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132 results for “Cobalt”
Dataset of "Cobalt and nickel doped WSe2 as efficient electrocatalysts for water splitting and as cathodes in hydrogen evolution reaction PEM water electrolysis"
<p>Efficient electrocatalysts are crucial for water splitting and fuel cells. Using cheap alternatives that can improve reaction kinetics is essntial for advancing fuel cell technology. Although, tungsten diselinide (WSe2) is promising for electrocatalysis is not fully explored, especially in oxygen evolution and in applications such as polymer electrolyte membrane water electrolyzer.<br>In this work, we used a simple approach to dope WSe2 with cobalt and/or nickel atoms. The doped material was subsequently tested for hydrogen evolution reaction and oxygen evolution reaction. Accordingly, the two electrocatalysts are highly active and stable, affording low overpotentials comparable to those of noble metals. The effective introduction of heteroatoms causes the retention of coordination vacancies, furnishing active catalytic sites that enhanced electrocatalytic performance both in activity and charge transfer. Moreover, both doped materials show excellent performance and stability as cathode electrocatalysts in the polymer electrolyte membrane water electrolyzer with great promise for real-world applications.</p>
Cobalt-Mediated Photochemical C−H Arylation of Pyrroles
<p>Optimized geometries in xyz-format, supplement to the journal article published in <em>Angew. Chem. Int. Ed. </em><strong>2024</strong>, e202405780 (<a href="https://doi.org/10.1002/anie.202405780">https://doi.org/10.1002/anie.202405780</a>).</p>
Dataset of "Nickel-cobalt spinel-based oxygen evolution electrode for zinc-air flow battery"
<p>Following dataset provides all measured data that were collected on nickel (Ni) based electrodes for the oxygen evolution reaction. The electrodes were following: nickel (Ni) pristine mesh (PM), catalysed mesh (CM), nickel pristine foam (PF), catalysed foam (CF). Catalyst was NiCo2O4. Firstly, the catalysed electrodes were prepared and characterized by SEM, EDS and XRD. The electrodes were characterized in three different arrangements: in electrolysis non-flow arrangement, in a flow electrolysis cell and in ZAFB according to the manuscript.</p>
mom6 cobalt model result for oceanic carbon response to El Niños
<p>GEOS_Chem atmospheric transport model, monthly, 2.5 degree resolution in tropical Pacific Ocean (120-300E, 30N-30S)<br> 1. GEOS_Chem_tropical_pacific_monthly_clim_1992_2017.nc<br> 2. GEOS_Chem_tropical_pacific_monthly_iav_1992_2017.nc<br> 1 and 2 are GEOS_Chem atmospheric transport model results</p> <p>MOM6 COBALT model results<br> Note1: region range is 120-300E, 30N-30S with a resolution of half degree, monthly result from 1982.1.1 to 2018.1.1<br> Note2: if the file name has a label "_detrend_deseason", this file is detrended and deseasonized using full value in 1982-2018 with CDO<br> "cdo -ymonsub -detrend $fin -ymonmean -detrend $fin $fout"<br> Note3: ocean/sea surface is the first layer which is 1 meter deep<br> Note4: MLD_001_temp/salt/dic/alk/kd is the vertical mean value in the mixing layer depth (criterial of 0.01 kg/m3)</p> <p>MOM6_COBALT_tropical_pacific_monthly_dic_deltap_1982_2018_detrend_deseason.nc<br> (detrended and deseasonalized delta pCO2 (ocean pCO2 minus air pCO2) in the ocean surface)<br> MOM6_COBALT_tropical_pacific_monthly_dic_deltap_1982_2018.nc<br> (delta pCO2 (ocean pCO2 minus air pCO2) in the ocean surface)<br> MOM6_COBALT_tropical_pacific_monthly_dic_stf_1982_2018_detrend_deseason.nc<br> (detrended and deseasonalized air-sea CO2 flux, positive to ocean)<br> MOM6_COBALT_tropical_pacific_monthly_dic_stf_1982_2018.nc<br> (air-sea CO2 flux, positive to ocean)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_1982_2018.nc<br> (Mixing layer depth with a density criterial of 0.01 kg/m3)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_alk_1982_2018_detrend_deseason.nc<br> (first compute vertical mean alkilinity in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_alk_zgradient_1982_2018_detrend_deseason.nc<br> (first compute vertical mean alkilinity gradient (dalk/dz) in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_dic_1982_2018_detrend_deseason.nc<br> (first compute vertical mean dissolved inorganic carbon (DIC) in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_dic_zgradient_1982_2018_detrend_deseason.nc<br> (first compute vertical mean DIC (ddic/dz) in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_Kd_interface_1982_2018_detrend_deseason.nc<br> (first compute vertical mean Diapycnal diffusivity at interfaces layers (kd_interface) in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_salt_1982_2018_detrend_deseason.nc<br> (first compute vertical mean salinity in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_temp_1982_2018_detrend_deseason.nc<br> (first compute vertical mean temperature in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)</p> <p>MOM6_COBALT_tropical_pacific_monthly_MLD_001_u_1982_2018_detrend_deseason.nc<br> (first compute vertical mean velocity u in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br> MOM6_COBALT_tropical_pacific_monthly_MLD_001_v_1982_2018_detrend_deseason.nc<br> (first compute vertical mean velocity v in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)</p> <p>MOM6_COBALT_tropical_pacific_monthly_MLD_003_1982_2018.nc<br> (Mixing layer depth with a density criterial of 0.03 kg/m3)<br> MOM6_COBALT_tropical_pacific_monthly_pco2surf_1982_2018_detrend_deseason.nc<br> (detrended and deseasonalized sea surface pCO2 (ocean pCO2))</p> <p>MOM6_COBALT_tropical_pacific_monthly_pco2surf_1982_2018.nc<br> (sea surface pCO2 (ocean pCO2))<br> MOM6_COBALT_tropical_pacific_monthly_sfc_chl_1982_2018.nc<br> (sea surface chlorophyll)<br> MOM6_COBALT_tropical_pacific_monthly_sfc_dic_1982_2018.nc<br> (sea surface dissolved inorganic carbon (DIC))<br> MOM6_COBALT_tropical_pacific_monthly_sfc_no3_1982_2018.nc<br> (sea surface nitrate, NO3)<br> MOM6_COBALT_tropical_pacific_monthly_sfc_po4_1982_2018.nc<br> (sea surface phosphate, PO4)<br> MOM6_COBALT_tropical_pacific_monthly_SSS_1982_2018.nc<br> (sea surface salinity)<br> MOM6_COBALT_tropical_pacific_monthly_SST_1982_2018.nc<br> (sea surface temperature)<br> MOM6_COBALT_tropical_pacific_monthly_taux_1982_2018_detrend_deseason.nc<br> (detrended and deseasonalized wind stress in zonal direction)<br> MOM6_COBALT_tropical_pacific_monthly_taux_1982_2018.nc<br> (wind stress in zonal direction)<br> MOM6_COBALT_tropical_pacific_monthly_tauy_1982_2018_detrend_deseason.nc<br> (detrended and deseasonalized wind stress in meridional direction)<br> MOM6_COBALT_tropical_pacific_monthly_tauy_1982_2018.nc<br> (wind stress in meridional direction)<br> MOM6_COBALT_tropical_pacific_monthly_tc_depth_1982_2018.nc<br> (thermocline depth defined as depth where the temperature equals 20oC)</p> <p>JRA_rain_tropical_pacific_monthly_prrn_1982_2018_detrend_deseason.nc<br> (detrended and deseasonalized JRA rainfall)<br> </p> <p>Budget terms based MOM6 COBALT model results<br> Note1: region range is 120-300E, 30N-30S with a resolution of half degree, monthly result from 1982.1.1 to 2018.1.1<br> Note2: this is the vertical mean result in the mixing layer depth (criterial of 0.01 kg/m3) after detrend and deseasonalize</p> <p>MOM6_COBALT_tropical_pacific_monthly_MLD_001_pco2w_budget_1982_2018_detrend_deseason.nc<br> (budget terms used for ocean pCO2 budget analysis, vertical mean in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br> pco2_hadv_hdif: horizontal transport term, H_circ;<br> dpco2_hadvx: zonal advection term;<br> dpco2_hadvy: meridional advection term;<br> dpco2_hdif: horizontal diffusivity term;<br> dpco2_vadv_vdif: vertical transport term;<br> dpco2_dic_vdif_vdif: vertical transport term induced by DIC;<br> dpco2_alk_vdif: vertical transport term induced by Alk;<br> dpco2_bio: biological term<br> dpco2_rain: surface freshwater term<br> dpco2_sst: thermal term<br> dpco2_dt: pco2 response term<br> dpco2_flux: CO2 flux response term<br> </p>
Dataset of "Tracking high-valent surface iron species in the oxygen evolution reaction on cobalt iron (oxy)hydroxides"
<p>Dataset of the paper entitled "Tracking high-valent surface iron species in the oxygen evolution reaction on cobalt iron (oxy)hydroxides"</p>
Femtosecond electron diffraction data of iron and cobalt
