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95 results for “Fuel Cell”
Dataset of "Activity-stability relationship in magnetron co-sputtered bimetallic catalysts for proton exchange membrane fuel cells"
<p>In the present study, magnetron sputtered PtxM100-x (M = Co, Cu, Y; x = 25, 50, 75 and 100) bimetallic alloys were investigated as PEMFC cathodes. Accurate composition control enabled a systematic study of the correlation between alloy composition, activity, and stability. The catalysts underwent thorough characterization, employing a diverse portfolio of characterization techniques such as scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy and cyclic voltammetry. The activity of all investigated alloys was tested directly in a fuel cell device, while stability was assessed through potentiodynamic cycling in a half-cell. <br>The activity-stability index, considering experimental results for both activity and stability, was calculated and compared for all investigated catalysts. All alloys exhibited a volcano-type trend in activity-stability index as a function of the concentration of alloying element with peaks observed at Pt50Co50, Pt50Cu50 and Pt75Y25 for respective alloys, surpassing that of monometallic platinum. Overall, Pt50Co50 emerged as a catalyst with the highest activity-stability ratio.</p>
Dataset for "Impact of the flow-field distribution channel cross-section geometry on PEM fuel cell performance: stamped vs. milled channel"
<p>Experimental data comprises raw data from load curve characterisation of a PEM fuel cell used for the validation of the mathematical model. Model data comprise of space-dependent values of hydrogen and oxygen concentration, local current densities, gas pressures and gas velocities in the modelled cell. These data were used for the investigation of the effect of different geometric parameters of flow-field channels on the performance of a PEM fuel cell.</p>
Dataset of "Capabilities of a novel electrochemical cell for operando XAS and SAXS investigations for PEM fuel cells and water electrolysers"
<p>With this work we present a reversible electrochemical cell and introduce a valuable approach, suitable for being used either for in operando X-Ray Absorption Spectroscopy (XAS) and Small Angle X-Ray Scattering (SAXS). The reversible electrochemical cell was used to depict the time-resolved degradation of a Pt/C catalyst material for Proton Exchange Membrane Fuel Cells (PEMFC). The evolution of the specific electrochemical active surface area (ECSA) was coupled to the evolution of morphological parameters, supported by the analysis of Pt oxidation state. As a result, we obtain a coherent picture in which: the increase of particle (and particle cluster) size is connected to the diminishing of ECSA and to the changes in the fraction of metallic Pt, detailing as the evolution develops in the first 2000 cycles, as previously observed on catalyst model systems. Finally, we introduce some preliminary results underlying the change in Ir oxidation state for a commercial Ir/IrO X catalyst material for PEM water electrolysers and showing as this change is not sufficient to induce any remarkable morphological variations within 500 cycles of accelerated stress tests.</p>
Nanostructured La0.75Sr0.25Cr0.5Mn0.5O3–Ce0.8Sm0.2O2 Heterointerfaces as All-Ceramic Functional Layers for Solid Oxide Fuel Cell Applications
<p>Dataset for article "Nanostructured La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Mn<sub>0.5</sub>O<sub>3</sub>–Ce<sub>0.8</sub>Sm<sub>0.2</sub>O<sub>2</sub> Heterointerfaces as All-Ceramic Functional Layers for Solid Oxide Fuel Cell Applications" published in <em>ACS Appl. Mater. Interfaces</em> 2022.</p> <p>The data includes:</p> <ul> <li>Schematic on the nanostructures fabricated for the work (Figure 1)</li> <li>Top view AFM images of the nanostructures studied (Figure 3)</li> <li>TEM-EDX images of the nanostructures studied (Figure 4)</li> <li>ASTAR analysis of the nanostructures studied (Figure 5)</li> <li>X-Ray Diffraction data of thin films with composition: La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Mn<sub>0.5</sub>O<sub>3</sub> (LSCrMn), Ce<sub>0.8</sub>Sm<sub>0.2</sub>O<sub>2</sub> (SDC), and two La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Mn<sub>0.5</sub>O<sub>3</sub>–Ce<sub>0.8</sub>Sm<sub>0.2</sub>O<sub>2 </sub>(LSCrMn-SDC) nanostructures -bilayer (BL) and nanocomposite (NC)-</li> <li>Electrochemical Impedance Spectroscopy raw data for LSCrMn, SDC and LSCrMn-SDC thin films measured under air and wet hydrogen atmospheres at different temperatures (630-750 ºC)</li> <li>Arrhenius analysis of the area specific resistance (ASR) of the films under air and hydrogen atmospheres</li> <li>In-plane conductivity evolution with temperature data measured under air and 5% hydrogen atmospheres of the two LSCrMn-SDC nanostructures</li> <li>ASR evolution with time measured for over 400 h at 780 ºC</li> </ul>
