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24 results for “Polymer Electrolytes”
Dynamic sparse X-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst: Raw data and reconstruction software
<pre>Dynamic sparse X-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst: Raw data and reconstruction software Dataset structure: <strong>- Dynamic_PEFC_data.h5</strong> # Raw projection data for dynamic tomography imaging of PEFC catalyst hydration. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /humidity_readout # Relative humidity value at the time each projection is measured, 1D array with axis (Nangle). - /Deform_X # X/Y/Z components for the deformation vector field which characterize nonrigid deformation of the sample. - /Deform_Y - /Deform_Z <strong>- liquid_simulation.h5</strong> # Numerical simulation of dynamic liquid filling process. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /groundtruth_tomograms # Ground truth of the simulated tomograms, 4-dimensional array with axes (Timeframe,Y axis, Z axis, X axis). <strong>- phasetran_simulation.h5</strong> # Numerical simulation of gradual linear density change process. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /groundtruth_tomograms # Ground truth of the simulated tomograms, 4-dimensional array with axes (Timeframe,Y axis, Z axis, X axis). Reconstruction codes: <strong>- astra_nonrigid.zip</strong> # Compressed python package of modified version of astra-toolbox with nonrigid computed tomography implementation. - /astra # Python package folder, need to be added to Python import search path (sys.path). # If the pre-compiled version doesn't work, source code of the pacakge can be downloaded: # https://github.com/zr-gao/astra-toolbox-nonrigid # Follow the instructions and requirements on the website to compile and install the package. <strong>- reconstruction_PEFC.py</strong> # Python script for sparse dynamic tomography of the PEFC dataset. # Need to be in the same folder with Dynamic_PEFC_data.h5 to load data. # Follow the instructions in the code to set reconstruction parameters and export results. # Requirements: cupy, numpy, astra(with nonrigid)*, h5py # * <strong>!!!</strong> Nonrigid computed tomography is used for the reconstruction, therefore the astra package with nonrigid implementation (in astra_nonrigid.zip) is required. <strong>- reconstruction_simulation.py</strong> # Python script for sparse dynamic tomography of numerical simulations. # Need to be in the same folder with liquid_simulation.h5 or phasetran_simulation.h5, loaded filename is selected in the code. # Follow the instructions in the code to set reconstruction parameters and export results. # Requirements: cupy, numpy, astra**, h5py # ** Reconstruction of numerical simulations does not use nonrigid computed tomography, therefore both the astra_nonrigid.zip and the official astra-toolbox package will work. # To download and install the official astra-toolbox refer to the repository: # https://github.com/astra-toolbox/astra-toolbox</pre>
Polymer Electrolyte Membrane Water Electrolyzer Oxygen Bubble Evolution Optical Video Recording For Deep Learning-Enhanced Characterization of Bubble Dynamics in Proton Exchange Membrane Water Electrolyzer by André Colliard-Granero, Keusra A. Gompou, Christian Rodenbücher, Kourosh Malek, Michael H. Eikerling, and Mohammad J. Eslamibidgoli
<p>Dataset used for the training of the segmentation model employed in the work "Deep Learning-Enhanced Characterization of Bubble Dynamics in Proton Exchange Membrane Water Electrolyzer" by André Colliard-Granero, Keusra A. Gompou, Christian Rodenbücher, Kourosh Malek, Michael H. Eikerling, and Mohammad J. Eslamibidgoli. This dataset consists in 35 images and the corresponding manual annotated masks of diverse bubbly scenarios extracted from the optical video recording of a PEMWE with a transparent flow field.</p>
Data - Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 1. Polymer-polymer systems
<p><strong>Overview</strong></p> <p>The production of recombinant biopharmaceuticals is highly dependent of a proper choice of the downstream processing stages. Particularly, the purification that must ensure that all the endotoxins (lipopolysaccharide - LPS) are efficiently removed from the final product. This dataset contains the raw data and statistical analysis for the research entitled - "Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 1. Polymer-polymer systems". </p> <p><strong>Info</strong></p> <p>ANOVA_Turkey_Sub.R <- code for ANOVA analysis in R statistic 3.3.3 <br> glm.R <- code for GLM analysis in R statistic 3.3.3<br> K&REC_LPS_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) and recover (REC) for ANOVA analysis<br> K&REC_LPS_PEG_NaPA_K.docx <- File with ANOVA result of partition coefficient (K) for GFP<br> K&REC_LPS_PEG_NaPA_REC.docx <- File with ANOVA result of recover (REC) for GFP <br> K_GFP_Pol_005.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.05M salt assays <br> K_GFP_Pol_005.