributions
<p>This folder contains a set of plasma Emission Measure Distributions (EMDs) vs. temperature, derived from observations of the solar corona with the Soft X-ray Telescope (SXT) on board the solar satellite Yohkoh, and the prescription to build EMDs for coronae of solar-type stars with different activity levels, including both quiescent and flaring components. For details read the Description PDF file.</p>
Ionome analysis of Salmonella mutants by Inductively coupled plasma mass spectrometry (ICP-MS)
<p>In many Gram-negative bacteria, the stress sigma factor of RNA polymerase, σS/RpoS, remodels global gene expression to reshape the physiology of quiescent cells and ensure their survival under non-optimal growth conditions. In the foodborne pathogen <i>Salmonella enterica</i> serovar Typhimurium, σS is also required for biofilm formation and virulence.</p><p>We have previously shown that a Δ<i>rpoS</i> mutation affects the <i>Salmonella</i> ionome. Indeed, inductively coupled plasma mass spectrometry analyses have unraveled a significant effect of the Δ<i>rpoS </i>mutation on the cellular concentration of manganese, magnesium, cobalt and potassium, suggesting that σS controls fluxes of ions that might be important for the fitness of quiescent cells (Metaane et al. 2022, PLoS ONE 17(3): e0265511).</p><p>Study: These findings prompted us to evaluate the impact on the<i> Salmonella</i> ionome of deletions of genes encoding the <i>Salmonella</i> Mn2+ transporters (<i>sitABCD</i> and <i>mntH</i>), the Co2+ transporter (<i>cbiMNQO</i> operon) and small proteins of unkown function (<i>yqaE</i> and <i>yqjDEK</i>) that accumulate in quiescent <i>Salmonella</i> under the tight control of σS (Levi-Meyrueis et al. PloS one. 2014; 9(5):e96918, Lago et al. Scientific reports. 2017; 7(1):2127 and Metaane et al. 2022, PLoS ONE 17(3): e0265511).</p><p>Material and Methods: Cell-associated contents of several elements were measured by inductively coupled plasma mass spectrometry (ICP-MS) as previously described in Metaane <i>et al </i>2022 PLoS ONE 17(3): e0265511.Dried cell pellets were prepared by V. Monteil and F. Norel (Institut Pasteur, Université de Paris, CNRS UMR3528, Biochimie des Interactions Macromoléculaires, F-75015, Paris, France). Cell-associated contents of several elements were measured by S. Ayrault and L. Bordier (ICP-MS platform, Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRSUVSQ,Université Paris-Saclay, 91191, Gif-sur-Yvette, France)</p><p><strong>This work was supported by the French National Research Agency (ANR-19-CE44-0005-01, PERIOMET project).</strong></p><p><strong>Linked studies:</strong></p><ul><li>NOREL Francoise, MONTEIL Veronique, DOUCHE Thibaut, & MATONDO Mariette. (2023). Global effects of deletions of the sitABCD, mntH, cbiMNQO and corA genes, encoding transporters for manganese, cobalt and magnesium on protein abundance in Salmonella enterica serovar Typhimurium grown to stationary phase in LB. [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8279780</li><li>Metaane S, Monteil V, Douché T, Giai Gianetto Q, Matondo M, Maufrais C, Norel F. Loss of CorA, the primary magnesium transporter of <i>Salmonella, </i>is alleviated by MgtA and PhoP-dependent compensatory mechanisms. PloS one. 2023;18(9):e0291736.</li></ul>
Plasma etching for fabrication of complex nanophotonic lasers from bonded InP semiconductor layers
<p>Integrating optically active III-V materials on silicon/insulator platforms is one potential path towards improving the energy efficiency and performance of modern computing. Here we demonstrate the applicability of direct wafer bonding combined with plasma etching to the fabrication of complex nanophotonic systems out of InP layers. We explore and optimise the plasma etching of InP, validating existing processes and developing improved ones. We explore the use of microdisk lasing as a way to evaluate fabrication fidelity, and demonstrate that we can create complex lasing systems of interest to us: coupled disk cavities and random network lasers.</p> <p><strong>This repository contains data used to generate figures in <a href="https://doi.org/10.1016/j.mne.2023.100196">https://doi.org/10.1016/j.mne.2023.100196</a>.</strong></p>
The Plasma-Prescribed Active Region Static Extrapolation Dataset
<p>The Plasma-Prescribed Active Region Static Extrapolation (PARSE) Dataset consists of approximately seven thousand magnetohydrostatic extrapolations of solar active regions for use in statistical or machine learning applications. The extrapolations are based on the Spaceweather HMI Active Region Patch (SHARP) library (doi <a href="https://doi.org/10.1007/s11207-014-0529-3">10.1007/s11207-014-0529-3</a>), and the magnetohydrostatic extrapolation is performed by the routine detailed in Mathews et al 2022 (doi <a href="https://doi.org/10.1016/j.jcp.2022.111214">10.1016/j.jcp.2022.111214</a>). </p>
Basins of attractions for six types hidden quasiperiodic attractors in a Thomas Fermi plasma
<p>This figures (a) and (b) represent cross-section of the basins of attractions on the z-x plane with f<sub>0</sub> equal to 3:96 and 6:5 respectively, for multistability behaviors or coexisting attractors of ion-acoustic waves in a magnetized Thomas Fermi plasma.<br> </p>
Transport Ratios for Plasma Waves Observed by MAVEN at Mars
<p>Transport ratios calculated for coherent plasma waves observed upstream from Mars by the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission. These values were calculated by sub-sampling the ion velocity distribution measurements made by the Solar Wind Ion Analyzer (SWIA) instrument and binning them by the wave phase as estimated from the vector magnetic field measured by the Magnetometer (MAG) instrument. </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.