Minimal data set for: Air-liquid interface exposure of A549 human lung cells to characterize the hazard potential of a gaseous bio-hybrid fuel blend
<p>This minimal data set presents the values behind the means and standard deviation for the publication entitled: "Air-liquid interface exposure of A549 human lung cells to characterize the hazard potential of a gaseous bio-hybrid fuel blend"</p>
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>
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>
Dataset for publication "Chemical-Dealloying-Derived PtPdPb-Based Multimetallic Nanoparticles: Dimethyl Ether Electrocatalysis and Fuel Cell Application" in ACS Applied Materials & Interfaces 2023, 15, 49, 56930–56944
<p>Dataset for publication "Chemical-Dealloying-Derived PtPdPb-Based Multimetallic Nanoparticles: Dimethyl Ether Electrocatalysis and Fuel Cell Application" in ACS Applied Materials & Interfaces 2023, 15, 49, 56930–56944, https://doi.org/10.1021/acsami.3c11003</p> <p>Dataset contains XRD, SAXS, Particle size distribution, HRTEM, Electrochemical characterisation, Fuel cell current-voltage curve, DFT calculations, Elemental maps and electrode stability measurements made on pristine and chemically dealloyed carbon supported Pt2PdPb2 nanoparticles.</p>
Data generated by the model presented in the research article entitled "Simulation of mass and heat transfer in an evaporatively cooled PEM fuel cell"
<p>This repository provides all the data and scripts necessary to reproduce the line plots shown in the manuscript entitled "Simulation of mass and heat transfer in an evaporatively cooled PEM fuel cell".</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>
Lattice Boltzmann simulation of liquid water transport in gas diffusion layers of proton exchange membrane fuel cells: Impact of gas diffusion layer and microporous layer degradation on effective transport properties
<p><span>Underlying data to publication Sarkezi-Selsky et al., <em>J. Pow. Sour.</em> 556 (2023) 232415,<span> https://doi.org/10.1016/j.jpowsour.2022.232415</span> <br><br>Polymer Electrolyte Membrane Fuel Cells (PEMFCs) represent a promising technology for clean drivetrain solutions, in particular for heavy-duty applications. However, lifetime requirements demand high durability of each cell component.<br></span><span>In this work, transport of liquid water through pristine and degraded gas diffusion layers (GDL) was simulated with a 3D Color-Gradient Lattice Boltzmann model. The GDL microstructure was reconstructed </span><span>from high-resolution X-ray micro-computed tomography (</span><span>μ</span><span>-CT) of an impregnated Freudenberg H14. The </span><span>effect of a microporous layer (MPL) was considered by reconstruction of an impregnated and MPL-coated H14. Aged microstructures were generated artificially, assuming loss of polytetrafluoroethylene (PTFE) within the GDL and increase of MPL macroporosity as main degradation mechanisms. Liquid water transport within aged microstructures was simulated by imposing a liquid phase flow rate until breakthrough was reached. Subsequently, the GDL microstructures were analyzed for their breakthrough characteristics by means of saturation and effective gas transport properties. When the MPL was pristine, no distinct GDL degradation effect was observable, this was attributed to the MPL dominating capillary transport. MPL aging, however, led to increased saturations and thus to a deterioration of the effective gas transport. With a partially degraded MPL, aging of the GDL then appeared to affect the breakthrough characteristics.</span></p>
Supplementary Material of "Fuel Starvation in Automotive PEMFC Stacks: Hydrogen Stoichiometry and Electric Cell-to-Cell Interaction"
<p>This video contains the discussed experimental data of the following journal publication, which explains experimental setup, test cycle and the shown data in detail.</p> <p><strong>Nissen, J., Boye, J. P., Schwämmlein, J. N., & Hölzle, M. (2024). Fuel starvation in automotive PEMFC stacks: hydrogen stoichiometry and electric cell-to-cell interaction. <em>Journal of Physics: Energy</em>. <br><a title="https://doi.org/10.1088/2515-7655/ad5f54" href="https://doi.org/10.1088/2515-7655/ad5f54">https://doi.org/10.1088/2515-7655/ad5f54</a></strong></p> <p>Version 01: Video as .MKV file. Quite large and not supported for in-browser visualization by zenodo.</p> <p>Version 02: Changed video format from .MKV to .MP4 to reduce file size and allow in-browser visualization by zenodo. Identical content as Version 01.</p>
