Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
414
datasets available to search
ShareScore release 0.9.0
Dataset results
414 results for “Lithium”
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>
Supporting data for "Understanding the impact of precipitation kinetics on the electrochemical performance of lithium–sulfur batteries by operando X-ray diffraction"
<p>This is the dataset of electrochemical and operando X-ray diffraction measurements for our publication "Understanding the impact of precipitation kinetics on the electrochemical performance of lithium–sulfur batteries by operando X-ray diffraction". This archive contains the raw data and scripts written in R used in the analysis and presentation of the results in this manuscript.</p> <p>Abstract of the manuscript:</p> <p>The complex reaction mechanism of the lithium–sulfur battery system consists of repetitive dissolution and precipitation of the sulfur-containing species in the positive electrode. In particular, the precipitation of lithium sulfide (Li<sub>2</sub>S) during discharge has been considered a crucial factor for obtaining a high degree of active material utilization. Here, the influence of electrolyte amount, electrode thickness, applied current and electrolyte salt on the formation of Li<sub>2</sub>S is systematically investigated in a series of operando X-ray diffraction experiments. Through a combination of simultaneous diffraction and resistance measurements, the evolution of Li<sub>2</sub>S is directly correlated to the variation in internal resistance and transport properties inside the positive electrode. The correlation indicates that at different stages, the Li<sub>2</sub>S precipitation both facilitates and impedes the discharge process. This information on the kinetics of Li<sub>2</sub>S formation offers mechanistic explanations for the strong impact of different electrochemical cell parameters on the cell performance and thus, directions for holistic optimizations to achieve high sulfur utilization.</p> <p> </p>
Supporting data for "Towards reliable three-electrode cells for lithium–sulfur batteries"
<p>This is the dataset of electrochemical measurements for our publication "Towards reliable three-electrode cells for lithium–sulfur batteries". This archive contains the raw data and scripts written in R used in the analysis and presentation of the results in this manuscript.</p> <p>Abstract of the manuscript:</p> <p>Three-electrode measurements are valuable to the understanding of the electrochemical processes in a battery system. However, their application in lithium–sulfur chemistry is difficult due to the complexity of the system and thus rarely reported. Here, we present a simple three-electrode cell format with relatively good life time and minimum interference with the cell operation. </p>
Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation
<p>Here are the datasets for the publication named "Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation" published in Nature Communications. Experimental cycling data for three commercial 18650 type batteries (Dataset_1:NCA battery, Dataset_2:NCM battery, and Dataset_3:NCM+NCA_battery) are given, where each csv file corresponds to one cell cycling data. The cells are named as CY<em>X-Y_Z</em>-#<em>N</em> according to their cycling conditions. <em>X</em> means the temperature, <em>Y_Z</em> represents the charge_discharge current rate, #<em>N</em> is the cell tag. Each csv file has 9 columns, including cycle time ('time/s'), controlled voltage and current ('control/V/mA'), battery voltage ('Ecell/V'), applied current ('<I>/mA'), charge or discharge electricity ('Q discharge/mA.h' and 'Q discharge/mA.h'), controlled voltage or current ('control/V', 'control/mA' and ), and cycle number ('cycle number'). In the impedance data, one representative cell from each cycling condition is chosen for the discussion in the main text. More detailed descriptions can be found in the zip file.</p>
Research data: "Effects of Network Structures on the Production Planning in Closed-loop Supply Chains – A Case Study based Analysis for Lithium-ion Batteries in Europe"
<p>This data set belongs to the paper Effects of Network Structures on the Production Planning in Closed-loop Supply Chains – A Case Study based Analysis for Lithium-ion Batteries in Europe in the International Journal of Production Economics (DOI). The BatPac model, as well as, the model for the economic assessment of the recycling route are not included. The needed data can be found in the file (name). Further, the BatPaC model can be gather from the website of Argonne National Laboratory and the assessment tool for the recycling routes via this DOI: 10.5281/zenodo.6500946.</p> <p> </p> <p>This work is part of the research project Recycling 4.0 (EFRE | ZW 6-85018080), which is funded by the European Regional Development Fund and managed by the development bank for the German federal state of Lower Saxony (NBank).</p>
