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1,491 results for “Ione”
A nanoparticle stored with an atomic ion in a linear Paul trap
<p>Radiofrequency traps are used to confine charged particles but are only stable for a narrow range of charge-to-mass ratios. Here, we confine two particles---a nanoparticle and an atomic ion---in the same radiofrequency trap although their charge-to-mass ratios differ by six orders of magnitude. The confinement is enabled by a dual-frequency voltage applied to the trap electrodes. We introduce a robust loading procedure under ultra-high vacuum and characterize the stability of both particles. It is observed that slow-field micromotion, an effect specific to the dual-field setting, plays a crucial role for ion localization and will be important to account for when engineering controlled interactions between the particles.</p>
NiFe-NO3 layered double hydroxide as a novel anode for sodium ion batteries
<p>raw data of the scheme present in the paper entitled: <span>NiFe-NO<sub>3</sub> layered double hydroxide as a novel anode for sodium ion batteries</span></p>
Dataset for publication Reaction Mechanism and Performance of Innovative 2D Germanane-Silicane Alloys SixGe1−xH Electrodes in Lithium-Ion Batteries
<p>A dataset for publication Datase for publication Reaction Mechanism and Performance of Innovative 2D Germanane-Silicane Alloys SixGe1−xH Electrodes in Lithium-Ion Batteries including all relevant data used in the manuscript. Information on how to use the dataset are included in the readme file.</p>
Project - Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis
<p>Here are the datasets for our publication entitled "<a href="https://www.nature.com/articles/s41467-024-48779-z">Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis</a>" published in Nature Communications. </p> <p>The object of this experiment is the 18650 nickel-cobalt-manganese (NCM) lithium-ion battery manufactured by "LISHEN". The chemical composition is LiNi<sub>0.5</sub>Co<sub>0.2</sub>Mn<sub>0.3</sub>O<sub>2</sub>. The nominal capacity of the battery is 2000 mAh, and the nominal voltage is 3.6 V. The charging cut-off voltage and discharging cut-off voltage are 4.2 V and 2.5 V, respectively. The whole experiment was conducted at room temperature. A total of 55 batteries were included in this experiment, conducted under 6 different charging and discharging strategies. The charging and discharging platform is ACTS-5V10A-GGS-D, and the sampling frequency for all data is 1Hz.</p> <p>Other details can be found in "Data Introduction.pdf" file.</p> <p>The <strong>Python Code</strong> for reading and preprocessing this dataset is available at: <a href="https://github.com/wang-fujin/Battery-dataset-preprocessing-code-library">https://github.com/wang-fujin/Battery-dataset-preprocessing-code-library</a></p> <p>Summary of articles using the this dataset: <a href="https://github.com/wang-fujin/XJTU-Battery-Dataset-Papers-Summary">https://github.com/wang-fujin/XJTU-Battery-Dataset-Papers-Summary</a></p> <p> </p> <p>If you find this data helpful, please consider citing our paper:</p> <p>Wang, F., Zhai, Z., Zhao, Z. <em>et al.</em> Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis. <em>Nat Commun</em> <strong>15</strong>, 4332 (2024). https://doi.org/10.1038/s41467-024-48779-z</p>
Characterizing Macroporous Ion Exchange Membrane Adsorbers for Natural Organic Matter (NOM) removal — Adsorption and Regeneration behavior
Open the record for dataset details and reuse information.
Determination of the Chloride Ion Deposition by the Bresle Method
<p> In corrosion science, accurate determination of chloride ion deposition rates is critical to mitigating the environmental impact on structures. Traditional methods, such as the wet candle and dry plate methods (ISO 9225), are often inaccurate in capturing localized conditions and are also time consuming and costly. The Bresle method, which measures soluble salts directly on metal surfaces, offers a more targeted approach. This article examines the Bresle method as an alternative for determining average monthly chloride ion deposition rates, including a regression analysis comparing the Bresle method with the wet candle method, and examines the long-term salinity of exposed surfaces in comparison with the additive approach to surface salinity. The paper hypothesizes that the Bresle method can be used as an alternative to the wet candle method. Linear regression analysis shows a strong correlation in chloride ion deposition rates compared to those measured by the wet candle method. However, cumulative measurements using long-term exposed coupons are unreliable due to inconsistent trends.</p>
Square Antiprismatic Ion Chelation Is a Key Determinant for Potassium Channel Selectivity
