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371 results for “electrodes”
Dataset for Link between Anisotropic Electrochemistry and Surface Transformations at Single Crystal Silicon Electrodes: Implications for Lithium Ion Batteries
<p>This dataset provides the raw data to the manuscript</p> <p>"<strong>Link between Anisotropic Electrochemistry and Surface Transformations at Single Crystal Silicon Electrodes: Implications for Lithium Ion Batteries"</strong></p> <p>Specifically, the following measurements are provided:</p> <ul> <li>Electrochemical measurements as cyclic voltammetry using scanning electrochemical cell microscopy for three different Si crystallographic orientations (100, 110, 311) in 1 M LiPF6 in ethylene carbonate - ethyl methyl carbonate ("SECCM/")</li> <li>Scanning electron microscopy and transmission electron microscopy imaging of pristine and cycled samples ("Images/")</li> </ul>
Data related to the article "Frequency-dependent impedance of nanocapacitors from electrode charge fluctuations as a probe of electrolyte dynamics"
<p>Contains input files and data used to generate the figures of the article:</p> <p>Frequency-dependent impedance of nanocapacitors from electrode charge fluctuations as a probe of electrolyte dynamics<br> (Giovanni Pireddu and Benjamin Rotenberg)</p> <p>arXiv: https://arxiv.org/abs/2206.13322</p> <p>The folder EXAMPLE_INPUT_FILES contains typical <a href="https://doi.org/10.21105/joss.02373">MetalWalls</a> (<a href="https://gitlab.com/ampere2/metalwalls">repository</a>) input files used to perform the simulations.</p> <p>The folder DATA_FIGURES contains the processed data used to plot all the figures of the paper (see below).<br> </p> <p>The 'd*' labels are used in the directory or file names to refer to the following interelectrode distances considered:<br> - 'd1' corresponds to 2.51 nm;<br> - 'd2' corresponds to 4.94 nm;<br> - 'd3' corresponds to 9.76 nm;<br> - 'd4' corresponds to 19.42 nm;</p> <p><br> Figure 1:<br> - 'Fig1_Continuum.dat': <br> - Capacitance calculated considering a continuum approximation<br> - 'Fig1_DDS.dat':<br> - Capacitance calculated considering the DDS model (three capacitors in series)<br> - 'Fig1_MD.dat':<br> - Capacitance calculated from MD simulations. Includes the capacitance of the empty capacitor.</p> <p>Figure 2:<br> Panel A<br> - 'Fig2_QACFd*.dat':<br> - Time autocorrelation function of the electrode charge fluctuations<br> Panel B<br> - 'Fig2_Qrampd*.dat':<br> - Charge profile upon a step in voltage (0 to 1 V)<br> - 'Fig2_Vramp.dat':<br> - Voltage ramp related to the charging profiles<br> Panel C<br> - 'Fig2_QACFNormd*.dat':<br> - Normalized charge autocorrelation function<br> -'Fig2_QrampNormd*.dat'<br> - Normalized charge profile</p> <p>Figure 3:<br> - 'Fig3_MDd*.dat':<br> - Real and imaginary parts of impedance as estimated from MD simulations<br> - 'Fig3_ECd*.dat'<br> - Real and imaginary parts of impedance as calculated from the equivalent circuit models</p> <p>Figure 4:<br> - 'Fig4_MDd*.dat':<br> - Magnitude of admittance as estimated from MD simulations<br> - 'Fig4_Debyed*.dat':<br> - Magnitude of admittance as calculated from the Debye relaxation model<br> Inset<br> - 'Fig4_MDTau.dat':<br> - Relaxation time estimated from MD simulations<br> - 'Fig4_TauFit.dat':<br> - Fit of the relaxation time</p>
Dataset for Charge collection efficiency, underlying recombination mechanisms, and the role of electrode distance of vented ionization chambers under ultra-high dose-per-pulse conditions
<p>Dataset for paper: Kranzer et al., <a href="https://www.sciencedirect.com/journal/physica-medica">Physica Medica</a> <a href="https://www.sciencedirect.com/journal/physica-medica/vol/104/suppl/C">Volume 104</a>, December 2022, Pages 10-17</p> <p><a href="https://doi.org/10.1016/j.ejmp.2022.10.021">https://doi.org/10.1016/j.ejmp.2022.10.021</a></p>
NewSOC, supplementary information to WT2.5.4 "Cells with honeycomb structured oxygen electrodes": electrochemical and post-mortem data sets.