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.05M salt assays <br> K_GFP_Pol_005_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.05M salt assays <br> K_GFP_Pol_025.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.25M salt assays <br> K_GFP_Pol_025.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.25M salt assays <br> K_GFP_Pol_025_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.25M salt assays <br> REC_GFP_Pol_005.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.05M salt assays <br> REC_GFP_Pol_005.doc <- File with GLM analysis of GFP recover (REC) in 0.05M salt assays <br> REC_GFP_Pol_005_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.05M salt assays <br> REC_GFP_Pol_025.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.25M salt assays <br> REC_GFP_Pol_025.doc <- File with GLM analysis of GFP recover (REC) in 0.25M salt assays <br> REC_GFP_Pol_025_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.25M salt assays <br> REM_LPS_PEG_NaPA.docx <- File with ANOVA result of LPS removal <br> REM_LPS_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of LPS removal for ANOVA analysis<br> Stability_GFP_PEG_NaPA.docx <- File with ANOVA result of GFP stability<br> Stability_GFP_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of GFP stability results for ANOVA analysis</p> <p>REM_LPS_Pol_005.csv <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.05M salt assays <br> REM_LPS_Pol_005.doc <- File with GLM analysis of LPS removal (REM) in 0.05M salt assays <br> REM_LPS_Pol_005_QQ.png <- Residual quantile plot of GLM analysis of LPS removal (REM) in 0.05M salt assays <br> REM_LPS_Pol_025.csv <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.25M salt assays <br> REM_LPS_Pol_025.doc <- File with GLM analysis of LPS removal (REM) in 0.25M salt assays <br> REM_LPS_Pol_025_QQ.png <- Residual quantile plot of GLM analysis of LPS removal (REM) in 0.25M salt assays</p> <p>K_GFP_Pol_025_NaCl_Li2SO4.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.25M salt assays comparing NaCl and Li2SO4 effect <br> K_GFP_Pol_025_NaCl_Li2SO4.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.25M salt assays comparing NaCl and Li2SO4 effect <br> K_GFP_Pol_025_NaCl_Li2SO4_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.25M salt assays comparing NaCl and Li2SO4 effect </p> <p>REM_LPS_Pol_KI_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in KI assays comparing salt concentration effect <br> REM_LPS_Pol_KI_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in KI assays comparing salt concentration effect<br> REM_LPS_Pol_KI_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in KI assays comparing salt concentration effect<br> REM_LPS_Pol_KNO3_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in KNO3 assays comparing salt concentration effect <br> REM_LPS_Pol_KNO3_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in KNO3 assays comparing salt concentration effect<br> REM_LPS_Pol_KNO3_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in KNO3 assays comparing salt concentration effect<br> REM_LPS_Pol_Li2SO4_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in Li2SO4 assays comparing salt concentration effect <br> REM_LPS_Pol_Li2SO4_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in Li2SO4 assays comparing salt concentration effect<br> REM_LPS_Pol_Li2SO4_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in Li2SO4 assays comparing salt concentration effect<br> REM_LPS_Pol_NaCl_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in NaCl assays comparing salt concentration effect <br> REM_LPS_Pol_NaCl_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in NaCl assays comparing salt concentration effect <br> REM_LPS_Pol_NaCl_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in NaCl assays comparing salt concentration effect</p> <p> </p> <p><strong>Annotation</strong></p> <p>12/12 - Concentration of 12% of each polymer PEG/NaPA</p> <p>16/16 - Concentration of 16% of each polymer PEG/NaPA</p> <p>P/N - PEG/NaPA</p> <p>10e4, 10e5, 10e6 - Concentration of LPS in scientific notation - 10000, 100000, 100000 EU/mL</p> <p>poly - Polymer</p> <p>salt - Salt concentration in the assay</p> <p>tsalt - Type of salt in the assay (NaCl, KNO3, KI and Li2SO4)</p> <p>lps - lipopolysaccharide</p> <p>K - GFP partition coefficient</p> <p>REM - LPS removal</p> <p>REC - GFP recover</p> <p>wo_salt - Assay without salt addition</p> <p><strong>Acknowledgements</strong></p> <p>The authors are grateful for financial support from FAPESP (São Paulo Research Foundation, Brazil) through the following projects: 2005/60159-7; 2007/51978-0; 2014/16424-7; and 2014/19793-3. The authors also acknowledge the support from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil) through the process #0366/09-9 and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil).</p> <p><strong>Consider citing our work. </strong></p> <p>1. Work in progress...</p>
Data Supplement for "Impact of Charged Surfaces on the Structure and Dynamics of Polymer Electrolytes: Insights from Atomistic Simulations"