Experimental Calendar Ageing Data for Lithium-Ion Battery Chemistries
<p>This data set has been generated by Technische Hochschule Ingolstadt (THI). If there are any questions,<br> please do not hesitate to get in touch with the authors.</p>
Supporting Information for "Wave heating during the helium flash and lithium-enhanced clump stars"
<p>"data" contains the data used to generate the plots in this paper.</p> <p>"batches" contains a log of nearly every MESA run performed in this work (including ~all failed experiments). These are stored as Python3 Pickle files. Experiments were run using the RemoteExperiments software package (https://github.com/adamjermyn/remote_experiments). See the documentation there for further information on the data format for these files.</p> <p>"Stokes_Experiments" contains a git repository which includes both the final version of the code used in our canonical run as well as the full history of (nearly) all experiments we performed along the way. Each experiment is a commit (detached from any branch) with the commit message "patch".</p> <p>"Scripts" contains both the scripts we used to run these experiments and those we used to analyze them and make the plots in the paper.</p> <p>Further detail is given in the paper itself.</p>
Photoresponsive Nanocarriers Based on Lithium Niobate Nanoparticles for Harmonic Imaging and On-Demand Release of Anticancer Chemotherapeutics
<p>Data set associated with the following publication:</p> <p>Gheata, A., Gaulier, G., Campargue, G., Vuilleumier, J., Kaiser, S., Gautschi, I., Riporto, F., Beauquis, S., Staedler, D., Diviani, D., Bonacina, L., Gerber-Lemaire, S. Photoresponsive Nanocarriers Based on Lithium Niobate Nanoparticles for Harmonic Imaging and On-Demand Release of Anticancer Chemotherapeutics. <em>ACS Nanoscience Au</em> <strong>2022</strong>, <em>2</em>, 355-366.</p> <p>Raw data for characterization of molecules and nanoparticles: NMR, TEM, DLS.</p> <p>Raw data for cell assays, cell imaging, cytotoxicity experiments and EGFR quantification.</p> <p>Metadata file.</p> <p>Copy of labbooks.</p>
Dataset related to the publication "New Technique for Probing the Protecting Character of the Solid Electrolyte Interphase as a Critical but Elusive Property for Pursuing Long Cycle Life Lithium-Ion Batteries"
<p>The formation of a protecting nano-layer, so-called Solid Electrolyte Interphase (SEI), on the negative electrode of Li-ion batteries (LIBs) from product precipitation of the cathodic decomposition of the electrolyte is a blessing since the electrically-insulating nature of this nano-layer protect the electrode surface preventing continuous electrolyte decomposition and enabling the large nominal cell voltage of LIBs, e.g. 3.3 – 3.8 V. Thus, the protecting performance of the nano-layer SEI is essential for LIBs to achieve long cycle life. Unfortunately, evaluation of this critical property of the SEI is not trivial. Herein, a new, cheap and easily-implementable methodology is presented to estimate the protecting quality of the SEI; the redox-mediated enhanced coulometry. The key element of the methodology is the addition of a redox-mediator in the electrolyte during degassing step (after the SEI formation cycle). The redox-mediator leads to an internal self-discharge process that is inversely proportional to the protecting character of the SEI. And the self-discharge process results in an easily-measurable decrease in coulombic efficiency. The influence of vinylene carbonate as electrolyte additive in the resulting SEI is used as case study to showcase the potential of the proposed methodology</p>
Dynamic viscosity of liquid lithium at different temperatures
<p><strong>Dynamic viscosity of liquid lithium at different temperatures</strong></p> <p>Junjie Chen</p> <p>Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com</p> <p> </p> <p>The viscosity of a fluid is a measure of its resistance to deformation at a given rate. For liquids, it corresponds to the informal concept of "thickness": for example, syrup has a higher viscosity than water. Viscosity quantifies the internal frictional force between adjacent layers of fluid that are in relative motion. For instance, when a viscous fluid is forced through a tube, it flows more quickly near the tube's axis than near its walls. In general, viscosity depends on a fluid's state, such as its temperature, pressure, and rate of deformation. However, the dependence on some of these properties is negligible in certain cases. For example, the viscosity of a Newtonian fluid does not vary significantly with the rate of deformation. The dynamic viscosity of the fluid, often simply referred to as the viscosity.</p> <p>Temperature (degrees Celsius), Dynamic viscosity (grams per meter per second)</p> <p>200 0.566</p> <p>250 0.503</p> <p>300 0.453</p> <p>350 0.412</p> <p>400 0.379</p> <p>450 0.352</p> <p>500 0.328</p> <p>550 0.308</p> <p>600 0.29</p> <p>650 0.275</p> <p>700 0.261</p> <p>750 0.249</p> <p>800 0.238</p> <p>850 0.228</p> <p>900 0.219</p> <p>950 0.211</p> <p>1000 0.204</p> <p>1050 0.197</p> <p>1100 0.191</p> <p>1150 0.185</p> <p>1200 0.18</p> <p>1250 0.175</p> <p>1300 0.17</p> <p>1350 0.166</p> <p>1400 0.162</p> <p>1450 0.158</p> <p>1500 0.155</p> <p>1550 0.151</p> <p>1600 0.148</p> <p>1650 0.145</p> <p>1700 0.142</p> <p>1750 0.139</p> <p>1800 0.137</p> <p>1850 0.135</p> <p>1900 0.132</p> <p>1950 0.13</p> <p>2000 0.128</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com, Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p>
