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501 results for “Charging”
Control of Charge-Spin Interconversion in van der Waals Heterostructures with Chiral Charge Density Waves
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Data associated to the manuscript "Simulating the charging mechanism of a realistic nanoporous carbon-based supercapacitor using a fully polarizable model"
<p>Contains input files and data used to generate the figures of the article:</p> <p>Simulating the charging mechanism of a realistic nanoporous carbon-based supercapacitor using a fully polarizable model</p> <p>Camille Bacon, Patrice Simon, Mathieu Salanne and Alessandra Serva</p> <p><em>ChemRxiv, </em>10.26434/chemrxiv-2024-9577m, 2024</p> <p>The folder <em>input_files</em> contains typical MetalWalls input files used to perform the simulations.</p> <p>The folder <em>raw_data</em> contains the processed data used to plot all the figures of the paper.</p>
Online data of "Strong hole-photon coupling in planar Ge for probing charge degree and strongly correlated states"
<h1>Online data of "Strong hole-photon coupling in planar Ge for probing charge degree and strongly correlated states"</h1> <p>DOI: https://doi.org/10.1038/s41467-024-54520-7</p> <h2>Authors</h2> <ul> <li>Franco De Palma</li> <li>Fabian Oppliger</li> <li>Wonjin Jang</li> <li>Stefano Bosco</li> <li>Marián Janík</li> <li>Stefano Calcaterra</li> <li>Georgios Katsaros</li> <li>Giovanni Isella</li> <li>Daniel Loss</li> <li>Pasquale Scarlino</li> </ul> <h2>Description</h2> <p>The data for all figures in the main text can be found in csv files in ASCII format in the corresponing folders. For Figures 4-6, the panels are numbered from top to bottom.</p>
Dataset for "Research on the effect of the refrigerant charge in a variable capacity heat pump"
<p>The Excel file contains raw experimental data of 75 experiments.<br>Measured parameters include: temperatures (T), gauge pressures (P), volumetric flow rates (V), compressor electric power (Welec) and atmopheric pressure.<br>See Figure 1 of the paper for the numbering and position of the different sensors.<br>See Table 2 of the paper for the types of sensors used and their accuracies.</p>
Impedance and Charge Density Data
<p>Impedance and charge density data for four particpants. Each sheet represents all the channels associated with one participant and one cuff. Impedance data is listed first then charge density data.</p>
Dataset for 'Smart Health Evaluation for Lithium-ion Battery with Super-short-segment Charging'
<p>This is the dataset used in our paper '<em>Smart Health Evaluation for Lithium-ion Battery with Super-short-segment Charging</em>', which mainly includes data from <strong>40Ah batteries</strong> at <strong>0.3C, 1C, 2C</strong>, and two <strong>280Ah batteries</strong> at <strong>20%, 60%, and 100% DOD</strong>, respectively. For specific details, please refer to Readme.text</p> <p>The data in<strong> LISHEN</strong> is the cycle test data of 40Ah battery at different discharge depths under 100%,60%,20%DOD working condition. The data in <strong>CATL</strong> and<strong> EVE </strong>is the cyclic test data of 280Ah battery at different discharge depths under 100%,60%,20%DOD conditions. <br>The CSV file has 21 or 17 columns, (17 columns for, data sequence number, good cycling, step number, step type, time (s) , total time (s) , current (a) , voltage (V) , capacity (AH) , charging capacity (AH) , discharge capacity (AH) , energy (Wh) , charging energy (Wh) , discharge energy (Wh) , absolute time (s) , power (W) , temperature (° C-RRB-) , the 21-column CSV adds four metrics (DQ/DV (AH/V) in column 17, dQm/DV (mAh/V) in column 18, contact resistance (m ω) in column 19, and module start-stop status in column 20) , More detailed files can be found in the zip file.</p>
Re-charging your fats: Charmm36 parameters for neutral lipids triacylglycerol and diacylglycerol
<p>Dataset containing files required to run the simulations and reproduce the Figures appearing in "Re-charging your fats: Charmm36 parameters for neutral lipids triacylglycerol and diacylglycerol"</p>
Spin-Charge Conversion in Fe/Au/Sb2Te3 Heterostructures as Probed By Spin Pumping Ferromagnetic Resonance (data)
<p>This dataset contains the raw data files connected with the figures included in the paper "<em>Spin-Charge Conversion in Fe/Au/Sb<sub>2</sub>Te<sub>3</sub> Heterostructures as Probed By Spin Pumping Ferromagnetic Resonance</em>" by <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/admi.202101244">E. Longo et al.<em>, </em><em>Adv. Mater. Interfaces</em> 2021, 2101244</a>.</p>
Examining the charge transfer in an unusual negative rocket-triggered lightning flash with branched upward positive leaders
<p>The data of the Case Tr_201807, figures, Optical images </p>
Research Data Supporting "Electrostatic co-assembly of nanoparticles with oppositely charged small molecules into static and dynamic superstructures"