<p>Data set containing the molecular dynamics simulation data used for the journal article "Impact of Charged Surfaces on the Structure and Dynamics of Polymer Electrolytes: Insights from Atomistic Simulations" (<span>Andreas Thum, </span><span>Diddo Diddens, </span><span>Andreas Heuer, </span><em>J. Phys. Chem. C</em> <strong>2021</strong>, <em>125</em>, 25392−25403, <a href="https://doi.org/10.1021/acs.jpcc.1c07751">https://doi.org/10.1021/acs.jpcc.1c07751</a>).</p>
Collection: Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes Confined Between Electrodes
<p>Metadata record collecting related data sets that contain molecular dynamics simulations of PEO-LiTFSI polymer electrolytes confined between model electrodes.</p> <p>Related data sets:</p> <ul> <li>Uncharged electrodes: <ul> <li><a href="https://doi.org/10.5281/zenodo.13164944">https://doi.org/10.5281/zenodo.13164944</a>:<br>Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Chain Lengths Confined Between Uncharged Electrodes</li> <li><a href="https://doi.org/10.5281/zenodo.13165450">https://doi.org/10.5281/zenodo.13165450</a>:<br>Molecular Dynamics Simulations of Monoglyme-LiTFSI Liquid Electrolytes With Various Salt Concentrations Confined Between Uncharged Electrodes</li> <li><a href="https://doi.org/10.5281/zenodo.13165725">https://doi.org/10.5281/zenodo.13165725</a>:<br>Molecular Dynamics Simulations of Tetraglyme-LiTFSI Liquid Electrolytes With Various Salt Concentrations Confined Between Uncharged Electrodes</li> <li><a href="https://doi.org/10.5281/zenodo.13166024">https://doi.org/10.5281/zenodo.13166024</a>:<br>Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Salt Concentrations Confined Between Uncharged Electrodes</li> </ul> </li> <li>Charged electrodes: <ul> <li><a href="https://doi.org/10.5281/zenodo.13166152">https://doi.org/10.5281/zenodo.13166152</a>:<br>Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Chain Lengths Confined Between Charged Electrodes (+/- 1.00 e/nm²)</li> <li><a href="https://doi.org/10.5281/zenodo.13167128">https://doi.org/10.5281/zenodo.13167128</a>:<br>Molecular Dynamics Simulations of Monoglyme-LiTFSI Liquid Electrolytes With Various Salt Concentrations Confined Between Charged Electrodes (+/- 1.00 e/nm²)</li> <li><a href="https://doi.org/10.5281/zenodo.13167338">https://doi.org/10.5281/zenodo.13167338</a>:<br>Molecular Dynamics Simulations of Tetraglyme-LiTFSI Liquid Electrolytes With Various Salt Concentrations Confined Between Charged Electrodes (+/- 1.00 e/nm²)</li> <li><a href="https://doi.org/10.5281/zenodo.13167551">https://doi.org/10.5281/zenodo.13167551</a>:<br>Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Salt Concentrations Confined Between Charged Electrodes (+/- 1.00 e/nm²)</li> <li><a href="https://doi.org/10.5281/zenodo.13167614">https://doi.org/10.5281/zenodo.13167614</a>:<br>Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Chain Lengths Confined Between Charged Electrodes With Various Surface Charges</li> </ul> </li> <li>Plots: <ul> <li><a href="https://doi.org/10.5281/zenodo.13168242">https://doi.org/10.5281/zenodo.13168242</a>:<br>Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Chain Lengths and Salt Concentrations Confined Between Charged Electrodes With Various Surface Charges: Plots</li> </ul> </li> </ul>
Collection: Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes in the Bulk and Confined Between Electrodes
<p>Metadata record collecting related data sets that contain molecular dynamics simulations of PEO-LiTFSI polymer electrolytes in the bulk and confined between model electrodes.</p> <p>Related data sets:</p> <ul> <li>In the Bulk: <ul> <li><a href="https://doi.org/10.5281/zenodo.13144737">https://doi.org/10.5281/zenodo.13144737</a>:<br>Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Chain Lengths and Salt Concentrations in the Bulk</li> </ul> </li> <li>Confined Between Electrodes: <ul> <li><a href="https://doi.org/10.5281/zenodo.13169120">https://doi.org/10.5281/zenodo.13169120</a>:<br>Collection: Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes Confined Between Electrodes</li> </ul> </li> </ul>
Cellulose nanofiber-reinforced solid polymer electrolytes with high ionic conductivity for lithium batteries
<p>The data contained herein support both the results described in the research article entitled "Cellulose nanofiber-reinforced solid polymer electrolytes with high ionic conductivity for lithium batteries" with the following DOI: <a href="https://doi.org/10.1039/D3TA00380A">10.1039/D3TA00380A</a>, and the corresponding supporting information.</p>
DataSet for "Hybrid Based on Phenazine Conjugated Microporous Polymer as a High-Performance Organic Electrode in Aqueous Electrolytes"
<p>All raw data were obtained directly by the instruments and were then elaborated by us using Origin and/or Excel. All the facilities used, except for the NMR measurements, are present in IMDEA Energy Institute <br> <br> </p>
NFFA-Europe|Pilot proporsal "Production and characterization of highly controlled silicon oxide nanoparticles for solid polymer electrolytes" (PID: 444).