<p>These are data set, related to participation of the IEN in project NewSOC. It includes results of the SEM-EDS analysis of the cells with hexagonal current collecting net and electrochemical performance data, both EIS and C-V characteristics. Results are grouped in zip archives, named according to cell design, “infill-net”.</p> <p>Compositions:</p> <p>LNF – LaNi<sub>0.6</sub>Fe<sub>0.4</sub>O<sub>3</sub> (net)</p> <p>LSC – La<sub>0.6</sub>Sr<sub>0.4</sub>CoO<sub>3-</sub><sub>d</sub> (infill)</p> <p>LSF – La<sub>0.5</sub>Sr<sub>0.5</sub>FeO<sub>3-</sub><sub>d</sub> (infill)</p> <p>LSCCF – La<sub>0.6</sub>Sr<sub>0.4</sub>Co<sub>0.15</sub>Cu<sub>0.05</sub>Fe<sub>0.8</sub>O<sub>3-</sub><sub>d </sub>(net)</p> <p>PCM – Pr<sub>0.5</sub>Ca<sub>0.5</sub>MnO<sub>3 </sub>(net)</p> <p>BSCFM – Ba<sub>0.5</sub>Sr<sub>0.5</sub>Co<sub>0.725</sub>Fe<sub>0.2</sub>Mo<sub>0.075</sub>O<sub>3-</sub><sub>d</sub> (infill)</p> <p> </p> <p><strong>Data presentation. </strong></p> <p><em>C-V characteristics:</em></p> <p>This is text files, generated by Zahner galvanostat, with self-decriptional titles.</p> <p>“05iv_650c_100h2+100h2o_500air.txt” – measurement at 650°C, 100 mL/min H<sub>2</sub> and 100 mL/min H<sub>2</sub>O on fuel side, 500 mL/min of air on air side.</p> <p><em>EIS data:</em></p> <p>EIS results were extracted from proprietary binary files, generated by Zahner galvanostat, and raw data is generally meaningless except the owners of such hardware. So, extracted EIS can be found in Excel files, used in analysis, in sheet “Experimental”. Other sheets in xlsx include some metadata (“info”), results of the equivalent circuit fit (“fit”) and some plots. Fit results might not be relevant. </p> <p><em>SEM</em></p> <p>Post-mortem results presented as SEM images (tif or jpg files) and pdf files with results of the EDS analysis.</p> <p><strong>LSC-LNF </strong></p> <p><em>(air flow 1 L/min, current density 0.25 A/cm<sup>2</sup>)</em></p> <p>test_1_07: </p> <p>03_eis20200917142808.xlsx – EIS, SOFC, 700°C, Flows L/min: F:0.2 H<sub>2</sub>;</p> <p>05_eis20200917123105.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.1 H<sub>2</sub>+ 0.1 H<sub>2</sub>O;</p> <p>08_eis20200917123857.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.1 H<sub>2</sub>+ 0.1 H<sub>2</sub>O;</p> <p>10_eis20200917131537.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.1 H<sub>2</sub>+ 0.1 H<sub>2</sub>O;</p> <p>test_1_08:</p> <p>03_eis20200917125707.xlsx – EIS, SOFC, 700°C, Flows L/min: F:0.2 H<sub>2</sub>;</p> <p>09_eis20200917130019.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.09 H<sub>2</sub>+ 0.21 H<sub>2</sub>O;</p> <p>10_eis20200917130600.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.06 H<sub>2</sub>+ 0.14 H<sub>2</sub>O;</p> <p>12_eis20200917130737.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.12 H<sub>2</sub>+ 0.28 H<sub>2</sub>O;</p> <p>test_3_14:</p> <p>01_eis20210517102042.xlsx– EIS, SOFC, 700°C, Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>; 05_eis20210517102625.xlsx– EIS, SOFC, 700°C, flows L/min: F:0.1 H<sub>2</sub>+ 0.1 H<sub>2</sub>O;</p> <p>07_eis20210517102305.xlsx– EIS, SOEC, 700°C, flows L/min: F:0.06 H<sub>2</sub>+ 0.14 H<sub>2</sub>O;</p> <p>SEM</p> <p><em>(post-mortem after test_1_07)</em></p> <p>ogniwo_310_2020 ****.jpg - surface</p> <p> </p> <p><strong>BSCMF-PCM</strong></p> <p><em>(SOFC, air flow 0.5 L/min)</em></p> <p>test_2_14</p> <p>01eis_700c_cc4a_100h2+100n2_500air_eqc20220110112836.xlsx –700°C, 0.25 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub></p> <p>02eis_700c_cc4a_100h2+100h2o_500ai_eqc20220110112724.xlsx –700°C, 0.25 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>04eis_650c_cc3a_100h2+100h2o_500ai_eqc20220110112503.xlsx–650°C, 0.1875 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>06eis_650c_cc3a_100h2+100n2_500air_eqc20220110112332.xlsx –650°C, 0.1875 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>07eis_625c_cc3a_100h2+100n2_500air_eqc20220110112214.xlsx –625°C, 0.125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>08eis_625c_cc3a_100h2+100h2o_500ai_eqc20220110111834.xlsx–625°C, 0.125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>test_1_67</p> <p>01_eqc20220831134628.xlsx–700°C, 0.125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub></p> <p>02_eqc20220831134724.xlsx - 700°C, 0.25 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>04_eqc20220831135442.xlsx–650°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>06_eqc20220831135622.xlsx - 650°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>08_eqc20220831135801.xlsx - 625°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>09_eqc20220831135933.xlsx –650°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>SEM</p> <p><em>(post-mortem of the test_2_14)</em></p> <p>493-2021-1.pdf, 493-2021-1i.pdf, 493-2021-2.pdf, 493-2021-2-2.pdf, 493-2021-2-3.pdf –cross-sections with EDS</p> <p>493_2021_*_**.tif - cross-sections</p> <p> </p> <p><strong>BSCMF-LSCCF</strong></p> <p><em>(SOFC, air flow 0.5 L/min)</em></p> <p> test_2_08</p> <p>01_eis20211104144342.xlsx - 700°C, 0.25 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2 </sub></p> <p>03eis_700c__eis20211108102241.xlsx - 700°C, 0.25 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>04eis_700c__eis20211108102401.xlsx - 700°C, 0.25 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>08eis__eis20211110094642.xlsx - 650°C, 0.1875 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2 </sub></p> <p>10eis__eis20211110094945.xlsx - 650°C, 0.1875 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>11eis__eis20211110101358.xlsx - 625°C, 0.125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>13eis__eis20211110100837.xlsx- 625°C, 0.125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p> test_2_26</p> <p>04_eqc20220817114103.xlsx - 700°C, 0.25 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>06_eqc20220817121529.xlsx - 700°C, 0.25 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2 </sub></p> <p>07_eqc20220802084119.xlsx - 650°C, 0.1875 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1</p> <p>08_eqc20220802084616.xlsx - 650°C, 0.1875 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>10_eqc20220802150705.xlsx - 625°C, 0.125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>11_eqc20220802150108.xlsx - 625°C, 0.125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>SEM</p> <p><em>(post-mortem of the test_2_26)</em></p> <p>661_BSCMF_LSCCF_p.pdf – cross-section with EDS</p> <p>661_BSCMF_LSCCF_PM.pdf - surface with EDS</p> <p>661_BSCMF_LSCCF_p_01.tif, 661_BSCMF_LSCCF_p_02.tif, 661_BSCMF_LSCCF_p_03.tif, 661_BSCMF_LSCCF_p_04.tif - cross-section, infill zone</p> <p>661_BSCMF_LSCCF_p_05.tif, 661_BSCMF_LSCCF_p_06.tif - cross-section, net zone zone</p> <p>661_BSCMF_LSCCF_PM_**.tif - surface</p> <p> </p> <p><strong>LSF-LSCCF</strong></p> <p><em>(SOFC, air flow 0.5 L/min)</em></p> <p>test_1_65</p> <p>01_eqc20220816105347.xlsx - 700°C, 0. 1875 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>02_eqc20220816105941.xlsx - 700°C, 0. 1875 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>04_eqc20220816112311.xlsx - 650°C, 0. 125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>06_eqc20220816111640.xlsx - 650°C, 0.125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>07_eqc20220816142436.xlsx- 625°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>08_eqc20220816142842.xlsx-625°C, 0.625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>SEM</p> <p><em>(post-mortem) </em></p> <p>663_LSF_LSCCF_p.pdf – cross-section with EDS</p> <p>663_LSF_LSCCF_PM.pdf - surface with EDS</p> <p>663_LSF_LSCCF_P_GR_**.tif – cross-section of the cell</p> <p>663_LSF_LSCCF_P_LSCCF_**.tif – surface of the LSCCF grid</p> <p>663_LSF_LSCCF_PM_**.tif - surface of the LSF infill</p> <p> </p> <p> </p> <p><strong>LSF-PCM</strong></p> <p><em>(SOFC, air flow 0.5 L/min)</em></p> <p>tests_1_66</p> <p>01_eqc20220831133210.xlsx - 700°C, 0. 125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub></p> <p>02_eqc20220831133409.xlsx - 700°C, 0. 125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub></p> <p>03_eqc20220831133928.xlsx - 700°C, 0. 125 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>05_eqc20220831134048.xlsx - 650°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>06_eqc20220831134142.xlsx - 650°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>08_eqc20220831134237.xlsx - 625°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 H<sub>2</sub>O;</p> <p>10_eqc20220831134412.xlsx - 625°C, 0.0625 A/cm<sup>2</sup> Flows L/min: F:0.1 H<sub>2</sub>+0.1 N<sub>2</sub>;</p> <p>SEM</p> <p><em>(post-mortem)</em></p> <p>658_LSF_PCM_p.pdf – cross-section with EDS</p> <p>658_LSF_PCM_PM.pdf - surface with EDS</p> <p>658_LSF_PCM_P_LSF_**.tif – cross-section, infill zone</p> <p>658_LSF_PCM_P_pcm_**.tif - cross-section, net zone</p> <p>658_LSF_PCM_PM_**.tif - surface</p> <p><strong>description.pdf </strong>- pdf version of this information.</p>