<p>Femtosecond electron diffraction data of iron and cobalt measured at the Fritz Haber Institute in Berlin. The excitation wavelength was 2300 nm in all measurements. For iron, data were recorded with four different pump fluences. For cobalt, data were recorded with six different pump fluences. The samples were polycrystalline films with a thickness of 20 nm, sandwiched between two layers of silicon nitride with a thickness of 5 nm each. More information is available here: https://arxiv.org/abs/2110.00525</p>
Initial Conditions for ATOM-COBALT dynamic N:P model simulations in GBC paper
<p>Adjustment of standard initial conditions file for COBALT simulations to add dynamic phytoplankton P fields. </p>
Catalyst sites and active species in the early stages of MTO conversion over cobalt AlPO-18 followed by IR spectroscopy
<p>Supplementary material: Ex-situ DR-UV-visible spectroscopy, Ex-situ FT-IR Spectroscopy. In-situ FT-IR Spectroscopy, In continuo FT-IR Spectroscopy, Brønsted acidity of SAPO-18 </p>
Selective recovery of boron, cobalt, gallium and germanium from seawater solar saltworks brines using N-methylglucamine sorbents: Column operation performance
<p>The European Union (EU) identified a list of Critical Raw Materials (CRMs) crucial for its economy, aiming to find alternative sources. Seawater is a promising option as it contains almost all elements, although most at low concentrations. However, to the present, the CRMs' recovery from seawater is technically and economically unfeasible. Other alternatives to implement sea mining might be preferred, such as reverse osmosis brines or saltworks bitterns (after sodium chloride crystallisation). The CRMs' extraction in a selective way can be achieved using highly selective recovery processes, such as chelating sorbents. This study focuses on extracting Trace Elements (TEs) from solar saltworks brines, including boron, cobalt, gallium and germanium, using commercial N-methylglucamine sorbents (S108, CRB03, CRB05). The application of these sorbents has shown potential for boron recovery, but their selectivity for cobalt, gallium, and germanium requires further investigation. This research aims to assess these sorbents' kinetics and column mode performance for TEs recovery from synthetic bitterns. Boron and germanium were rapidly sorbed, reaching equilibrium (>90 %) within 1 h, except for S108, which took 2 h. In column mode, 20–25 pore volumes of bittern were treated to remove boron and germanium, but competition from other elements reduced treatment capacity. An acidic elution (1 M hydrochloric acid) allowed to elute them (>90 %), reaching concentration factors for germanium and boron of 35 and 11, respectively, while cobalt and gallium had less affinity for the sorbents. In addition, the experiments performed were fitted by a mass transfer model to determine the equilibrium constants and selectivities. Therefore, bittern mining has been proven as a secondary/alternative source to obtain CRMs, which can lead the EU to a position in which its dependence on other countries to obtain these raw materials would be decreased.</p>
Carbon-Substituted Amines of the Cobalt Bis(dicarbollide) Ion: Stereochemistry and Acid–Base Properties
<p>Analytical dataset for "Carbon-Substituted Amines of the Cobalt Bis(dicarbollide) Ion: Stereochemistry and Acid–Base Properties"</p>
Atomistic spin dynamics simulations of iron and cobalt
<p>Atomistic spin dynamics (ASD) simulations of ultrafast demagnetization in ferromagnetic iron and cobalt. The ASD simulations here are energy-conserving, which means that energy flow into and out of the spin system is considered.</p> <p>The dataset contains simulations at four different pump laser fluences for iron and six different fluences for cobalt. The excitation was assumed to be homogeneous throughout the simulated volume.</p> <p>The heat capacities and electron-phonon coupling parameters which were used in the ASD simulations are provided in the folder "heat capacities and G_ep".</p> <p>More information is available here:<br> - https://arxiv.org/abs/2110.00525<br> - Zahn et al. Phys. Rev. Research 3, 023032 (2021)<br> https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.3.023032</p> <p> </p>