3D micro/nano-CT datasets of sandstone rock, lithium-ion battery, and fuel cell used for testing P3T-Net
<p>These are the datasets used for training and testing P3T-Net for 3D unpaired domain transfer in .tif format. Images can be directly opened with ImageJ, Avizo, Python, Matlab, etc.</p> <p>Dataset contains overall 8 3D images of 4 cases. Each case contains images from the target domain and source domain. </p> <p>Case 1. Target domain: micro-CT image of a 9-hour long scan of a sandstone (voxel size: 2.15um); Source domain: micro-CT image of a 7-minute fast scan of a sandstone (voxel size: 2.15um).</p> <p>Case 2. Target domain: micro-CT image of a 7-hour long scan of a sandstone (voxel size: 3.28um); Source domain: synchrotron micro-CT image of a 24-second fast scan of a sandstone (voxel size: 6.75um).</p> <p>Case 3. Target domain: nano-CT image of a dual-mode scan of Lithium-ion battery cathode (voxel size: 128nm); Source domain: three nano-CT images of a single-mode scan of lithium-ion battery cathode (two absorption and one phase mode) (voxel size: 128nm).</p> <p>Case 4. Target domain: micro-CT image of a 3-hour long scan of a fuel cell (voxel size: 2.25um); Source domain: micro-CT image of a 10-minute fast scan of a fuel cell (voxel size: 2.25um).</p> <p>For any further questions or requirements, please contact kunning.tang@unsw.edu.au.</p>
Dataset for publication: "Influence of Ag co-activation on the Dy3+ luminescence in lithium tetraborate glasses"
<p>Dataset for the article: I.I. Kindrat, B.V. Padlyak, A. Drzewiecki, V.T. Adamiv, I.M. Teslyuk, R. Lisiecki, Influence of Ag co-activation on the Dy<sup>3+</sup> luminescence in lithium tetraborate glasses, Mater. Res. Bull. 179 (2024) 112979, <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.materresbull.2024.112979" target="_blank" rel="noopener">https://doi.org/10.1016/j.materresbull.2024.112979</a></p>
Supporting data for "Cellulose separators with integrated carbon nanotube interlayers for lithium-sulfur batteries: an investigation into the complex interplay between cell components"
<p>This is the dataset of electrochemical experiments for our publication "Cellulose separators with integrated carbon nanotube interlayers for lithium-sulfur batteries: an investigation into the complex interplay between cell components". This archive contains the raw data and scripts written in R used in the analysis and presentation of the results in this manuscript.</p> <p><strong>Abstract for the manuscript:</strong></p> <p>This work aims to address two major roadblocks in the development of lithium-sulfur (Li-S) batteries: the inefficient deposition of Li on the metallic Li electrode and the parasitic “polysulfide redox shuttle”. These roadblocks are here approached, respectively, by the combination of a cellulose separator with a cathode-facing conductive porous carbon interlayer, based on their previously reported individual benefits. The cellulose separator increases cycle life by 33%, and the interlayer by a further 25%, in test cells with positive electrodes with practically relevant specifications and a relatively low electrolyte/sulfur (E/S) ratio. Despite the prolonged cycle life, the combination of the interlayer and cellulose separator <em>increases</em> the polysulfide shuttle current, leading to reduced Coulombic efficiency. Based on XPS analyses, the latter is ascribed to a change in the composition of the solid electrolyte interphase (SEI) on Li. Meanwhile, electrolyte decomposition is found to be slower in cells with cellulose-based separators, which explains their longer cycle life. These counterintuitive observations demonstrate the complicated interactions between the cell components in the Li-S system and how strategies aiming to mitigate one unwanted process may exacerbate another. This study demonstrates the value of a holistic approach to the development of Li-S chemistry.</p> <p>Manuscript preprint <a href="http://dx.doi.org/10.26434/chemrxiv.8835728">available at ChemRxiv</a> (pending approval as of 9/7/19).</p>
Metadata - Tetrathiafulvalene-based covalent organic framework as high-voltage organic cathodes for lithium batteries
Open the record for dataset details and reuse information.
