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Dataset results
433 results for “FE”
The role of dynamics in heterogeneous catalysis: surface diffusivity and N2 decomposition on Fe(111)
<p>Data related to the molecular dynamics simulations reported in the manuscript "The role of dynamics in heterogeneous catalysis: surface diffusivity and N2 decomposition on Fe(111)"</p><p>- Inputs of the MD simulations of surface morphology and dynamics (LAMMPS)</p><p>- Inputs of the OPES simulations for N2 adsorption and dissociation (LAMMPS+PLUMED)</p><p>- MD outputs: trajectory files</p><p>- Code for analysis and post-processed data</p><p>- Jupyter notebook to reproduce the pictures reported in the manuscript</p>
Large-scale Comparison of Fe and Ru Polyolefin C–H Activation Catalysts
<p>We performed a large-scale density functional theory comparison of polyolefin C–H hydroxylation trends across over 200 Fe and Ru catalysts that are identical except for their metal centers for the radical-rebound conversion of propane to propanol. </p><p>This ZIP contains optimized structures of all reactive intermediates of the Fe and Ru catalysts in the final dataset; approximate transition state structures from the calculated reaction coordinates; raw electronic energies and reaction energies for all Fe and Ru catalysts in the final dataset; electronic properties of all intermediates of the Fe and Ru catalysts in the final dataset; Fe and Ru catalysts that were discarded during DFT (ZIP)</p>
Artesania Santa Fe de Antioquia V.2
Artesania (Souvenir) de visita a Santa Fe de Antioquia Colombia, VERSION 2 con nuevas tomas, nuevo Pipeline Mejorado (Workflow 2.1), optimizando tiempo, procesos y calidad. Primera pieza de la serie UHD, 150 imagenes procesado en RC y postprocesado en el ProyectoSCAN MiniLab. Version 1 del modelo para comparacion: https://skfb.ly/6ZOE8 Musica autoctona de la region: "Santa Fe de Antioquia", Trío Vino Blanco - Héctor Ochoa https://www.amazon.com/-/es/Trio-Vino-Blanco/dp/B000002FY3 Souvenir from Santa Fe de Antioquia Colombia, Second Version with new shots (150), new pipeline 2.1, less time, high quality and details, fist scan on the UHD series, processed on RC and postprocesed an tha ProyectoSCAN Minilab. ProyectoSCAN Photogrammetry! Source: Objaverse 1.0 / Sketchfab
Datasets for Insights into prismatic loop formation in irradiated Fe-Cr alloys from hypothesis-driven active learning and causal analysis
<p>Datasets for irradiated Fe-Cr alloys are collected from the experimental reports on dislocation loop type and dislocation density. We have constructed a data set from experimental literature containing 182 data points. To address such challenges to predict dislocation density, we have implemented a three-step ML approach as listed in the following:</p> <div> <div> <div> <ul> <li> <p>impute dataset to fill in the missing data to construct a predictive model using the RF regression algorithm. </p> </li> <li> <p>generate functionalized features and evaluate feature importance using the predictive model</p> </li> <li> <p>use the physics-based important functionalized features as hypotheses (physics-augmented GP models) in a hypothesis-driven active learning scheme to learn and predict dislocation density for all alloys. </p> </li> </ul> </div> </div> </div>
Data and Codes for Experimentally Validated Inverse design of Multi Property Fe-Co-Ni alloys: Data and codes release v1.0.1
<p>Data and Codes for Experimentally Validated Inverse design of Multi-Property Fe-Co-Ni alloys</p>
NI FE LATERIZATION TREND AND NI LATERITE PROSPECT AREA DETERMINATION ON LATERITE DEPOSITS IN LASOLO KEPULAUAN DISTRICT, NORTH KONAWE REGENCY, SOUTHEAST SULAWESI
<p>XRF Datas obtained from laterite from Lasolo Kepulauan District, North Konawe, Southeast Sulawesi, Indonesia</p>
Data from the paper "Porphyrin central metal ion driven self-assembling in heterogeneous ZnTPP – CoTPP films grown on Fe(001)-p(1 × 1)O"
Open the record for dataset details and reuse information.