Scenario data for article: Effects of the energy transition on environmental impacts of cobalt supply: A prospective Life Cycle Assessment study on future supply of cobalt
<p>This dataset contains the background data for the paper '<a href="https://onlinelibrary.wiley.com/doi/10.1111/jiec.13258">Effects of the energy transition on environmental impacts of the cobalt supply: A prospective Life Cycle Assessment study on the future cobalt supply</a>' as published in the Journal of Industrial Ecology.</p> <p><strong>Please note that an easier to use version of this data for LCA is available through the Premise (<a href="https://www.sciencedirect.com/science/article/pii/S136403212200226X">Sacchi et al. 2022</a>) Community Scenarios <a href="https://github.com/premise-community-scenarios/cobalt-perspective-2050">here</a>.</strong> This version is slightly adapted to fit into the Premise architecture and is compatible with ecoinvent v3.8 cutoff.</p> <p>This repository contains:</p> <ul> <li>Python code + readme to model the variables, generate presamples packages and generate LCA results based on those. (code folder)</li> <li>Input and output data for Variables 1-3 (files 1&2)</li> <li>Presamples excel sheets for each variable/scenario combination (file 3)</li> <li>Summarized LCA results (the full results can be generated through running the code provided) (file 4)</li> <li>Full LCA results used for the contribution analysis (file 5)</li> <li>Underlying data for each of the figures (file 6)</li> </ul> <p>We refer to the paper (linked above) for more information on the study.<br> </p> <p><strong>License: </strong>The metal supply scenario data is licensed under the CC-BY 4.0 license.</p> <p><strong>Access: </strong>Open access</p> <p> </p> <p>[Changelog]</p> <p>2023-03-23 - 1.3.1: Add link to Premise Community scenario page.<br> 2022-05-18 - 1.3.0: Fix minor error in data files '4 - LCA results' and '6 - Figure data' in demand amounts for total impacts.<br> 2022-04-06 - 1.2.1: Included link to article after publication<br> 2022-03-30 - 1.2.0: Included underlying figure data<br> 2022-01-24 - 1.1.1: Opened repository after paper acceptance<br> 2021-11-26 - 1.1.0: Update of code to comply with peer-review<br> 2021-07-12 - 1.0.0: Set-up of repository</p>
Supplementary material for "Development of novel carbon-free cobalt-free iron-based hardfacing alloys with a hard π-ferrosilicide phase"
<p>EBSD, EDS and XRD data for the manuscript "<a href="https://www.sciencedirect.com/science/article/pii/S2589152924001042"><span><span>Development of novel carbon-free cobalt-free iron-based hardfacing alloys with a hard π-ferrosilicide phase</span></span></a>"</p>
Experimental data related to the publication: "In-situ analysis of the effect of residual fcc phase and special grain boundaries on the deformation dynamics in pure cobalt"
<p>The article figures were produced solely from these data sets employing data processing methods described therein. For experimental conditions and naming conventions please refer to the paper.</p> <p><br>1. Deformation data files contained within "deformation_data.zip":</p> <p>The .zip archive contains five files related to five samples of thermally treated cobalt:<br>def_co600.csv<br>def_co800.csv<br>def_co1100.csv<br>def_co1100-10c.csv<br>def_co1100-20c.csv</p> <p>The data were recorded during compression of the above-listed samples at room temperature. </p> <p><br>2. Acoustic emission (AE) data files contained within "AE_data.zip":</p> <p>The .zip archive contains four files related to four samples of thermally treated cobalt:<br>AE_co600.wav<br>AE_co800.wav<br>AE_co1100.wav<br>AE_co1100-20c.wav</p> <p>The AE data were recorded in continuous mode ("data streaming" at 2 MHz) during compression of the above-listed samples at room temperature. </p> <p> </p> <p>3. Electron back-scatter diffraction (EBSD) data files contained within "EBSD_data.zip":</p> <p>The .zip archive contains fifty-three .osc files related to samples of as-drawn and thermally treated cobalt within four folders:<br>0c - as-drawn and annealed samples (i.e. without thermal cycling)<br>10c - annealed samples after thermal cycling of 10 cycles<br>20c - annealed samples after thermal cycling of 20 cycles<br>ex-situ_def - ex-situ EBSD during deformation of selected samples</p> <p>The .osc data files represent EBSD data after clean-up procedures described in detail in the manuscript.</p> <p> </p> <p> </p> <p> </p>