<p>XPS, IR, and QMS data of the nanoparticles synthesized within the NFFA-Europe|Pilot proporsal PID 444</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>
Improved Mechanical Strength without Sacrificing Li-Ion Transport in Polymer Electrolytes
Open the record for dataset details and reuse information.
Data set for theh paper "Recovery of Polymer Electrolyte Fuel Cell exposed to sulfur dioxide" DOI:10.1016/j.ijhydene.2016.01.077
<p>This Excel file contains the data from the following publication</p> <p><br /> Biraj Kumar Kakatia, Anusree Unnikrishnan, Natarajan Rajalakshmi, RI Jafri, KS Dhathathreyan, Anthony RJ Kucernak</p> <p>Recovery of Polymer Electrolyte Fuel Cell exposed to sulfur dioxideInternational Journal of Hydrogen Energy</p> <p>2016</p> <p>DOI:10.1016/j.ijhydene.2016.01.077</p>
Dataset for paper "Investigation of convective transport in the so-called 'gas diffusion layer' used in polymer electrolyte fuel cell"
<p>Dataset containing all data for figures and supplemental material for the paper:<br /> Investigation of convective transport in the porous media of a fuel cell-like system</p> <p>O. Beruski, T. Lopes, A. R. Kucernak and J. Perez.</p>
Data file for the paper "Using corrosion-like processes to remove poisons from electrocatalysts: a viable strategy to chemically regenerate irreversibly poisoned polymer electrolyte fuel cells", Electrochimica Acta 2016, DOI: 10.1016/j.electacta.2016.11.054
<p>Data used in producing the figures in the paper described below</p> <p>If you use this data then please specify as a reference</p> <p>B. K. Kakati, A. R. J. Kucernak, and K Fahy, "Using corrosion-like processes to remove poisons from electrocatalysts: a viable strategy to chemically regenerate irreversibly poisoned polymer electrolyte fuel cells "Electrochimica ActaDOI: 10.1016/j.electacta.2016.11.054</p> <p>Supported by funding from the Engineering and Physical Sciences Research Council under project EP/I037024/1 and the Technology Strategy board under the IDP11 framework for project 102283. </p>
Supplemental Data for Cell Reports Physical Science article "Probing transference and field-induced polymer velocity in block copolymer electrolytes"
<p>The data and Jupyter notebook uploaded here is Supplemental Information for the article:</p><p><strong>Probing transference and field-induced polymer velocity in block copolymer electrolytes </strong></p><p>Coauthored by:</p><p>Michael D. Galluzzo, Hans-Georg Steinrück, Christopher J. Takacs, Aashutosh Mistry, Lorena S. Grundy, Chuntian Cao, Suresh Narayanan, Eric M. Dufresne, Qingteng Zhang, Venkat Srinivasan, Michael F. Toney, and Nitash P. Balsara.</p><p>Journal: Cell Reports Physical Science</p><p>Notes:</p><ul><li>This depository includes the experimental data used in Figure 2, 3, and 4 of the main text and an additional data set.</li><li>The Jupyter notebook "velocity_Echem_Data.ipynb' can be used to visualize the data in the .csv files provided in the folder 'echem' and 'XPCS_fits'.</li><li>The folder 'echem' contains the raw electrochemical data obtained from the two XPCS experiments discussed in the main text and an additional experiment set.</li><li>The folder 'XPCS_fits' contains the results of fitting the autocorrelation functions at each spatial position in the cell at each time point for the two XPCS experiments discussed in the main text and an additional experiment set. </li><li>The additional experiment included here (reffered to as Cell P in the Jupyter notebook) is not discussed in the main text, however it demonstrates that the second 'hump' in velocity (see Figure 3 and S5) that is observed after switching the direction of polarization was replicated in a separate experiment.</li></ul><p> </p>
Dataset for the paper "Nanostructured Catalyst Layer Allowing Production of Ultralow Loading Electrodes for Polymer Electrolyte Membrane Fuel Cells with Superior Performance" published in ACS Appl. Energy Mater.
