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441 results for “Battery”
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 Detailed Li-ion Battery Characterization Model for Economic Operation
<p>Dataset accompanying the research paper "Detailed Li-ion Battery Characterization Model for Economic Operation"</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>
Code and measurement data - Capacity and internal resistance diagnosis of batteries with voltage-controlled models
<p><strong>This dataset contains the research data (Matlab code, measurement data, figure files) of the journal article: <a href="https://doi.org/10.1149/1945-7111/ad6938">Wolfgang G. Bessler, “Capacity and resistance diagnosis of batteries with voltage-controlled models,” J. Electrochem. Soc. 171, 080510 (2024), https://doi.org/10.1149/1945-7111/ad6938</a>.</strong><br><br></p> <p><strong>Abstract:</strong></p> <p>Capacity and internal resistance are key properties of batteries determining energy content and power capability. We present a novel algorithm for estimating the absolute values of capacity and internal resistance from voltage and current data. The algorithm is based on voltage-controlled models (VCM). Experimentally-measured voltage is used as input variable to an equivalent circuit model. The simulation gives current as output, which is compared to the experimentally-measured current. We show that capacity loss and resistance increase lead to characteristic fingerprints in the current output of the simulation. In order to exploit these fingerprints, a theory is developed for calculating capacity and resistance from the difference between simulated and measured current. The findings are cast into an algorithm for operando diagnosis of batteries operated with arbitrary load profiles. The algorithm is demonstrated using cycling data from lithium-ion pouch cells operated on full cycles, shallow cycles, and dynamic cycles typical for electric vehicles. Capacity and internal resistance of a “fresh” cell was estimated with high accuracy (mean absolute errors of 0.9 % and 1.8 %, respectively). For an “aged” cell, the algorithm required adaptation of the model’s open-circuit voltage curve in order to obtain high accuracies.</p> <p> </p> <p><strong>Copyright and IP information:</strong></p> <p>Copyright 2024 by Wolfgang G. Bessler. The Matlab codes and the research data provided here are under <strong><a href="https://creativecommons.org/licenses/by-nc/4.0/legalcode">CC-BY-NC-4.0</a></strong> license (Creative Commons Attribution Non Commercial 4.0 International). Please note that the algorithms themselves are subject to intellectual property rights, including, but not necessarily limited to, German patent DE102022129314 and international patent WO2024/099513A1. Any use of the codes and algorithms presented here is subject to these property rights.</p> <p><br><strong>Quick start:</strong></p> <p>Copy all files into one folder. Open and run capacityAndResistanceDiagnosisFigures8and10.m with Matlab. Observe the reproduction of Figure 8 of the paper.</p> <p><br><strong>Description of the files:</strong></p> <p>Matlab code (tested using versions R2019a and R2022b):</p> <ul> <li>capacityAndResistanceDiagnosisFigures8and10.m: this is the main Matlab script. It performs the capacity and resistance diagnosis on experimental data V(t) and I(t). The script reproduces Figures 8 ("fresh" cell) or 10 ("aged" cell) of the paper, depending on which lines you uncomment in upper part of the script.</li> <li>calculateDeltaR.m, calculatefC.m: functions that evalue deltaR and fC, which are two key outputs of the diagnosis algorithm. </li> <li>simulateVCMSimple.m, simulateVCMDynamic.m: functions that simulate the voltage-controlled equivalent circuit models (either "simple" of "dynamic"). Input is V(t), output are I(t) and SOC(t).</li> <li>interpolateCurve.m: performs linear interpolation of the OCV(SOC) curve. We use this because Matlab's interp1() function is awfully slow.