Research Data for the Journal Article: Insertion of CO2 to 2-methyl furoate promoted by a cobalt hypercrosslinked polymer catalyst to obtain a monomer of CO2-based biopolyesters
Open the record for dataset details and reuse information.
Global effects of deletion of the sdh genes, encoding succinate dehydrogenase, and of cobalt on protein abundance in stationary phase Salmonella enterica serovar Typhimurium.
<p>A common strategy that bacteria utilize to increase their survival under stressful conditions in their natural environments, including antibiotic treatment, is the entry into quiescence, a state of reversible cell growth arrest that offers protection against many environmental insults. Understanding quiescence is an important fundamental question, with relevance in the medical and environmental fields. Little is known about the molecular and physiological determinants that orchestrate survival during this temporary arrest of proliferation, or those that allow a rapid transition back to the proliferating state when conditions again become favorable. In the wide host-range pathogen <em>Salmonella enterica</em> serovar Typhimurium (S. Typhimurium) and other Gram-negative bacteria, this temporary arrest of proliferation induces the expression of the alternative sigma subunit of RNA polymerase, σS/RpoS, which remodels global gene expression to reshape the cell physiology and ensure survival under starvation and various stress conditions (<em>i.e</em>., the general stress response). One important aspect of persistence is the phenotypic differentiation of quiescent populations into sub-population(s) of "persisters" that survive in the presence of lethal concentrations of antibiotics. This phenomenon is worsening the worldwide antibiotic crisis, by causing therapy failure and chronic infections and potentially favoring the development of antibiotic resistance. Understanding mechanisms governing bacterial persisters is thus an important topic and a key issue for drug developments. However, despites many studies, the physiological and molecular mechanisms controlling the formation of persisters are poorly understood and controversial.</p> <p>We have recently discovered an unexpected functional interaction between σS and succinate dehydrogenase (Sdh) in the formation of persisters. Succinate dehydrogenase (Sdh), a membrane bound complex that connects the TCA cycle and respiratory chain, is one major target down regulated by σS (Levi-Meyrueis <em>et al</em>. 2014, 2015, Lago <em>et al.</em> 2017). Stationary-phase <em>Salmonella</em> grown in LB rich medium form persisters with a higher frequency than actively growing bacteria, after transfer to fresh LB medium in the presence of lethal concentrations of ampicillin and ciprofloxacin, but not significant effect of the Δ<em>rpoS</em> mutation on this phenomenon was observed. Surprisingly however, the Δ<em>rpoS</em> mutation suppressed the defect in persister formation of a Δ<em>sdh </em>mutant. It is very likely that the Δ<em>rpoS</em> mutation compensates for a metabolic perturbation provoked by the Δ<em>sdh </em>mutation, and key for persister formation.</p> <p>To get further insights into the synthetic rescue process involved in persisters formation, we used a mass spectrometry-based proteomics approach to compare the proteome of the wild-type, Δ<em>rpoS</em>, Δ<em>sdh</em> and Δ<em>sdh</em>Δ<em>rpoS</em> strains grown to late stationary phase in nutrient-rich LB medium. Cells were also grown in LB supplemented with cobalt to pinpoint major changes induced by cobalt on the <em>Salmonella</em> proteome. Indeed, the synthetic rescue process involved in persisters formation in the presence of ampicillin was abolished when the inoculum has been grown in the presence of a non-lethal dose of cobalt (100 μM).</p> <p><strong>Accession number</strong>.The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier <strong>PXD043726.