Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
26
datasets available to search
ShareScore release 0.9.0
Dataset results
26 results for “Kinetics mechanism”
Kinetic Insights into Glycerol Electrooxidation on Nickel: Current-Dependent Product Distribution and Reaction Mechanism
<p>## FILE DESCRIPTION<br>--------------<br>### Figure 1<br>- Fig1a.txt : Cyclic voltammetry of a Ni-based electrode in 0.1 M LiOH and 50 mM glycerol, measured at 5 mV s^-1. <br>- Fig1b.txt : IS spectra obtained at 1.50 V vs RHE in 0.1 M LiOH and 0.1 M LiOH + 50 mM glycerol.<br>- Fig1c.txt : Chronopotentiometric curves at 1 mA cm^-2, 3 mA cm^-2, 5 mA cm^-2 during 2 hours in 0.1 M LiOH + 50 mM glycerol.</p> <p>### Figure 2<br>- Fig2a.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 1 mA cm^-2.<br>- Fig2b.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 3 mA cm^-2.<br>- Fig2c.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 5 mA cm^-2.<br>- Fig2d.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 10 mA cm^-2.<br>- Fig2e.txt : Concentration of reaction products vs. time plots during glycerol oxidation (50 mM) in 0.1 M LiOH at 1 mA cm^-2.<br>- Fig2f.txt : Concentration of reaction products vs. time plots during glycerol oxidation (50 mM) in 0.1 M LiOH at 3 mA cm^-2.<br>- Fig2g.txt : Concentration of reaction products vs. time plots during glycerol oxidation (50 mM) in 0.1 M LiOH at 5 mA cm^-2.<br>- Fig2h.txt : Concentration of reaction products vs. time plots during glycerol oxidation (50 mM) in 0.1 M LiOH at 10 mA cm^-2.</p> <p>### Figure 3<br>- Fig3a.txt : Rate constant comparison at varying current densities applied for the formation of formate, glycolate, glycerate, tartronate and oxalate with its error bar.</p> <p>### Figure 4<br>- Fig4a.txt : Differential optical density (m∆O.D) taken at the maximum absorption peak as a function of potential applied in a solution of 0.1 M LiOH and LiOH 0.1 M + 50 mM glycerol in different regions (capacitive, NiOOH formation and GEOR and OER).<br>- Fig4b.txt : Rate law plot for glycerol and LiOH considering current density as a function of the normalized differential absorption (m∆O.D).</p> <p>### Figure S3<br>- FigS3.txt : X-ray diffraction (XRD) analysis </p> <p><br>### Figure S4<br>- FigS4a.txt : Cyclic Voltammetries in different electrolytes.</p> <p>### Figure S5<br>- FigS5a.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 1.53 V vs RHE.<br>- FigS5b.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 1.62 V vs RHE.<br>- FigS5c.txt : Faradaic Efficiencies for Glycerol oxidation electrolysis at 1.78 V vs RHE.</p> <p>### Figure S6<br>- FigS6a.txt : pH measurement near to the surface of the electrode and in the bulk of the solution every five minutes at 1 mA cm^-2.<br>- FigS6b.txt : pH measurement near to the surface of the electrode and in the bulk of the solution every five minutes at 3 mA cm^-2.<br>- FigS6c.txt : pH measurement near to the surface of the electrode and in the bulk of the solution every five minutes at 5 mA cm^-2.</p> <p>### Figure S7<br>- FigS7a.txt : UV-Vis absorbance spectra as a function of applied potentials in 0.1 M LiOH.<br>- FigS7b.txt : Chronoamperometry measurement without glycerol.<br>- FigS7c.txt : UV-Vis absorbance spectra as a function of applied potentials in 0.1 M LiOH + 50 mM glycerol.<br>- FigS8d.txt : Chronoamperometry measurement with glycerol.</p> <p>### Figure S8<br>- FigS8a.txt : Differential UV-Vis spectra of pre-catalytic (species formed in capacitive and NiOOH formation region) in 0.1 M LiOH.<br>- FigS8b.txt : Differential UV-Vis spectra of catalytic species (formed in OER and GEOR region) in 0.1 M LiOH.<br>- FigS8c.txt : Differential UV-Vis spectra of pre-catalytic species in 0.1 M LiOH + 50 mM glycerol. <br>- FigS8d.txt : Differential UV-Vis spectra of catalytic species in 0.1 M LiOH + 50 mM glycerol.<br>- FigS8e.txt : Steady state J-V curve with the onset for OER (Oxygen Evolution Reaction) and GEOR (Glycerol Electrooxidation Reaction) indicated.</p> <p>### Figure S9<br>- FigS9.txt : Rate law plot for glycerol and LiOH considering current density (j) as a function of the normalized differential absorption (m∆O.D).</p>
Supporting Information for Accelerating Combustion Mechanism Discovery with Automated Uncertainty, Sensitivity, Thermodynamics, and Kinetics Calculations