Guidelines for the rational design and engineering of 3D manufactured solid oxide fuel cell composite electrodes
<p>This file contains the data reported in the paper:</p> <p>A Bertei, F Tariq, V Yufit, E Ruiz-Trejo, N P Brandon, <em>Guidelines for the rational design and engineering of 3D manufactured solid oxide fuel cell composite electrodes</em>, <strong>Journal of the Electrochemical Society</strong> (2016)</p> <p>All the data here reported can be reproduced by solving the equations reported in the manuscript with the corresponding parameters.</p>
PV electrodes electrochemistry
<p>Electrochemistry of Polyviologens deposited on FTO glass by dropcasting</p>
Datasets to Poly(ethylene oxide)-based Electrolytes for Solid-State Potassium Metal Batteries with Prussian Blue Positive Electrode
<p>This dataset provides the raw data to the manuscript</p> <p>"<strong>Poly(ethylene oxide)-based Electrolytes for Solid-State Potassium Metal Batteries with Prussian Blue Positive Electrode"</strong></p> <p>published in ACS Appl. Polym. Mater. (DOI: <a href="https://doi.org/10.1021/acsapm.2c00014">10.1021/acsapm.2c00014</a> ) / <a href="https://doi.org/10.1021/acsapm.2c00014">https://doi.org/10.1021/acsapm.2c00014</a></p> <p>Specifically, the following measurements are provided:</p> <p>Electrochemical cell tests of liquid and solid electrolytes ("CYCLING_" & Ratecapability test)</p> <p>Solid electrolyte characterization:</p> <p>Differential Scanning Calorimetry ("DSC_")</p> <p>Electrochemical Impedance Spectroscopy ("EIS_")</p> <p>Rheological measurements ("RHEO_")</p> <p>X-ray diffraction data ("XRD_")</p>
Imaging data of mechanically loaded, micro-patterned, silk-reinforced cellulose films with gold coating for flexible electrodes in medical implants
<p>Neurodegenerative diseases can be treated using a functional interface between the physically soft tissue such as brain and the man-made electrodes. The orders of magnitude harder neural probes cause local injuries, due to periodic micromovements owing to breathing and pulsatile blood flow leading to encapsulation and related collapsing signals. An alternative to the currently used neural implant films including polyimide, poly(p-xylylene), SU-8 - epoxy-based negative photoresist, liquid crystal polymer, and benzocyclobutene is the natural polymer cellulose with an elastic modulus between 100 and 200 MPa. This article elucidates the measurement of the mechanical properties of bare as well as mono- and double-layer silk-reinforced cellulose in phosphate-buffered saline using a universal testing machine. In addition, the article contains electron microscopy data of these micro-structured, gold-coated films subsequent to peel-off tests to access the impact of micro-structures on gold adhesion on cellulose. These imaging data were completed by electron micrographs of mechanically loaded gold-coated cellulose films to demonstrate the impact of micro-structures on crack formation. Finally, the phosphate-buffered saline-induced swelling of the micro-structure was visualized by electron micrographs obtained before and after two-month storage in air and phosphate-buffered saline, respectively.</p>
Accelerated Stress Tests for Solid Oxide Cells via Artificial Aging of the Fuel Electrode