</li> </ul> <p>Experimental data:</p> <ul> <li>Experimental_data_fresh_cell.csv: Tabulated experimental data (time, current, voltage, temperature) of the long-term experiment (99 h total with 1 s resolution) of a "fresh" lithium-ion cell. The cell is initally completely discharged. The data consist of full cycling, shallow cycling, and WLTP cycling.</li> <li>Experimental_data_aged_cell.csv: Tabulated experimental data (time, current, voltage, temperature) of the long-term experiment (85 h total with 1 s resolution) of a "pre-aged" lithium-ion cell. The cell is initally completely discharged. The data consist of full cycling, shallow cycling, and WLTP cycling.</li> <li>OCV_vs_SOC_curve_fresh_cell.csv: Tabulated experimentally-derived open-circuit voltage (OCV) as function of state of charge (SOC) of the "fresh" lithium-ion cell. 1001 data points between SOC = 0 and SOC = 1 in increments of 0.001.</li> <li>OCV_vs_SOC_curve_aged_cell.csv: Tabulated experimentally-derived open-circuit voltage (OCV) as function of state of charge (SOC) of the "aged" lithium-ion cell. 1001 data points between SOC = 0 and SOC = 1 in increments of 0.001.</li> </ul> <p>Figure files:</p> <ul> <li>Figures.zip: contains .emf (Windows format) and .fig (Matlab format) versions of Figures 2-10 of the paper.</li> </ul>
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>
Supporting Data for "Why Half‐Cell Samples Provide Limited Insight Into the Aging Mechanisms of Potassium Batteries"
<p>This dataset provides the raw data to the manuscript</p> <p><strong>"Why Half‐Cell Samples Provide Limited Insight Into the Aging Mechanisms of Potassium Batteries"</strong></p> <p>published in Advanced Energy Materials, <strong>2024</strong>, DOI 10.1002/aenm.202403811</p> <p><a href="https://doi.org/10.1002/aenm.202403811">Link to Publisher</a></p> <p> </p> <p>Comments:</p> <ul> <li>HAXPES synchrotron data is provided as IGOR file (IGOR Pro (v6.37, WaveMaterics Inc.). The file contains the original 2D data and the converted 1D datasets used for analysis</li> <li>In-House XPS data is provided with corresponding peak fits as excel spreadsheet</li> <li>peak data (binding energy (after referencing), intensity, area, FWHM and at.%) is provided in separate excel spreadsheet.</li> </ul> <p> </p>
Simulation data of Schmidt et al., An Electro-Chemo-Mechanic Model Resolving Delamination between Components in Complex Microstructures of Solid-State Batteries, 2024, DOI: https://doi.org/10.1149/1945-7111/ad76dc
<p>This data set includes the simulation results of the relevant simulations published in the paper: "Schmidt et al., An Electro-Chemo-Mechanic Model Resolving Delamination between Components in Complex Microstructures of Solid-State Batteries, 2024, DOI: https://doi.org/10.1149/1945-7111/ad76dc".</p> <p>Please refer to the paper for the details of the model as well as the parameterization of the model for the respective simulations.</p> <p>The data is provided in a zip archive. After extracting you find a short README.txt with further hints on the structure and available data.</p>
Analysis of Determining the Location of Public Electric Battery Exchange Stations (SPBKLU) using The Buffer Method in The Geographical Information System (GIS) in The Central Jakarta Region (Case Study of PT. XYZ)
<p>Figure 1. The Existing Station Map in the Central Jakarta Area</p> <p><strong><span>Figure 2.</span></strong><span> The Suitability of Battery Replacement Station Location and Closeness to Alfamart Supermarket </span></p> <p><strong><span>Figure 3.</span></strong><span> The Suitability of Battery Replacement Station Location and Closeness to District Office </span></p> <p><strong><span>Figure 4.</span></strong><span> The Suitability of Battery Replacement Station Location in the Central Jakarta Area</span></p> <p><span>Data (The Variable Weight & The Variable Criteria)</span></p>
Battery sizing capacity, Carbon emission and NPV data
<p>The dataset contains: The simulation environment and results of the building energy model, including meteorological data, battery capacity sizing data, and battery degradation data. The data set also includes calculations and results based on the net present value and carbon intensity of the systems described above.</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>