<p>This repository contains the set of data shown in the paper "<strong>Electrostatic co-assembly of nanoparticles with oppositely charged small molecules into static and dynamic superstructures</strong>", published on <strong>Nature Chemistry </strong>(DOI: 10.1038/s41557-021-00752-9).</p> <p>The files in the folders are organized as follow:</p> <p><strong>AA_models/ : </strong>contains all the files needed to run the Atomistic simulations discussed in the paper (including the topologies and starting configurations).</p> <p><strong>CG_models/ : </strong>contains all the files needed to run the Coarse Grained simulations discussed in the paper (including the topologies and starting configurations).</p> <p><strong>citrate_analysis/ : </strong>contains all the files needed to reproduce the analysis of the CV and SOAP+PCA+PAMM (including input files and python scripts).</p> <p>Additional details are available in the methods section and in the Supporting Information of the main paper.</p>
Supplementary data: Na2.4Al0.4Mn2.6O7 anionic redox cathode material for sodium ion batteries- a combined experimental and theoretical approach to elucidate its charge storage mechanism
<p>This data repository contains the output files of density-functional theory (DFT) calculations that were used for the paper "Na2.4Al0.4Mn2.6O7 anionic redox cathode material for sodium ion batteries- a combined experimental and theoretical approach to elucidate its charge storage mechanism". </p>
Nanotubes from the Misfit Layered Compound (SmS)1.19TaS2: Atomic Structure, Charge Transfer, and Electrical Properties_experimental dataset
<p>This dataset contains the raw experimental data for the Sreedhara et al., Nanotubes from the Misfit Layered Compound (SmS)1.19TaS2: Atomic Structure, Charge Transfer, and Electrical Properties, <em>Chem. Mater.</em> 2022, 34, 4, 1838–1853</p>
Dataset for 'Unveiling the charge distribution of a GaAs-based nanoelectronic device'
<p>*********************************************************<br> This repository contains the raw experimental data associated with the manuscript<br> "Unveiling the charge distribution of a GaAs-based nanoelectronic device: A large experimental data-set approach"<br> by Eleni Chatzikyriakou, Junliang Wang et al.<br> See Arxiv:2205.00846 for more details. <br> *********************************************************</p> <p>***************************************<br> Content of the different data files<br> ***************************************</p> <p>The data are stored in 5 different files in the csv format.</p> <p>* data_1D_4K.csv: current versus gate voltage data for all the samples at 4K. <br> The same gate voltage is applied on the Top and bottom gates.</p> <p>For sample X1Y3, X2Y3, X5Y3 and X6Y3 some additional measurements have been realised :</p> <p>* data_1D_mk.csv : top and bottom gates of each QPC have been swept at the same time at 50 mK temperature.</p> <p>* data_2D_4K_TB.csv : top gate has been swept for different values of the bottom gate at 4K.<br> * data_2D_mK_TB.csv : top gate has been swept for different values of the bottom gate at 50 mK temperature.<br> * data_2D_mK_BT.csv : bottom gate has been swept for different values of the top gate at 50 mK temperature.</p> <p>***********************************<br> Format of the csv files<br> ***********************************</p> <p>--- All the data files are in the following format. </p> <p>* A given curve "current versus gate voltage" is stored in two consecutive raws. The first one contains the value of the measured current, the second one contains the values of the applied<br> gate voltages.</p> <p>* A 2D measurement "current versus top gate and bottom gate" is stored in three consecutive raws. The first one contains the value of the measured current, the second one contains the list of values of voltage applied on one of the gate. The third third raw contains the list of values of voltage applied on the other gate.</p> <p>--- Each row of a csv file has the following format: </p> <p>* The first column identifies the quantum point contact and the quantity. The format is Xx_Yy_QpcNb_Meas.<br> - Xx is the column on the chip (from X1 to X6).<br> - Yy is the row on the chip (Y1, Y2 or Y3).<br> - QpcNb is the number of the qpc (from 1 to 8 or from 9 to 16).<br> - Meas is the reported quantity, either the (measured) "current" or the (applied) "voltage"<br> or the "TopVoltage" or "BotVoltage" for 2D scans.</p> <p>* The second column is the unit (A or V).</p> <p>* The third column is the number of sweeps (1, 2 or 3) performed. <br> For some measurements, the same sweep has been done multiple times.</p> <p>* The fourth column is the design of the quantum point contact (A, B, C, D or E).</p> <p>* All the following columns contain the measured value. For 2D scans the different values of the gate corresponding to the third raw are placed one after the other.</p> <p>*******************************<br> Python scripts for data analysis<br> *******************************</p> <p>For convenience, we provide an example python scripts that can be used to load the data and plot them.</p> <p>extract.py : Extracts the data into a dictionary and plots the I-V characteristics<br> extract.ipynb : jupyter notebook using the different functions of extract.py</p> <p>type -h for help</p>
Data for "Spin-charge separation in a 1D Fermi gas with tunable interactions"
<p>This dataset is corresponding to the article "Spin-charge separation in a 1D Fermi gas with tunable interactions"</p>
Data and Code For: Closing the Loop Between Microstructure and Charge Transport in Conjugated Polymers by Combining Microscopy and Simulation.
