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Dataset results
19 results for “gas diffusivity”
Time series of methane and carbon dioxide diffusive fluxes using an Ultraportable Greenhouse Gas Analyzer (UGGA) for Falling Creek Reservoir and Beaverdam Reservoir in southwestern Virginia, USA during 2018-2025
Diffusive fluxes of methane and carbon dioxide were measured using an Ultraportable Greenhouse Gas Analyzer (UGGA) at the surface of Falling Creek Reservoir (FCR) and Beaverdam Reservoir (BVR; Vinton, Virginia, USA). FCR and BVR are owned and operated by the Western Virginia Water Authority as drinking water sources for Roanoke, Virginia. The dataset consists of calculated diffusive fluxes of methane and carbon dioxide measured at the deepest site of the reservoir adjacent to the dam (2018–2025) and additional reservoir upstream sites in FCR (2018, 2023) and BVR (2022). In 2025, two littoral sites were measured at the northernmost wetland inflow to FCR. Measurements were collected approximately fortnightly in FCR throughout the summer stratified periods of 2018–2021 and 2023-2025, while measurements from BVR were only taken in 2018 and 2022-2024.
Dataset of "Photoelectrochemical generation of H2O2 using hematite (α-Fe2O3) and gas diffusion electrode (GDE)"
<p>In contrast to the industrial-scale production of H2O2 the electrochemical or photoelectrochemical synthesis is environmentally friendly. In the present work, <br>the photoelectrochemical generation of H2O2 was studied by combining the hematite (α-Fe2O3/FTO/glass) photoanode and gas diffusion electrode (GDE) modified by <br>incorporation of tin (II) phthalocyanine (SnPc) in its hydrophilic layer. The experiments were carried out in a photoelectrochemical cell with two compartments <br>separated by a proton exchange membrane under applied bias and AM1.5 irradiation (100 mW/cm2). The generated amount of H2O2 was determined by chemical analysis <br>(visible light spectrophotometry) of the electrolyte. As a tool to determine the efficiency of such a process, the Faradaic efficiency (FE) was calculated. The <br>best configuration used air as an inlet gas for GDE and phosphate buffer (pH 6.4) as an electrolyte in the cathodic compartment. The combination of hematite and <br>GDE (with SnPc) was the most effective in H2O2 photoelectrochemical generation. The highest value of FE was 52.4 % for GDE (O2 reduction to H2O2) and 0.4 % for <br>hematite photoanode (H2O oxidation to H2O2).</p>
Raw data for the article "Visualisation and quantification of flooding phenomena in gas diffusion electrodes used for electrochemical CO2 reduction: A combined EDX/ICP–MS approach"
<p>Raw data for the article "Visualisation and quantification of flooding phenomena in gas diffusion electrodes used for electrochemical CO2 reduction: A combined EDX/ICP–MS approach", published in Journal of Catalysis 2022 408:1–8, doi: <a href="https://doi.org/10.1016/j.jcat.2022.02.014">10.1016/j.jcat.2022.02.014</a></p> <p>Folder names describe the type of data content.</p>
Dataset for publication "Enhancing C≥2 product selectivity in electrochemical CO2 reduction by controlling the microstructure of gas diffusion electrodes"
<p>Data used for publication:</p> <p>Broad topic: electrochemical reduction of CO2 using gas diffusion electrodes and neutral electrolyte</p> <p>Data is devided in subfolders named after the figure of the paper.</p> <p>Raw data, processed data, and Origin/Power Point files are all contained in the subfolders </p> <p>A subfolder corresponding to a sample contains: data from a potentiostat, gas and liquid chromatograms, recording of flow, pressure and temperature, tables of calculated Faradaic efficiency (FE), png image of the FE vs t, zipped raw files.</p> <p>.json file was created using a yadg scheme (https://dgbowl.github.io/yadg/master/index.html), and data was processed by a dgpost scheme (<a href="https://pypi.org/project/dgpost/">https://dgbowl.github.io/dgpost/master/index.html</a>)</p>
Dataset for publication "Importance of Substrate Pore Size and Wetting Behavior in Gas Diffusion Electrodes for CO2 Reduction"
<p>Dataset for the publication "Importance of Substrate Pore Size and Wetting Behavior in Gas Diffusion Electrodes for CO2 Reduction" containing war and processed data used to compose the various figures. </p> <p>DOI Publication: <a href="https://doi.org/10.1021/acsaem.2c03054">https://doi.org/10.1021/acsaem.2c03054</a> </p>