<p>Supplementary material to accompany the manuscript "Accelerating Combustion Mechanism Discovery with Automated Uncertainty, Sensitivity, Thermodynamics, and Kinetics Calculations" by Sevy Harris and Richard H West.</p> <ul> <li>The software (mostly Python scripts) is in autoscience_workflow.zip. </li> <li>DFT results (Gaussian log files, Arkane input files, Arkane output files) for all species and reactions are in dft.zip</li> <li>RMG-built detailed kinetic models are in mechanisms.zip </li> <li>Additional plots and results (as described in the manuscript) are in supporting_information.pdf</li> </ul>
Kinetics and mechanisms of acid-pH weathering of pyroxenes
<p>Weathering of primary silicate minerals under acidic conditions occurs in contexts as varied as acid mine drainage, volcanic environments, soils, stone monuments subjected to acid rain or Geological Carbon Storage (GCS). Considering the abundance of pyroxenes on the Earth crust, knowledge of their weathering kinetics and mechanisms may help to optimize carbonate yield in GCS. Here we report experimental results from the reaction of the clinopyroxenes augite and diopside in acidic solutions. Dissolution at far-from-equilibrium conditions results in the formation of etch pits where crack initiate and propagate by stress corrosion and pressure exerted by swelling of an amorphous, gel-like Si-rich phase, which precipitates despite the undersaturation of the bulk solution and whose formation is highly controlled by the heterogeneity of the mineral surface and the local transport mechanism. These precipitates are commonly localized within deep etch pits and cracks, characterized by a low fluid renewal where high Si-concentrations can be reached locally, so that supersaturation with respect to amorphous silica can occur. Cracks and silica precipitates are most abundant in the case of augite weathered in flow-through experiments. This is related to its faster reaction rate compared to diopside, most likely due to its higher iron content. Finally, in the case of diopside an amorphous magnesium silicate hydrate (M-S-H) precursor forms, which represents an indirect evidence of the high pH conditions prevailing at the diopside-solution interface during dissolution.</p>
Data for Automatic Mechanism Generation Involving Kinetics of Surface Reactions with Bidentate Adsorbates
<p>Data and scripts for the preprint "Automatic Mechanism Generation Involving Kinetics of Surface Reactions with Bidentate Adsorbates".</p>
Development of predictive models of the kinetics of a hydrogen abstraction reaction combining quantum-mechanical calculations and experimental data
<p>The files contain the electronic structure calculations for all the levels of theory tested in this work.</p>
Atmospheric hydroxyl distribution from the EMAC model (MOM kinetic chemistry mechanism)
<p>This dataset contains the output from the simulations with the EMAC model implementing the MOM kinetic chemistry mechanism presented in <a href="https://doi.org/10.5194/acp-16-12477-2016">Lelieveld et al. (2016)</a> study. In addition to the computed atmospheric hydroxyl (OH) and hydroperoxyl (HO2) radicals abundance distributions, we add related model fields facilitating usage/comparison of these results with other estimates.</p><p>The data containers format is netCDF v.4 (compressed); please refer to the container variables/attributes for the extended information. We present here the actual model output (weekly averages for the 2013−2014 period, in EMAC-MOM__*.nc) and the monthly "climatology" fields (average, SD, minima and maxima of the time steps falling in particular month, in EMAC-MOM__*--clim.nc, respectively).</p><p>See the .README.pdf file for additional notes.</p><p>Changes w.r.t. initial version from 2020/09/22:</p><p>2020/10/30: Updated attributes and DOIs in .nc/.jnl files, added OH "climatology", updated README.</p><p>2020/10/31: Updated description and "climatology" (SD fields were missing).</p><p>2022/06/19: Added hydroperoxyl (HO2) fields, updated species average concentration plot sample script.</p><p>2023/10/26: Dataset title adjusted for clarity</p>
Fig. 2 in The hydroperoxyl radical scavenging activity of natural hydroxybenzoic acids in oil and aqueous environments: Insights into the mechanism and kinetics
Fig. 2. The optimized structures of TS of the HOO• + HBA reactions following the FHT mechanism in pentyl ethanoate.