<p><strong>AD ASTRA: Data from Experiments for Artificial Aging of the Fuel Electrode in Solid Oxide Cells via Redox Cycling</strong></p> <p>One of the big hurdles towards fast deployment of Solid Oxide Cells (fuel cells or electrolyzers) is durability. Although intensive works are carried out for life time improvement, they meet a serious problem concerning long term electrochemical tests for accumulation of reliable data that may continue several years, which is unaffordable. A problem-solving approach is the introduction of Accelerated Stress Tests (AST) applying high levels of stress for a shorter period thus reducing the test time for degradation qualification.</p> <p>Since there are no definite criteria for the level of acceleration of a specific degradation phenomenon, the selection of aggravating conditions is a critical moment which is under studies in the FCH JU Project AD ASTRA (GA 825027).</p> <p>Herein we present data accumulated during the development of a procedure for artificial accelerated aging of the fuel electrode via redox cycling. They include electrochemical testing (current-voltage curves and impedance measurements) and microstructural characterization (SEM-BSE image analysis), as well as procedure for redox cycling.</p>
DATASET: Using auxiliary electrochemical working electrodes as probe during contact glow discharge electrolysis: A proof of concept study
<p>This project contains all the data shown in the figures of the manuscript (and the supporting information) entitled:<br> 'Using auxiliary electrochemical working electrodes as probe during contact glow discharge electrolysis: A proof of concept study'<br> (doi:10.26434/chemrxiv-2022-0v5sc).</p> <p>The data to each figure is provided in a subfolder where each curve is stored as a single CSV.<br> The filenames contain labels describing the curves.</p>
Free-standing electrochemically coated MoSx based 3D-printed nanocarbon electrode for solid-state supercapacitor application
<p>Raw data of journal article "Free-standing electrochemically coated MoSx based 3D-printed nanocarbon electrode for solid-state supercapacitor application" DOI: 10.1039/d0nr06479c</p>
Flexible Graphite−Poly(Lactic Acid) Composite Films as Large-Area Conductive Electrodes for Energy Applications
<p>Raw data of energy storage part -author Kalyan Ghosh </p>
Sample dataset to accompany Hamilton, Chang, Lee, & Chang. Semi-automated anatomical labeling and inter-subject warping of high-density intracranial recording electrodes in electrocorticography
<p>This dataset accompanies the following paper: <br> Hamilton, Chang, Lee, and Chang. Semi-automated anatomical labeling and inter-subject warping of <br> high-density intracranial recording electrodes in electrocorticography</p> <p>This data includes an anonymized and de-identified CT and T1 MRI scan, plus all intermediate and final files<br> produced by the img_pipe software for testing and instructional purposes. This subject had a right hemisphere implantation including high density grids, strip electrodes, and depth electrodes.</p> <p>img_pipe software and installation instructions can be found at http://github.com/changlabucsf/img_pipe</p> <p>If you wish to follow along yourself, we recommend creating a new subject in your Freesurfer $SUBJECTS_DIR, <br> then copy the acpc and CT directories from this dataset into that new subject directory. </p> <p>The electrode montage is provided in test_subj_montage.txt and describes the type of electrodes implanted<br> (grid, strip, or depth) and their general location. </p>
Raw data for the article entitled ''Evaluation of in-plane architecture in a thermo-electrochemical cell with nanostructured and porous Sb:SnO2 electrodes''
<p>Raw data for the plots in the article entitled ''Evaluation of in-plane architecture in a thermo-electrochemical cell with nanostructured and porous Sb:SnO2 electrodes''.</p>
In vivo and in vitro electrochemical impedance spectroscopy analysis of acute and chronic intracranial electrodes
<p>Invasive intracranial electrodes are used in both clinical and research applications for recording and stimulation of brain tissue, providing essential data in acute and chronic contexts. The impedance characteristics of the electrode–tissue interface (ETI) evolve over time and can change dramatically relative to pre-implantation baseline. Understanding how ETI properties contribute to the recording and stimulation characteristics of an electrode can provide valuable insights for users who often do not have access to complex impedance characterizations of their devices. In contrast to the typical method of characterizing electrical impedance at a single frequency, we demonstrate a method for using electrochemical impedance spectroscopy (EIS) to investigate complex characteristics of the ETI of several commonly used acute and chronic electrodes. We also describe precise modeling strategies for verifying the accuracy of our instrumentation and understanding device–solution interactions, both in vivo and in vitro. Included with this publication is a dataset containing both in vitro and in vivo device characterizations, as well as some examples of modeling and error structure analysis results. These data can be used for more detailed interpretation of neural recordings performed on common electrode types, providing a more complete picture of their properties than is often available to users.</p>