Raw data for the journal article "Cracks as efficient tools to mitigate flooding in gas diffusion electrodes used for the electrochemical reduction of carbon dioxide"
<p>This data set corresponds to the article by Kong et al. entitled "Cracks as efficient tools to mitigate flooding in gas diffusion electrodes used for the electrochemical reduction of carbon dioxide", published in Small Methods</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>
Tracer gas (SF6 and Xe) migration data collected in 2018 as a part of the Diffusion experiment
<p>The dataset contains the results of the gas sampling performed following two injections of a mixture of the tracer gases (SF<sub>6</sub> and Xe). Two tracer gas injections were conducted in 2018 in Carroll, New Hampshire. Tracer gas injections were performed beneath the water table in two chemical-explosion generated cavities to compare the migration of sulfur hexafluoride (SF<sub>6</sub>) and xenon (Xe) through an explosion-generated fracture network and to study the influence of ground water on gas transport. A mixture of tracer gases (50% of SF<sub>6</sub> and 50% of Xe) was injected into each cavity. The first gas injection took place on September 8, 2018 and gas sampling continued until September 20, 2018. The second injection was performed on October 31, 2018 and gas sampling continued until November 8, 2018. The data were collected using an automatic sampling system. The data analysis was performed by using a gas chromatograph (Shimadzu GC-8A) with a Thermal Conductivity Detector (TCD). The gas concentrations measured at the surface from 4 sampling locations are provided.</p> <p>In addition, we provide measurements of the barometric pressure and temperature recorded using an Onset HOBO pressure transducer placed in the vicinity of the injection site approximately 1 m above ground and collecting pressure and temperature samples every 15 minutes for the duration of the experiment. The pressure and temperature data is provided in Tables S2 and S4.</p> <p> </p>
Science ready spectra, their best-fitting models and results of Jeans axisymmetric modelling described in the research paper "Transforming gas-rich low-mass discy galaxies into ultra-diffuse galaxies by ram pressure" by Grishin, Chilingarian, Afanasiev et al.
<p>This package contains data presented in the paper "Transforming gas-rich low-mass discy galaxies into ultra-diffuse galaxies by ram pressure" by Grishin, Chilingarian, Afanasiev et al. (2021 Nature Astronomy in press). The dataset can be used to reproduce Figures 3 and 4 from the main manuscript and Extended Data Figures 1, 2, 4, 5 from the Supplementary Information.</p> <p>(1) Python scripts and data points required to reproduce Figure 4 in the manuscript and Extended Data Figure 5 from the Supplementary Information. The data and scripts are presented in a combined .zip archive for both figures.</p> <p>(2) One-dimensional spectra extracted within 1 half-light radius from long-slit Binospec spectra and multi-wavelength far-UV-to-near-IR broadband spectral energy distributions (SEDs) assembled from the photometric measurements extracted within the same aperture for 11 galaxies from the main sample (9 in the Coma cluster and 2 in the Abell 2147 cluster) and 5 galaxies from the supplementary (auxiliary) list. The spectra and SEDs are accompanied with their best-fitting stellar population models and parameters determined by the NBursts+phot algorithm: radial velocity, velocity dispersion, truncation age, final stellar metallicity. The templates are MILES-based models with self-consistent chemical evolution presented in Grishin et al. 2019 (https://ui.adsabs.harvard.edu/abs/2019arXiv190913460G/abstract). The filenames contain the coefficient for galactic winds and the mass fraction of stars in the final starburst, e.g. _l15_60 means lambda=1.5, SSP_frac=60 per cent. The files are presented as binary FITS tables with the fields annotated using unified content descriptors (UCDs) from the list established by the International Virtual Observatory Alliance and physical units where applicable.</p> <p>(3) Two-dimensional profiles of internal kinematics (radial velocity and velocity dispersion) and stellar population properties (truncation age and final stellar metallicity) derived from the analysis of long-slit Binospec spectra for 12 galaxies after adaptive binning, 11 from the main sample and GMP3016 in the Coma cluster from the supplementary sample; best-fitting Jeans axisymmetric models without adaptive binning, i.e. full profiles along the slit. The data are presented in binary FITS tables in the two FITS extensions, one for the profiles derived from the corresponding spectra and the second one for dynamical models.</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>