<p>Files presented here are archives K_DB.tar.gz, MEMB_DB.tar.gz and PDB70.tar.gz.</p> <p>Archives KDB.tar.gz, MEMB_DB.tar.gz and PDB70.tar.gz contain models of indentified sites for potassium channels (dataset #1), other membrane proteins, excluding potassium channels (dataset #2) and non-membrane proteins form PDB70 (dataset #3). The name of a folder in the dataset corresponds to PDB ID of a protein for which calculation were made. Each folder contain the following files:</p> <ul> <li><PDB_ID>.pdb — the original pdb file.</li> <li><PDB_ID>.ref — file that contains oxygens and nitrogens from original pdb that were used for scanning.</li> <li><PDB_ID>_COMBS.txt — combinations of atoms that were used for calculations.</li> <li><PDB_ID>_alignment_X.pdb — original template that was aligned to the protein atoms. X denotes a number of the alignment.</li> <li><PDB_ID>_site_X.pdb — this pdb file contains eight atoms that form the site for K+ and which were used for the corresponding alignment X.</li> <li><PDB_ID>_RES.txt — the combinations of protein atoms that form the site are written in square brackets. The RMSD value for the alignment to this site is written to the right of them.</li> <li><PDB_ID>_RMSD.log — this file contains RMSD values of the template alignment to the corresponding site.</li> </ul>
Square Antiprismatic Chelation Is a Key Determinant for Potassium Ion Selectivity
<p><strong>DATASETS</strong></p> <p>Archives <em>K_DB.tar.gz</em>, <em>MEMB_DB.tar.gz</em> and <em>PDB70.tar.gz</em> contain models of indentified sites for potassium channels (dataset #1), other membrane proteins, excluding potassium channels (dataset #2) and non-membrane proteins form PDB70 (dataset #3). The name of a folder in the dataset corresponds to PDB ID of a protein for which calculation were made. Each folder contain the following files:</p> <ul> <li><PDB_ID>.pdb — the original pdb file.</li> <li><PDB_ID>.ref — file that contains oxygens and nitrogens from original pdb that were used for scanning.</li> <li><PDB_ID>_COMBS.txt — combinations of atoms that were used for calculations.</li> <li><PDB_ID>_alignment_X.pdb — original template that was aligned to the protein atoms. X denotes a number of the alignment.</li> <li><PDB_ID>_site_X.pdb — this pdb file contains eight atoms that form the site for K+ and which were used for the corresponding alignment X.</li> <li><PDB_ID>_RES.txt — the combinations of protein atoms that form the site are written in square brackets. The RMSD value for the alignment to this site is written to the right of them.</li> <li><PDB_ID>_RMSD.log — this file contains RMSD values of the template alignment to the corresponding site.</li> </ul> <p><strong>SUPPLEMENTARY TABLES S1-S5</strong></p> <p>The file <em>Supporting Information_Tables S1-S5.xlsx </em>contain tables S1-S5 for the supporting information from the original paper. These tables describe potassium binding sites indentifieid in potassium channels, other membrane proteins and randomly chosen non-membrane proteins. (See the article text for details)</p> <p> </p> <p> </p>
Data from the paper "Porphyrin central metal ion driven self-assembling in heterogeneous ZnTPP – CoTPP films grown on Fe(001)-p(1 × 1)O"
Open the record for dataset details and reuse information.
Ab initio data to generates machine-learned force fields of ions in aqueous medium in VASP format.
<p>ML_AB_H: Datasets of 64 water molecules and a single proton with 64 water molecules.</p> <p>ML_AB_VP2: Datasets of a single V^2+ ion with 64 water molecules.</p> <p>ML_AB_VP3: Datasets of a single V^3+ ion with 64 water molecules.</p> <p>ML_AB_FeP2: Datasets of a single Fe^2+ ion with 64 water molecules.</p> <p>ML_AB_FeP3: Datasets of a single Fe^3+ ion with 64 water molecules.</p> <p>ML_AB_CuP1: Datasets of a single Cu^+ ion with 64 water molecules.</p> <p>ML_AB_CuP2: Datasets of a single Cu^2+ ion with 64 water molecules.</p> <p>ML_AB_RuP2: Datasets of a single Ru^2+ ion with 64 water molecules.</p> <p>ML_AB_RuP3: Datasets of a single Ru^3+ ion with 64 water molecules.</p> <p>ML_AB_AgP1: Datasets of a single Ag^+ ion with 64 water molecules.</p> <p>ML_AB_AgP2: Datasets of a single Ag^2+ ion with 64 water molecules.</p> <p>ML_AB_O2: Datasets of a single O2 ion with 64 water molecules.</p> <p>ML_AB_O2N1: Datasets of a single O2^- ion with 64 water molecules.</p> <p>ML_AB_water: Datasets of 64 water molecules presenting bulk water and 64 water molecules representing water slab.</p> <p>All datasets were generated by VASP using PAW, plane wave basis sets with cutoff energy of 520 eV and RPBE+D3 exchange-correlation functional with zero-damping. All ab initio calculations were done on extended systems with periodic boundary conditions. See details in <a href="https://doi.org/10.48550/arXiv.2409.11000">https://doi.org/10.48550/arXiv.2409.11000</a>.</p>
Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset – version 2: result data]
<p>Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies can help to better understand and model degradation and to optimize the operation strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications.<br>To our knowledge, the dataset presented in the following is one of the largest published to date. It contains data from 228 commercial NMC/C+SiO lithium-ion cells aged for almost 600 days under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to some of the cells.<br>This dataset is an update to the dataset previously published under the DOI 10.35097/1947 and described in the publication with the DOI 10.1038/s41597-024-03831-x. This dataset only includes result data (capacity, impedance, and pulse resistance measurements). The log data is published under the DOI 10.35097/kww7jv8ajuvchcah.</p>
Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset – version 2: log data]
<p>Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies can help to better understand and model degradation and to optimize the operation strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications.<br>To our knowledge, the dataset presented in the following is one of the largest published to date. It contains over 3 billion data points from 228 commercial NMC/C+SiO lithium-ion cells aged for almost 600 days under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to some of the cells.<br>This dataset is an update to the dataset previously published under the DOI 10.35097/1947 and described in the publication with the DOI 10.1038/s41597-024-03831-x. This dataset only includes log data. The result data is published under the DOI 10.35097/1969.</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>
Simulation dataset for New Insights on the High Reconnection Rate and the Diminishment of Ion Outflow
<p>The dataset contains simulation data used in the paper of "New Insights on the High Reconnection Rate and the Diminishment of Ion Outflow". Data are generated from a particle-in-cell simulation using the VPIC code. Please see the paper for the descriptions of the simulation setup.</p> <p>The fields_moments.gda files in runs.7z are fields and plasma moments data of the simulations presented in the paper. The time step in unit of twci for each simulation is: A1:0.025, A2:0.1, A3:0.25, A4:0.25, A5:0.5, B1:0.1, B2:0.1, B3:0.1, B4:0.025, B5:0.05, C1:0.02, C2:0.02. Each file contains float-type data arrays with a size of (Lx/Δ)×1×(Lz/Δ), corresponding to x-y-z dimensions, respectively. Lx, Lz and Δ for each simulation are presented in the paper. Data can be read by softwares like IDL, python, matlab, etc., using the standard data reading methods.</p> <p>The runs_Hparticle_t_x_z files contain ion particle data for the time step t, for the domain of x=[x-0.03, x+0.03]di, z=[z-0.03,z+0.03]di. The files are IDL save files. To read the data, use restore, file=file in IDL. Each data chunk constitues of the following variables in order: all_vxs, all_vys, all_vzs, ws, all_xs, all_ys. Here all_vxs, all_vys and all_vzs are velocities in unit of light speed (c); all_xs and all_ys are x and z locations in unit of de; ws represents the weight of the particles, so the contribution of a particle to the phase space density needs to multiply by this ws factor (In the paper, ws factors are re-normalized while the relative weights between particles remain the same).</p>
Mechanism of Praziquantel action at a parasitic flatworm ion channel
<p>Data supporting Park <em>et al.</em> [Mechanism of praziquantel action at a parasitic flatworm ion channel]</p> <p> </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>
Estimation of sulfuric acid concentrations using ambient ion composition and concentration data obtained by ion mass spectrometry measurements (APi-TOF)
<p>The dataset has been used to estimate the sulfuric acid concentration from APi-TOF data. Using the bisulfate ion, the sulfuric acid molecule clustered with the bisulfate ion (dimer) and the trimer, we were able to determine the daytime concentration of sulfuric acid with the concentration of ambient ions, including the condensation sink, ion-ion recombination and collision rate of HSO4- with H2SO4.</p>
Data for: Optimizing broad ion beam polishing of zircaloy-4 for electron backscatter diffraction analysis
<p>This is the data to support a manuscript that explores how to optimize sample preparation of zircaloy-4 using broad ion beam polishing.</p> <p>If you wish to follow-up on this data, please contact Dr Ben Britton (ben.britton@ubc.ca).</p> <p>The data was collected and curated by Ning Fang and Ruth Birch.</p>
Dataset of Effect of meteoric ions on ionospheric conductance at Jupiter
<p>This dataset contains the input parameters and the simulated results used for figures in the paper "Effects of meteoric ions on ionospheric conductance of Jupiter" by Y. Nakamura, K. Terada, C. Tao, N. Terada, Y. Kasaba, F. Leblanc, H. Kita, A. Nakamizo, A. Yoshikawa, S. Ohtani, F. Tsuchiya, M. Kagitani, T. Sakanoi, G. Murakami, K. Yoshioka, T. Kimura, A. Yamazaki and I. Yoshikawa. Detailed informations about the data files can be found in "README.txt".</p>
CW EPR data supporting : Twenty-three–millisecond electron spin coherence of erbium ions in a natural-abundance crystal
<p>Continuous Wave electron spin resonance. Data corresponding to supporting information. Sample: CaWO4 recorded at 8K</p> <p>Dataset for the reference :</p> <p>Twenty-three–millisecond electron spin coherence of erbium ions in a natural-abundance crystal</p> <p>https://doi.org/10.1126/sciadv.abj9786</p> <p> </p> <p><strong>Marianne Le Dantec</strong><strong>, Miloš Rančić</strong><strong>, Sen Lin</strong><strong>, Eric Billaud</strong><strong>, Vishal Ranjan</strong><strong>,<br> Daniel Flanigan, Sylvain Bertaina</strong><strong>, Thierry Chanelière</strong><strong>, Philippe Goldner</strong><strong>, Andreas Erb</strong><strong>, </strong><br> <strong>Ren Bao Liu , Daniel Estève , Denis Vion , Emmanuel Flurin , Patrice Bertet * </strong></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.