<p>This repository contains the datasets and scripts used in the article "Closing the Loop Between Microstructure and Charge Transport in Conjugated Polymers by Combining Microscopy and Simulation." </p> <p>Contents:</p> <p>4D-STEM data of the polymer PBTTT, annealed at 180C for 2h, vapor doped with the molecule F4TCNQ</p> <ul> <li>3_80x80_ss=10nm_spot9_alpha=p48_cl=480_RT_300kV_33ms_bin=4.zip ("Scan 3", Main case study)</li> <li>05 CL480 alpha p48 300kV spot11 50ms 80x80 s10.zip</li> </ul> <p>4D-STEM data of the polymer PBTTT, annealed at 180C for 2h, undoped</p> <ul> <li>10 A1 CL480 alpha p48 300kV spot11 50ms 80x80 s10.zip</li> <li>15 A1 CL480 alpha p48 300kV spot11 50ms 80x80 s10.zip</li> </ul> <p>Preprocessed data from "Scan 3." Images are centered, artifacts are removed, and images are binned and converted to radial coordinates.</p> <ul> <li>4D-STEM Preprocessed.zip <ul> <li>sample_preprocessed_data_80x80_ss=10_cl=480__q 1.00 3.00 0.05 a 5.00.npy (medium resolution, wide range, used in paper)</li> <li>sample_data_cube_q_1.0_2.0_0.1_angle_5.npy (low resolution, narrow range)</li> </ul> </li> </ul> <p>Grazing-Incidence Wide-Angle X-ray scattering (GIWAXs) scan of annealed PBTTT, supporting our interpretation of the 4D-STEM data.</p> <ul> <li>3 raw images</li> <li>Calibration files</li> <li>Combined processed image</li> </ul> <p>Spatially resolved diffraction intensity mapped onto a spherical harmonic basis set, for use as an input to structural simulations. One for each of the four 4D-STEM datasets.</p> <ul> <li>spherical_harmonics.zip</li> </ul> <p>Simulated structures of polymer chains based on the processed 4D-STEM data, created using code at https://github.com/SpakowitzLab/wlcsim. Each simulation produced 15 structures using different levels of chain alignment.</p> <ul> <li>chain_geometries.zip <ul> <li>main_dataset_03 (main case study)</li> <li>hi_align_03 (3.3x higher alignment factors than main dataset)</li> <li>undoped_10</li> <li>undoped_15</li> </ul> </li> </ul> <p>Simulations of charge transport through the structures</p> <ul> <li>transport_simulations.zip <ul> <li>ct_16_n100 (explores structural modifications and their effects on mobility)</li> <li>ct_18_n1000 (explores transport in all 4 directions and is used for making GIFs of simulations)</li> <li>ct_20_n1000 (explores the effect of degree of chain alignment)</li> <li>ct_28_n1000 (explores the effect of electric field strength)</li> <li>ct_29_n100 (tracks distances of individual on-chain moves)</li> <li>ct_30_n10000 (uses a high sample size and varied start positions to sample both short-time and long-time mobility)</li> </ul> </li> </ul> <p>Code for 4D-STEM analysis and simulations of charge transport. (Code for structural simulations can be found at https://github.com/SpakowitzLab/wlcsim).</p> <ul> <li>code.zip <ul> <li>preprocess_4dstem.py: package for preprocessing 4D-STEM files</li> <li>flow_fields.py: package for visualizing 4D-STEM data using director maps</li> <li>autocorrelation.py: package for measuring correlation lengths in 4D-STEM data via multiple methods</li> <li>spherical_harmonics.py: package for mapping diffraction intensity onto a spherical harmonic basis set. The results can be used as an input for structural simulations. </li> <li>charge_transfer_assets.py: package for performing charge transfer simulation on simulated chain coordinates</li> </ul> </li> <li>examples.zip <ul> <li>preprocess_demo: sample usage for preprocess_4dstem.py</li> <li>visualization_demo: sample usage for flow_fields.py, autocorrelation.py, and spherical_harmonics.py</li> <li>charge_tranpsort_demo: sample usage for charge_transfer_assets.py</li> <li>paper_figures: shows the code for producing several figures from the paper, using the included simulation datasets. </li> </ul> </li> </ul>
Data release for the paper "Measurements of protons and charged pions emitted from the $\nu_{\mu}$ charged-current interactions on iron at a mean neutrino energy of 1.49 GeV using a nuclear emulsion detector"