</strong></p> <p><strong>See also:</strong></p> <p>NOREL, F., & MONTEIL, V. (2023). Unraveling a synthetic rescue process involved in persisters formation [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10277562</p> <p>Phégnon, L., Uttenweiler-Joseph, S., & Létisse, F. (2024). <span>Key physiological and metabolic characteristics for the differentiation of quiescent Salmonella's cells into persisters [Data set]. </span>Zenodo. <a href="https://doi.org/10.5281/zenodo.10885905" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10885905</a></p> <p><strong>This work was supported by the French National Research Agency (ANR-19-CE44-0005-01, PERIOMET project).</strong></p> <p><strong>References</strong></p> <p>Levi-Meyrueis C, Monteil V, Sismeiro O, Dillies MA, Monot M, Jagla B<em>, et al. </em>Expanding the RpoS/sigmaS-network by RNA sequencing and identification of sigmaS-controlled small RNAs in <em>Salmonella</em>. PloS one. 2014;9(5):e96918.</p> <p>Levi-Meyrueis C, Monteil V, Sismeiro O, Dillies M-A, Kolb A, Monot M <em>et al</em>. Repressor activity of the RpoS/sigmaS-dependent RNA polymerase requires DNA binding. Nucleic Acids Res 2015 43, 1456–1468.</p> <p>Lago M, Monteil V, Douche T, Guglielmini J, Criscuolo A, Maufrais C, <em>et al</em>. Proteome remodelling by the stress sigma factor RpoS/sigma(S) in <em>Salmonella</em>: identification of small proteins and evidence for post-transcriptional regulation. Scientific reports. 2017;7(1):2127.</p> <p> </p>
Why The Perfectly Symmetric Cobalt-Pentapyridyl Loses the H2 Production Challenge: Theoretical Insight into Reaction Mechanism and Reduction Free Energies
<p>Abstract</p> <p>Researchers have extensively investigated photo-catalytic water reduction utilizing Cobalt-based catalysts with poly-pyridyl ligands. While catalysts exhibiting distorted poly-pyridyl ligand demonstrate higher H2 production yields, those with ideal octahedral coordination display poor performance. This outcome suggests the crucial role of ligand framework in catalytic activity, yet reasons behind the disparity in H2 production rates for catalysts with octahedral geometries remain unclear. We theoretically examined the water reduction mechanism of Co-based poly-pyridyl catalyst, CoPy5, having perfect octahedral coordination. We clarified the effect of octahedral coordination by utilizing each intermediate step of ECEC mechanism. We determined spin states, solvent response, electronic structures, and reduction free energies. CoPy5 with perfect octahedral coordination, alongside its distorted counterparts, exhibit similar spin states as the reaction progresses through each intermediate step. However, the first reduction free energy obtained for the CoPy5 is slightly higher than that of its distorted counterparts. Following the second protonation, resulting H2 molecule experiences limited diffusion from the Co center due to the compact structure of the CoPy5, which blocks the Co center for the next H2 production cycle. Catalysts having distorted octahedral geometries facilitate fast removal of H2 into the solvent. Thus, the reaction center becomes immediately available for subsequent H2 production.</p> <p>Computational Details</p> <p>AIMD simulations have been performed for modeling intermediate states of the ECEC mechanisms of H2 production through water splitting. Open source CP2K simulation package have been used in all simulations. PBE density functional in general gradient approximation (GGA) formalism was employed for the AIMD simulations. Goedecker-Teter-Hutter (GTH) potentials were applied for the estimation of core electron interactions with the valence shell and nucleus. Valence electrons were modeled explicitly and valence shells of Co, N, C, O and H contain 17, 5, 4, 6 and 1 electrons, respectively. DZVP-MOLOPT basis set was used for all atomic kinds. For auxiliary plane wave basis set, a cutoff of 400 Ry was utilized. Dispersion interactions were taken into consideration by applying Vydrov and Van Voorhis vdW density functional, in the revised form (rVV10). Periodic boundary<br> conditions and spin polarization were always applied. For the CoPy5 complex, AIMD simulations were carried out in a box defined as cubic with explicit water environment. The CoPy5 catalyst was first solvated in 215 water molecules and the simulation volume was relaxed by performing AIMD simulations for approximately 20 ps in the isothermal-isobaric ensemble (NPT). Cubic simulation box volume was determined as 6163.28 ̊A3. Following the determination of the simulation box size, each intermediate step were modeled by applying AIMD simulations in the canonical ensemble (NVT) for approximately 20 ps. Time step was set to 0.5 fs. Canonical sampling through velocity rescaling (CSVR) thermostat with a time constant of 100 fs was applied in order to keep<br> the simulation temperature at 300 K.