Dataset to: Realistic accelerated stress tests for PEM fuel cells: Test procedure development based on standardized automotive driving cycles
<p>This is the dataset to the published article "Realistic accelerated stress tests for PEM fuel cells: Test procedure development based on standardized automotive driving cycles" (DOI: 10.1016/j.ijhydene.2023.08.292) in which the degradation of two commercial PEM fuel cell stacks was analyzed. <strong>Please cite this publication if you use the dataset in a publication as follows</strong>:</p> <p>P. Thiele, Y. Yang, S. Dirkes, M. Wick, S. Pischinger, Realistic accelerated stress tests for PEM fuel cells: Test procedure development based on standardized automotive driving cycles, Int. J. Hydrogen Energy 52 (Part D) (2024) 1065–1080, https://doi.org/10.1016/j.ijhydene.2023.08.292.</p>
[DATASET 8] - MICROBIAL FUEL CELLS (MFCS)
<p>In the framework of GrowBot project, Task 7.1 aims to develop autonomous MFCs that can provide energy to the robot and, in addition, do not require continuous monitoring of the cell conditions.</p> <p>Bioo's objectives are: i) to have a cell that is easy to install, ii) that does not require of a continuous maintenance and iii) that is adaptable to non-wet lands. In order to achieve the objective described, different configurations for the MFC will be tested and adapted regarding to predominant plant species, soil pH, temperature, average humidity, organic matter and mineral salt composition. New electrode materials (combinations of polymers, metals, carbon) and surface treatments (i.e. doping with catalysts, new 2D materials, and functionalization with bacteria for on-demand activation) will be developed to improve their performance. Energy harvesting and storage will be established by considering low power harvesting technologies like tunnel FET and supercapacitors.</p> <p>DS8 aims at collecting all the experimental data gathered during these activities.</p>
NewSOC, supplementary information to WT2.3 "Development of doped lanthanum chromite based fuel electrodes", WT2.5 "Electrochemical characterization of single cells"
<p>These are experimental data related to CERTH participation in NewSOC project (874577) regarding WT2.3 “Development of doped lanthanum chromite based fuel electrodes”, WT2.5 “Electrochemical characterization of single cells”. The data set includes:</p> <ul> <li>physicochemical characterization (ICP, BET, XRD and SEM) of the powders and electrodes or cells produced (SEM)</li> <li>electrochemical characterization (iV characteristics, impedance, stability tests)</li> </ul> <p> </p> <p><strong>LSCrF0.1.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Fe<sub>0.1</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV, EIS and stability testing for button cells using different electrolyte substrates (formulation and thickness) and oxygen electrode materials operating under steam electrolysis, co-electrolysis of steam and carbon dioxide and reversible operation in steam or carbon dioxide cycle.</p> <p><strong>LSCrF0.5.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Fe<sub>0.5</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide. </p> <p><strong>LSCrNi0.1.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Ni<sub>0.1</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide. </p> <p><strong>LSCrNi0.5.rar:</strong> The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Ni<sub>0.5</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, and (B) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.</p> <p><strong>LSCrMn0.1.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Mn<sub>0.1</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide. </p> <p><strong>LSCrF0.05Ti0.05.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Fe<sub>0.05</sub>Ti<sub>0.05</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide.</p> <p><strong>LSCrF0.05V0.05.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Fe<sub>0.05</sub>V<sub>0.05</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide.</p> <p><strong>LSCrF0.25Ti0.25.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Fe<sub>0.25</sub>Ti<sub>0.25</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide. </p> <p><strong>LSCrF0.25V0.25.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Fe<sub>0.25</sub>V<sub>0.25</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.</p> <p><strong>Ni-GDC.rar</strong>: The zip folder contains data related to button cell stability testing using a commercial Ni-GDC fuel electrode material operating under steam electrolysis. </p> <p><strong>LARGE CELLS.rar</strong>: Data set for large cells (5x5 cm2) including iV, EIS and short-term stability testing employing Keracell III cell, Ni-GDC and LSCrF0.1 fuel electrodes operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.</p> <p> </p> <p> </p> <p> </p>