<p>This data release is associated with the paper "Measurements of protons and charged pions emitted from the <span class="math-tex">\(\nu_{\mu}\)</span> charged-current interactions on iron at a mean neutrino energy of 1.49 GeV using a nuclear emulsion detector". It is currently available on <a href="http://arxiv.org/abs/2203.08367">arXiv:2203.08367</a> and to be submitted to Phys. Rev. D.</p> <p><strong>When citing this data release, please cite as well the paper.</strong></p> <p>The provided zip file contains the data as below.</p> <ol> <li>event.root: Event by event information of 183 iron-target interactions.</li> <li>plot.root: Plot information as shown in the paper.</li> <li>detector_efficiency.root: Detectrion efficiencies for muons, charged pions, and protons.</li> <li>momentum_resolution.root: Relation between true and reconstructed momentum for muons, charged pions, and protons.</li> <li>misPID.root: Mis-PID rates of protons and pions.</li> <li>syscov.root: Covariance matrices of systematic uncertainties.</li> <li>flux.root: The neutrino flux and the covariance matrix of the flux error.</li> </ol> <p>The zip file also contains a README.pdf file with detailed information on the included files. Please read it.</p>
Dataset of "Modelling the Frequency-Dependent Effective Excess Charge Density in Partially Saturated Porous Media"
<p>This dataset supports the research study 'Modelling the Frequency-Dependent Effective Excess Charge Density in Partially Saturated Porous Media' by S. G. Solazzi, L. D Thanh, K. Hu, and D. Jougnot.</p> <p>We provide with a commented MATLAB code (Freq_Sat_SP.m) for estimating the frequency-dependent (i) effective excess charge density, (ii) the electrokinetic coupling coefficient, and (iii) the effective dynamic permeability for partially saturated porous media. The code allows to consider fractal, lognormal, and double lognormal pore size distributions.</p>
Tests showing the projectile flight trajectory of 5, 7 and 8mm diameter steel spheres attached to either a detonator or a rear detonated C4 spherical explosive charge.
<p>These videos are the results of an experimental campaign carried out in the department of Propellant, Explosives and Blast Engineering of the Royal Military Academy in Brussels to study the flight trajectory of a projectile (steel sphere (5 or 7 or 8mm diameter)) attached to either a detonator or a rear detonated C4 spherical explosive charge. The projectile is accelerated by the blast wave generated by the explosive. The projectile initial trajectory is hidden by the flash of the detonation. After its passage through the opaque gas cloud, the first appearance of the projectile is captured and an almost straight trajectory can be tracked until the end of the field of view of the high speed camera. The test campaign reveals the capability of the projectiles to maintain an oriented path until impact on a target placed at 910mm stand of distance from the center of the explosion. </p>
Energy differences between multielectron atoms (H to Ne) with non-integer nuclear charges using SCF methods and AIT
<p>Energy difference predictions for multi-electron atoms: for the basis set def2-TZVP and the basis functions of the reference atom xenon, self-consistent field (SCF) energy differences between an atom's initial charge and an atom of final charge have been calculated using the unrestricted Hartree-Fock method of <a href="https://pyscf.org/">PySCF</a>. Each energy difference is complemented by the prediction of the same difference using the <a href="https://arxiv.org/abs/2203.13794">Alchemical Integral Transform</a> (AIT), given in separate perturbative orders 1,2,3,4,5.</p>
EXAMPLE: Lattice-based equation of state tables with three conserved charges (BSQ)
<p>These table is intended to provide an example format of the equation of state expected for the CCAKE hydrodynamic code which propagates conserved charge densities for baryon number <span class="math-tex">\(B\)</span>, net strangeness <span class="math-tex">\(S\)</span>, and electric charge <span class="math-tex">\(Q\)</span>. They are included primarily for demonstration purposes and no claim is made as to the accuracy of their contents.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.