Enhancement of bubble transport in porous electrodes and catalysts
<p>data for the publication "Enhancement of bubble transport in porous electrodes and catalysts" in <em>J. Chem. Phys.</em> 160, 194706 (2024)</p>
BRAIN Journal-Brain signal analysis using EEG and Entropy to study the effect of physical and mental tasks on cognitive performance-Figure 1. The 10-20 international system electrode placement showing the EEG electrode placement
<p>For the EEG analysis, the average power in the theta band (4 – 8 Hz), and alpha band (8 – 12<br> Hz) were computed at the frontal and parietal electrodes Fz and Pz respectively. Next, the ratio of<br> these two powers was determined, and named the ‘cognitive ratio’ as several researchers found that<br> the fronto-parietal network play important roles in cognitive activities.</p>
Figure 3. Electrode placement diagram-Classification of Human Emotion from Deap EEG Signal Using Hybrid Improved Neural Networks with Cuckoo Search
<p>Reference electrode placed AFz placed in between AF1 and AF2 electrode and ground<br> electrode Oz is placed between O1 and O2 electrodes. The impedance of the electrode range is<br> 5KΩ. The sampling rate was fixed range between 256 samples per second for all the channels.<br> Figure 3 shown in below which is represent the electrode placement diagram. The recorded EEG<br> signal is used to recognize the different level of emotions.</p>
Activity – or lack thereof – of RuO2 based electrodes in the electrocatalytic reduction of CO2
<p>Raw data for the article</p> <p><em>Activity – or lack thereof – of RuO<sub>2</sub> based electrodes in the electrocatalytic reduction of CO<sub>2</sub></em></p> <p>Stefano Mezzavilla, Yu Katayama, Reshma R Rao, Jonathan Hwang, Anna Regoutz, Yang Shao-Horn, Ib Chorkendorff, Ifan Erfyl Lester Stephens</p> <p>DOI: 10.1021/acs.jpcc.9b01431</p> <p> </p> <p>The dataset includes:</p> <p>1) Experimental Methods</p> <p>2) File with raw data of figures in the main text and supplementary Information file (Excel file with multiple tabs)</p>
Brain Invaders calibration-less P300-based BCI using dry EEG electrodes Dataset (bi2014a)
<p><strong>Summary:</strong></p> <p>This dataset contains electroencephalographic (EEG) recordings of 71 subjects playing to a visual P300 Brain-Computer Interface (BCI) videogame named <em>Brain </em><em>Invaders</em>. The interface uses the oddball paradigm on a grid of 36 symbols (1 Target, 35 Non-Target) that are flashed pseudo-randomly to elicit the P300 response. EEG data were recorded using 16 active dry electrodes with up to three game sessions. The experiment took place at GIPSA-lab, Grenoble, France, in 2014. A full description of the experiment is available at <a href="https://hal.archives-ouvertes.fr/hal-02171575">https://hal.archives-ouvertes.fr/hal-02171575</a>. Python code for manipulating the data is available at <a href="https://github.com/plcrodrigues/py.BI.EEG.2014a-GIPSA">https://github.com/plcrodrigues/py.BI.EEG.2014a-GIPSA</a>. The ID of this dataset is <em>bi2014a.</em></p> <p> </p> <p><strong>Full description of the experiment and dataset: </strong><a href="https://hal.archives-ouvertes.fr/hal-02171575">https://hal.archives-ouvertes.fr/hal-02171575</a></p> <p> </p> <p><strong><em>Investigators</em>:</strong> Eng. Louis Korczowski, B. Sc. Ekaterina Ostaschenko</p> <p> </p> <p><strong><em>Technical</em></strong> <strong><em>Support</em></strong>: Eng. Anton Andreev, Eng. Grégoire Cattan, Eng. Pedro. L. C. Rodrigues, M. Sc. Violette Gautheret</p> <p> </p> <p><strong><em>Scientific Supervisor:</em></strong> Ph.D. Marco Congedo</p> <p> </p> <p><strong>ID of the dataset: </strong><em>bi2014a</em></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.