<p>The data in this spreadsheet was used to produce the figures in the paper</p><p>Authors:</p><p>Colleen Jackson, Michalis Metaxas, Jack Dawson, Anthony Kucernak</p><p>Title:</p><p>Nanostructured Catalyst Layer Allowing Production of Ultralow Loading Electrodes for Polymer Electrolyte Membrane Fuel Cells with Superior Performance</p><p>Journal:</p><p>ACS Appl. Energy Mater. </p><p>DOI:</p><p>10.1021/acsaem.3c01987</p><p>Please cite the above reference if you wish to use this data</p><p>DOI of data:</p><p>10.5281/zenodo.10256698</p>
Dataset for "Investigation of convective transport in the gas diffusion layer used in polymer electrolyte fuel cell"
<p>Dataset to all the figures in the paper (including Supplementary Material):</p> <p>Investigation of convective transport in the gas diffusion layer used in polymer electrolyte fuel cell</p> <p>Beruski, O., Lopes, T., Kucernak, A. R., Perez, J.</p> <p>Phys. Rev. Fluids, 2, 103501, 2017.</p> <p> </p>
Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Chain Lengths and Salt Concentrations in the Bulk
<p>Data set containing molecular dynamics (MD) simulations performed with <a href="https://www.gromacs.org/">Gromacs</a> to investigate the effect of polymer chain length and salt concentration on the atomistic structure and dynamics of PEO-LiTFSI polymer electrolytes in the bulk.</p> <p>PEO = Methoxy-terminated poly(ethylene oxide), sometimes also abbreviated as PEGDME for polyethylene glycol dimethyl ether<br>LiTFSI = Lithium bis(trifluoromethanesulfonyl)imide, sometimes also abbreviated as Li[NTf2].</p> <p>The data set contains:</p> <ul> <li>Gromacs input and output files (except trajectories due to their huge filesize)</li> <li>Processed data</li> <li>Various plots of the data</li> </ul> <p>The zip archives contain:</p> <ul> <li><code>coiling.zip</code>: MD simulations of single PEO chains in vacuum that were performed to produce coiled PEO chains, which were used to generate the starting structures for the bulk simulations.</li> <li><code>bulk.zip</code>: MD simulations of PEO-LiTFSI polymer electrolytes in the bulk.</li> <li><code>plots.zip</code>: Plots of various structural and dynamic quantities as function of the PEO chain length and the salt concentration.</li> </ul>
Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Salt Concentrations Confined Between Uncharged Electrodes
<p>Data set containing molecular dynamics (MD) simulations performed with <a href="https://www.gromacs.org/">Gromacs</a> to investigate the effect of salt concentration on the atomistic structure and dynamics of PEO-LiTFSI polymer electrolytes in the vicinity of uncharged, graphite-like model electrodes.</p> <p>PEO = Methoxy-terminated poly(ethylene oxide), sometimes also abbreviated as PEGDME for polyethylene glycol dimethyl ether<br>LiTFSI = Lithium bis(trifluoromethanesulfonyl)imide, sometimes also abbreviated as Li[NTf2].</p> <p>The data set contains:</p> <ul> <li>Gromacs input and output files (except trajectories due to their huge filesize)</li> <li>Processed data</li> </ul>
Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Chain Lengths Confined Between Uncharged Electrodes
<p>Data set containing molecular dynamics (MD) simulations performed with <a href="https://www.gromacs.org/">Gromacs</a> to investigate the effect of polymer chain length on the atomistic structure and dynamics of PEO-LiTFSI polymer electrolytes in the vicinity of uncharged, graphite-like model electrodes.</p> <p>PEO = Methoxy-terminated poly(ethylene oxide), sometimes also abbreviated as PEGDME for polyethylene glycol dimethyl ether<br>LiTFSI = Lithium bis(trifluoromethanesulfonyl)imide, sometimes also abbreviated as Li[NTf2].</p> <p>The data set contains:</p> <ul> <li>Gromacs input and output files (except trajectories due to their huge filesize)</li> <li>Processed data</li> </ul>
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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)
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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.