Data for the publication: Advancing Reversible Magnesium−Sulfur Batteries with a Self-Standing Gel Polymer Electrolyte
<p>This is a collection featuring the data generated and used within the paper: "Advancing Reversible Magnesium−Sulfur Batteries with a Self-Standing Gel Polymer Electrolyte"</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>
DEVELOPMENT OF AN INNOVATIVE PROCESS INVOLVING THE USE IONIC LIQUIDS FOR THE RECOVERY AND PURIFICATION OF RARE EARTH FROM PERMANENT MAGNETS AND NiMH BATTERIES
<p>Experimental data</p>
Cycling Rate-Induced Spatially-Resolved Heterogeneities in Commercial Cylindrical Li-Ion Batteries: Datasets
<p>Sinogram XRD-CT data used in the manuscript entitled "Cycling Rate-Induced Spatially-Resolved Heterogeneities in Commercial Cylindrical Li-Ion Batteries".</p>
Real Operatiοn Data from PV, WT, Battery (measurements from pilot site)
<p>Real Operatiοn Data from PV, WT, Battery (measurements from pilot site)</p>
Mechanical behaviour of inorganic solid-state batteries: Can we model the ionic mobility in the electrolyte with Nernst-Einstein's relation?
<p>(Top left) Governing forces given by Nernst-Einstein’s relationship, where the forward electric force is in a dynamic equilibrium with the backward viscous force. (Bottom left) The dynamic viscosity is a measure of the fluid resistance to flow. (Right) For brittle inorganic solid electrolytes characterised by cracks formation and electrolyte fracture, the stress-strain relationship before the electrolyte fracture can be approximated as linear.</p>
Characterization of photodiodes for detection of variations in part-to-part gap and weld penetration depth during remote laser welding of copper-to-steel battery tab connectors
<p>In this folder, .csv files and Matlab scripts for processing data from experimental campaign that has been reported in the following paper:<br> Chianese, G., Franciosa, P., Nolte, J., Ceglarek, D., and Patalano, S., “Characterization of photodiodes for detection of variations in part-to-part gap and weld penetration depth during remote laser welding of copper-to-steel battery tab connectors.” Journal of Manufacturing Science and Engineering. In-press.</p> <p>As the experimental campaign is made up of two phases, files are divided in two folders:<br> (i) Phase I - Weld penetration depth; and,<br> (ii) Phase II - Part-to-part gap.</p> <p>In each of these two folders, there are:<br> (i) a Matlab live script that, once the code is run, allows the user to select the signals (please, select all of them);<br> (ii) functions to run the code;<br> (iii) Matlab variable files;<br> (iii) a folder with .csv files that contain signals recorded during experimental campaign;<br> (iv) an Excel file reporting experimental setup and process parameters;<br> (v) a PDF file with the live script and results of the data processing for the readers that cannot run Matlab codes.</p>
Supplementary material "Designing robust transformation toward a sustainable circular battery production"
<p>Supplementary material for the publication " Designing robust transformation toward a sustainable circular battery production" in Procedia CIRP. The paper is available at <a href="https://doi.org/10.1016/j.procir.2023.02.069">https://doi.org/10.1016/j.procir.2023.02.069</a>.</p> <p> </p> <p>The underlying research of this publication was funded by the German Federal Ministry of Education and Research within the Competence Cluster Recycling & Green Battery (greenBatt) (03XP0302A) and the research project EffizientNutzen (033R240C). The authors are responsible for the content of this publication.</p> <p><em>Accepted for publication</em></p>
Dataset for publication "Planar sodium-nickel chloride batteries with high areal capacity for sustainable energy storage"
<p><span lang="EN-US">High-temperature ZEBRA battery; sodium-metal halide battery; molten-salt battery; stationary energy storage; alkali metal anode.</span></p> <p>Data used to create Figures 1-4 in the above manuscript.</p>
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