Research Data for "In-vacuo scratching yields undisturbed insight into the bulk of lithium-ion battery positive electrode materials"
<p>This are the datasets supporting the figures and tables in the manuscript and supporting information of the publication "In-vacuo scratching yields undisturbed insight into the bulk of lithium-ion battery positive electrode materials".</p> <p>Available in ACS Energy Letters under <span><a href="https://doi.org/10.1021/acsenergylett.4c02106"><span>https://doi.org/10.1021/acsenergylett.4c02106</span></a></span></p>
Dataset for publication: "Structural and spectroscopic studies of lithium tetraborate glass co-doped with Sm and Cu"
<p>Dataset for the article: B.V. Padlyak, I.I. Kindrat, V.T. Adamiv, A. Drzewiecki, B. Cieniek, I. Stefaniuk, Structural and spectroscopic studies of lithium tetraborate glass co-doped with Sm and Cu, Phys. Chem. Chem. Phys. 26 (2024) 22006–22022, https://doi.org/10.1039/d4cp01633e.</p>
Lithium Ion Battery Test Dataset for Maritime Transport INR18650-MJ1
<p>INR18650-MJ1 test data obtained from cycling under conditions relevant for maritime transport applications.</p>
Dataset of "Thermal Stability of Valuable Metals in Lithium-Ion Battery Cathode Materials: Temperature Range 500-800 °C"
<p>Examination of the cathode part of a lithium-ion battery, which is composed of NMC spinel 622 (LiNi0.6Mn0.2Co0.2O2), and investigation of its stability during annealing at temperatures ranging from 500-800 °C. Determination of valuable metals (Li, Ni, Mn and Co) after exposure to temperatures from 500 to 800 °C using ICP-OES analysis. The correlation between element stability and the temperature of PVDF release, a binder in cathodes, was demonstrated by DTA. SEM-EDS performed local chemical analysis. XRD characterised the crystalline structures of the original material and changes after annealing at 800 °C. This work builds on Part I, which focusses on the thermal stability of the material in lower temperature ranges. This research aimed to gain a deeper understanding of the pyrometallurgical aspect of the recycling process and identify the ideal annealing temperature for maximising the recovery of valuable metals. </p>
Large-area periodically-poled lithium niobate wafer stacks optimized for high-energy narrowband terahertz generation - Dataset
<p>Dataset for the publication "Large-area periodically-poled lithium niobate wafer stacks optimized for high-energy narrowband terahertz generation".</p>
Online Repository for "Sorting lithium-ion battery electrode materials using dielectrophoresis"
<p>Please see the readme file.</p> <p>The matlab script for evaluating the measurements is called “Eval_Fluoro.m” and can be found in this repository.</p> <p>The excel sheet “20221028_photometric_iron.xlsx” contaiins the data from the chemical analysis.</p> <p>The manufacturing data for the electrodes is provided in the zip folder: PCB_boards_Giesler.zip and can be uploaded to a manufacturer of choice.</p>
ScienceDex guides
Understand access before you commit
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.