FIB-tomography data of Ni-YSZ anodes for Solid Oxide Fuel Cells (SOFC): Comparison of pristine and degraded materials (before/after redox cycling)
<p><em>Contents: </em></p> <p>This dataset contains 3D image stacks acquired with FIB-tomography from Ni-YSZ cermet anodes for Solid Oxide Fuel Cells (SOFC).</p> <p>The data was collected from three different Ni-YSZ anodes (fine-, medium- and coarse-grained). Each of these anodes was investigated first in pristine state (after sintering and reduction) and then also in degraded state (after exposure to 8 redox cycles).</p> <p>The 6 tomographs are then presented as stacks of 2D-tiff-images in 2 different versions: as gray-scale images (raw data) and as segmented images (Ni=white, YSZ=gray and pores=black). In total this gives 12 image stacks.</p> <p><strong>Further details</strong>, such as the voxel resolutions and image window sizes are listed in the downloadable excel file (<strong>2_3D_Data_Info.xlsx</strong>).</p> <p> </p> <p><em>Scientific Context: </em></p> <p>The microstructures of the cermet anodes were investigated for the purpose of optimizing the anode performance, which depends on effective transport properties (i.e. conductivity of ions in YSZ and of electrons in Ni, as well as diffusivity of fuel/gas in the pores). Furthermore the anode performance also depends on the catalytic/electrochemical activity (i.e. Ni-surface area and three phase boundary length TPBL). The microstructure characteristics have a strong influence on effective properties, electrochemical activity and associated anode performance. Furthermore, microstructure degradation (e.g. by Ni-coarsening) may lead to performance loss over time.</p> <p>Hence, the investigations focus on a fundamental, quentitative understanding of the relationships between microstructure characteristics and effective properties. The study reveals quantitative descriptions of all relevant microstructure characteristics (porosity, tortuosity, constrictivity, surface/interface areas, TPBL) and of the corresponding effective transport porperties (electric and ionic.conductivities). The corresponding anode performance was characterized by impedance spectroscopy.</p> <p>The quantitative <strong>results of the microstructure investigation were published</strong> in:</p> <p><strong>Pecho et al</strong> 2015a (doi:10.3390/ma8095265),</p> <p><strong>Pecho et al</strong> 2015b (doi:10.3390/ma8105370),</p> <p><strong>Holzer et al</strong> 2013 (doi: 10.1016/j.jpowsour.2013.05.047),</p> <p><strong>Holzer et al</strong> 2011a (doi: 10.1016/j.jpowsour.2010.08.017) and</p> <p><strong>Holzer et al</strong> 2011b (doi: 10.1016/j.jpowsour.2010.08.006).</p>
dataset figures - Assessing the Performance of Fuel Cell Electric Vehicles Using Synthetic Hydrogen Fuel - Article Energies
<p>Dataset for Table 1 - 2 and for Figure 4</p>
Dataset for the paper "High Loading of Single Atomic Iron Sites in Pyrolysed Fe-NC Oxygen Reduction Catalysts for Proton Exchange Membrane Fuel Cells", DOI:10.1038/s41929-022-00772-9
<p>The data in this spreadsheet was used to produce the figures in the paper </p> <p>Authors: Asad Mehmood, Mengjun Gong, Frédéric Jaouen, Aaron Roy, Andrea Zitolo, Anastassiya Khan, Moulay-Tahar Sougrati, Mathias Primbs, Alex Martinez Bonastre, Dash Fongalland, Goran Drazic, Peter Strasser, Anthony Kucernak</p> <p>Title: High Loading of Single Atomic Iron Sites in Pyrolysed Fe-NC Oxygen Reduction Catalysts for Proton Exchange Membrane Fuel Cells</p> <p>Journal: Nature Materials</p> <p>DOI: 10.1038/s41929-022-00772-9</p> <p>Please cite the above reference if you wish to use this data </p> <p> </p> <p>DOI of data: 10.5281/zenodo.6411262</p>
HAEOLUS Project Fuel Cell Data.
<p>Dataset from a Fuel Cell test in the HAEOLUS European Project <a href="https://haeolus.eu/" target="_blank" rel="noopener">https://haeolus.eu/.</a></p> <p> </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>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.