Fig. 4 in The hydroperoxyl radical scavenging activity of natural hydroxybenzoic acids in oil and aqueous environments: Insights into the mechanism and kinetics
Fig. 4. Calculated log(koverall) at 298.15 K, in the reactions of the HBA with HOO• in water following pH values.
Fig. 3 in Modeling the peroxyl radical scavenging behavior of Carnosic acid: Mechanism, kinetics, and effects of physiological environments
Fig. 3. Deprotonated forms of CA under the physiological aqueous environment. The proton affinity (PA) values are in kcal/mol.
Fig. 6 in Modeling the peroxyl radical scavenging behavior of Carnosic acid: Mechanism, kinetics, and effects of physiological environments
Fig. 6. Optimized structures of the TSs of CA + HOO• reaction in physiological environments (W = water and PE = pentyl ethanoate). Distances are in Aand angles in ◦.
Fig. 2 in Modeling the peroxyl radical scavenging behavior of Carnosic acid: Mechanism, kinetics, and effects of physiological environments
Fig. 2. The stable conformation, HOMO, LUMO, and ESP of CA calculated at M06–2X/6–311++ G(d,p) level.
Fig. 4 in Modeling the peroxyl radical scavenging behavior of Carnosic acid: Mechanism, kinetics, and effects of physiological environments
Fig. 4. Computed BDE values in kcal/mol of CA in the gas phase (G) and pentyl ethanoate (PE) as well as of CA– in water (W).
Fig. 3 in The hydroperoxyl and superoxide anion radical scavenging activity of anthocyanidins in physiological environments: Theoretical insights into mechanisms and kinetics
Fig. 3. Regeneration cycle of the hydroperoxyl and superoxide radical scavenging of anthocyanidins following the SET mechanism in aqueous solution.
Fig. 2 in The hydroperoxyl and superoxide anion radical scavenging activity of anthocyanidins in physiological environments: Theoretical insights into mechanisms and kinetics
Fig. 2. Optimized geometries of TSs following the FHT mechanism between the selected compounds and HOO• radicals (P: pentyl ethanoate).
Kinetics of Nasal Cytokine Responses to Mechanical Stimulation
ClinicalTrials.gov study NCT04878237. IPD Sharing: NO. Countries: 1. Publications: 7.
Fig. 3 in The hydroperoxyl radical scavenging activity of natural hydroxybenzoic acids in oil and aqueous environments: Insights into the mechanism and kinetics
Fig. 3. The selected mechanisms of the HOO• + HBA reactions in water.
Fig. 1 in The hydroperoxyl radical scavenging activity of natural hydroxybenzoic acids in oil and aqueous environments: Insights into the mechanism and kinetics
Fig. 1. Structures of hydroxybenzoic acid derivatives (HBA).
Fig. 5 in Modeling the peroxyl radical scavenging behavior of Carnosic acid: Mechanism, kinetics, and effects of physiological environments
Fig. 5. ΔG values in kcal/mol of CA + HOO• reaction in the gas phase, pentyl ethanoate, and water.
Fig. 1 in Modeling the peroxyl radical scavenging behavior of Carnosic acid: Mechanism, kinetics, and effects of physiological environments
Fig. 1. Molecular structure of Carnosic acid (CA).
Fig. 1 in The hydroperoxyl and superoxide anion radical scavenging activity of anthocyanidins in physiological environments: Theoretical insights into mechanisms and kinetics
Fig. 1. Structures of the 12 anthocyanidins studied in this work.
ScienceDex guides
Understand access before you commit
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.