Pore network modeling as a new tool for determining gas diffusivity in peat
<p>The data and scripts are related to the manuscript “Pore network modeling as a new tool for determining gas diffusivity in peat” by Petri Kiuru, Marjo Palviainen, Arianna Marchionne, Tiia Grönholm, Maarit Raivonen, Lukas Kohl, and Annamari (Ari) Laurén submitted to Biogeosciences. The folder structure is similar to the one in the package “Peat macropore networks – new insights into episodic and hotspot methane emission” <a href="https://doi.org/10.5281/zenodo.6327112">https://doi.org/10.5281/zenodo.6327112</a>, and the remaining required data files can be found there.</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>
Influence of Temperature on Transcutaneous Blood Gas Diffusion: CAPNOS Project
ClinicalTrials.gov study NCT05637138. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of Gas Exchange by the Measurement of Lung Diffusion for Carbon Monoxide During General Anaesthesia
ClinicalTrials.gov study NCT01503879. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data_Use of Nanoscale Carbon Layers on Ag-Based Gas Diffusion Electrodes to Promote CO Production
<p>The folder contains the processed data of figures 3, 4, 5, 6, 8, S6 and S10 that appear in:</p> <p>L. Pacquets, J. Van den Hoek, D. Arenas-Esteban, R. Ciocarlan, P. Cool, K. Baert, T. Hauffman, N. Daems, S. Bals and T. Breugelmans, Use of Nanoscale Carbon Layers on Ag-Based Gas Diffusion Electrodes to Promote CO Production, ACS Applied Nano Materials, 2022, 5, 7723-7732.</p> <p><a href="https://doi.org/10.1021/acsanm.2c00473">https://doi.org/10.1021/acsanm.2c00473</a> </p>
Data_Influence of flow and pressure distribution inside a gas diffusion electrode on the performance of a flow-by CO2 electrolyzer
<p>The folder contains the processed data of figures 3, 4, 6, 7, 8, 10, S1 and S2 that appear in:</p> <p>Bert De Mot, Jonas Hereijgers, Miguel Duarte, Tom Breugelmans, Influence of flow and pressure distribution inside a gas diffusion electrode on the performance of a flow-by CO2 electrolyzer, Chemical Engineering Journal, Volume 378, 2019, 122224, ISSN 1385-8947, https://doi.org/10.1016/j.cej.2019.122224.</p>
Data_Electrochemical Reduction of CO2: Effect of Convective CO2 Supply in Gas Diffusion Electrodes
<p>The folder contains the processed data of figures 3, 4, 5 and 6 that appear in:</p> <p>M. Duarte, B. De Mot, J. Hereijgers, T. Breugelmans, Electrochemical Reduction of CO2: Effect of Convective CO2 Supply in Gas Diffusion Electrodes, ChemElectroChem. 6 (2019)</p> <p><a href="https://doi.org/10.1002/celc.201901454">https://doi.org/10.1002/celc.201901454</a></p>
Data_Size-controlled electrodeposition of Cu nanoparticles on gas diffusion electrodes in methanesulfonic acid solution
<p>The folder contains the processed data of figures 1, 2, 3, 4, 9, 10, S1, S2, S3, S7, S6 and S7 that appear in:</p> <p> </p> <p>Pacquets, L., Irtem, E., Neukermans, S. et al. Size-controlled electrodeposition of Cu nanoparticles on gas diffusion electrodes in methanesulfonic acid solution. J Appl Electrochem 51, 317–330 (2021)</p> <p>https://doi.org/10.1007/s10800-020-01474-5</p>
Steering Hydrocarbon Selectivity in CO2 Electroreduction over Soft-landed CuOx Nanoparticle-Functionalized Gas Diffusion Electrodes
<p>The folder contains the tabulated data of figures 3,4,5,6, S3, S12 and S13 in excel, as well as the edited figures in ppt and tiff format, as appeared in:</p> <p>Steering Hydrocarbon Selectivity in CO2 Electroreduction over Soft-landed CuOx Nanoparticle-Functionalized Gas Diffusion Electrodes. <em>ACS Applied Materials & Interfaces</em> 14 (2), 2691-2702.</p>
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