</p> <p>Please see the corresponding article for more details.</p>
1/8˚ resolution MOM6-COBALT physical and biogeochemical diagnostics for the Gulf of Mexico, monthly means between 2008-2018
<p>The files in this dataset contain monthly mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2008-2018 for the region between 18-31˚N, 98-80˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, https://github.com/NOAA-GFDL/MOM6 ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at https://rda.ucar.edu/datasets/ds551.0/. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021).</p> <p><br> References:</p> <p><br> Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726</p> <p><br> Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791</p> <p><br> Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687</p> <p><br> Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097</p> <p><br> Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.</p> <p><br> Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043</p> <p> </p>
Fives Input dataset (Cobalt & Darshan traces, combined and preprocessed)
<p>Dataset made of aggregated and curated Cobalt and Darshan logs from the Theta HPC platform at ALCF.</p> <p>Cobalt and Darshan logs were obtained from ALCF Public Data repository (https://reports.alcf.anl.gov/data/index.html) and cover the year 2022. This data was generated from resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. In order to use the scripts contained within this archive, these datasets must be downloaded and placed in the directory '2022' at the root of the extracted archive.</p> <p>The Darshan logs used in this datasets are originillay available in an aggregated form. The levels of details are usually the following : </p> <ul> <li>job (reservation made to a resource manager for some platform resources)</li> <li>application run (application running inside the job, on the reserved resources ; there may be multiple ones, sequentially or in parallel, during a job's execution)</li> <li>I/O operation (read or write registered to a file from a process of an application)</li> </ul> <p>Darshan CSV files for Theta contain job and application runs informations, but individual I/O of each application run is aggregated into a single entry.</p> <p>This resource is organised as a single archive containing:</p> <ul> <li>YAML files with our datasets, at various granularity levels (in 'preprocessed_datastets' directory): <ul> <li>48 files containing each<strong> 1 month worth of job traces</strong> for one of <strong>3 job classes</strong> (4 files per month, one per job class and one with all job classes) </li> <li>4 files containing each the entire year worth of job traces ; 1 file per job class, 1 file with all job classes.</li> </ul> </li> <li>A Jupyter Lab notebook, which contains the necessary routines to create aformentionned datasets from raw logs files from ALCF, for the Theta system</li> <li>A requirements.txt file, describing required Python packages and their versions.</li> <li>Various empty directories meant to receive outputs from the Jupyter notebook.</li> </ul>
Heating curves of catalytic probe with cobalt tip and varying thicknesses of carbon nanowall deposition in oxygen plasma
<p>Heating curves measured while exposing catalytic probe to oxygen plasma. The tip of the probe was a cobalt disk, which was thoroughly oxidized before use. Varying deposition times of carbon nanowalls were used to achieve different thicknesses of the carbon nanowall layer, which altered the heating curve.</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.