Fe-C-N melting tempreature
<p>Melting data obtained with the resistance jump criterion.</p>
Chemical reaction between ferropericlase (Mg,Fe)O and water under high pressure-temperature conditions of the deep lower mantle
<p>The XRD datasets and the multigrain dataset for the article "Chemical reaction between ferropericlase (Mg,Fe)O and water under high pressure-temperature conditions of the deep lower mantle" by Yang et al.</p>
Cation non-stoichiometry in Fe:SrTiO3 thin films and its effect on the electrical conductivity
<p>This dataset contains raw data and figures used in the publication: <a href="https://doi.org/10.1039/D1NA00358E">https://doi.org/10.1039/D1NA00358E</a></p>
Digitizing Los Millares (Santa Fe de Mondujar, Almería, Spain) through geospatial technologies: preserving and disseminating the archaeological heritage
<p>Data originated from the research project "Digitizing Los Millares (Santa Fe de Mondujar, Almería, Spain) through geospatial technologies: preserving and disseminating the archaeological heritage"</p>
Surface Ocean Biogeochemistry Regulates the Impact of Anthropogenic Aerosol Fe Deposition on the Cycling of Iron and Iron Isotopes in the North Pacific
<p>Monthly-average (year 2014) netcdf output files of NEMO/PISCES Fe isotope model experiments on the ORCA2 grid for experiments with updated iron deposition fields; "ptrc" files contain model outputs for heavy and light iron tracers, "diad" files contain diagnostic model outputs for iron uptake (of light and heavy iron), primary production (for diatoms and nanophytoplankton), and iron deposition fluxes (from dust, anthropogenic, and fire sources).</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>
Melting Experiments on Fe-O-H and Fe-H: Evidence for Eutectic Melting in Fe-FeH and Implications for Hydrogen in the Core
<p>Tables S1 and S2 show data of the melting experiments on the Fe-O-H ternary and Fe-H binary systems, respectively. Dataset S1 reproduces the rainbow-colored areas in Figures 4a–d.</p>
Dataset for: Identification of genomic regions of wheat associated with grain Fe and Zn content under drought and heat stress using genome-wide association study
<p>The study material in the GWAS panel with 282 advanced breeding lines of bread wheat genotypes from IARI stress breeding program was selected to map the genomic regions responsible for grain iron and Zinc content under drought and heat stress treatments.</p> <p>Phenotypic data:</p> <p>The GWAS panel was evaluated at IARI, New Delhi - DL (28.6550° N, 77.1888° E, MSL 228.61 m) under Irrigated (IR), Restricted Irrigated (RI) and Late sown (LS) treatment conditions with augmented RCBD design. Data was collected on Grain Iron and Grain zinc content along with thousand-grain weight. Around 20 g of grain sample from each of 282 genotypes from the GWAS panel under all three conditions were used for phenotyping GFeC and GZnC through high-throughput Energy Dispersive X-ray Fluorescence (ED-XRF) machine (model X-Supreme 8000; Oxford Instruments plc, Abingdon, United Kingdom) calibrated with glass beads-based values. To record TGW, manual counting of grains was followed and the weight of the grains was recorded in grams with an electronic balance.</p> <p>Genotypic data:</p> <p>Genomic DNA of the GWAS panel was extracted from the leaves of seedlings by Cetyl Trimethyl Ammonium Bromide (CTAB) method. The panel was genotyped using Axiom Wheat Breeder's Genotyping Array (Affymetrix, Santa Clara, CA, United States) having 35,143 genome-wide SNPs. The monomorphic, markers with minor allele frequency (MAF) of <5%, missing data of >20%, and heterozygote frequency >25% were removed from the analysis. The remaining set of 10546 high-quality SNPs was used in GWAS analysis.</p>
Modelling Amorphization and Dissolution of Zr(Fe,Cr)2 Secondary Phase Precipitates in Zircaloys
<p>Data and accompanying paper "Modelling Amorphization and Dissolution of Zr(Fe,Cr)2 Secondary Phase Precipitates in Zircaloys" J. D. Robson, Journal of Nuclear Materials</p>
STEM Data ANP-6 Ion_Irradiated_Fe_5MeV_1.0_dpa_Loops
<p>STEM data on the RPV weld ANP-6 after ion irradiation with 5MeV Fe ions to 1.0dpa at 500nm</p> <p>for the ENTENTE Database</p>
STEM Data ANP-6 Ion_Irradiated_Fe_5MeV_0.1_dpa_Loops
<p><span><span>STEM data on the RPV weld ANP-6 after ion irradiation with 5MeV Fe ions to 0.1dpa at 500nm for the ENTENTE Database</span></span></p>
STEM Data ANP-10 Ion_Irradiated_Fe_5MeV_0.1_dpa_Loops
<p><span><span>STEM data on the RPV steel ANP-10 after ion irradiation with 5MeV Fe ions to 0.1dpa at 500nm for the ENTENTE Database</span></span></p>
STEM Data ANP-10 Ion_Irradiated_Fe_5MeV_1.0_dpa_Loops
<p><span><span>STEM data on the RPV steel ANP-10 after ion irradiation with 5MeV Fe ions to 1.0dpa at 500nm for the ENTENTE Database</span></span></p>
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Allen Brain Atlas
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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.