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83 results for “Kinetic modeling”

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zenodo40/100

Supplemental data of publication "Reactive Transport Model of Kinetically Controlled Celestite to Barite Replacement".

<p>Supplemental data of publication &quot;Reactive Transport Model of Kinetically Controlled Celestite to Barite Replacement&quot;.</p> <p>Authors: Morgan Tranter, Maria Wetzel, Marco De Lucia, Michael K&uuml;hn</p> <p>Contact: mtranter@gfz-potsdam.de</p> <p>Submitted to Advances in Geosciences (31.06.2021).<br> Special Issue: European Geosciences Union General Assembly 2021, EGU Division Energy, Resources &amp; Environment (ERE)</p> <p>EGU21 Abstract:<br> https://doi.org/10.5194/egusphere-egu21-9832</p> <p>Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)</p>

opencc-by-4.0Jun 2021View details →
zenodo40/100

Data from: Fluid-kinetic model of a propulsive magnetic nozzle

<p>#&nbsp;Data&nbsp;from:&nbsp;Fluid-kinetic&nbsp;model&nbsp;of&nbsp;a&nbsp;propulsive&nbsp;magnetic&nbsp;nozzle</p> <p>&nbsp;</p> <p>-&nbsp;Authors:&nbsp;Mario&nbsp;Merino,&nbsp;Judit&nbsp;Nuez,&nbsp;Eduardo&nbsp;Ahedo</p> <p>-&nbsp;Contact&nbsp;email:&nbsp;mario.merino@uc3m.es</p> <p>-&nbsp;Date:&nbsp;2021-10-08</p> <p>-&nbsp;Keywords:&nbsp;magnetic&nbsp;nozzle,&nbsp;plasma&nbsp;propulsion,&nbsp;electrodeless&nbsp;plasma&nbsp;thrusters,&nbsp;kinetic&nbsp;model,&nbsp;collisionless&nbsp;electron&nbsp;cooling,&nbsp;magnetic&nbsp;thrust</p> <p>-&nbsp;Version:&nbsp;1.0.0</p> <p>-&nbsp;Digital&nbsp;Object&nbsp;Identifier&nbsp;(DOI):&nbsp;10.5281/zenodo.5557592</p> <p>-&nbsp;License:&nbsp;This&nbsp;dataset&nbsp;is&nbsp;made&nbsp;available&nbsp;under&nbsp;the&nbsp;[Open&nbsp;Data&nbsp;Commons&nbsp;Attribution&nbsp;License](http://opendatacommons.org/licenses/by/1.0/)</p> <p>&nbsp;</p> <p>##&nbsp;Abstract</p> <p>&nbsp;</p> <p>This&nbsp;dataset&nbsp;contains&nbsp;the&nbsp;magnetic&nbsp;nozzle&nbsp;fluid-kinetic&nbsp;simulation&nbsp;results&nbsp;used&nbsp;to&nbsp;prepare:</p> <p>&nbsp;</p> <p>_[Mario&nbsp;Merino,&nbsp;Judit&nbsp;Nuez,&nbsp;Eduardo&nbsp;Ahedo,&nbsp;&quot;Fluid-kinetic&nbsp;model&nbsp;of&nbsp;a&nbsp;propulsive&nbsp;magnetic&nbsp;nozzle&quot;,&nbsp;Plasma&nbsp;Sources&nbsp;Science&nbsp;and&nbsp;Technology](https://doi.org/10.1088/1361-6595/ac2a0b)._</p> <p>&nbsp;</p> <p>##&nbsp;Dataset&nbsp;description</p> <p>&nbsp;</p> <p>The&nbsp;simulations&nbsp;have&nbsp;been&nbsp;prepared&nbsp;combining&nbsp;two&nbsp;open&nbsp;source&nbsp;codes:</p> <p>[Akiles](10.5281/zenodo.1098432)&nbsp;and&nbsp;[Fumagno](10.5281/zenodo.593787).</p> <p>The&nbsp;model&nbsp;and&nbsp;the&nbsp;simulation&nbsp;cases&nbsp;are&nbsp;explained&nbsp;in&nbsp;the&nbsp;accompanying&nbsp;paper&nbsp;(https://doi.org/10.1088/1361-6595/ac2a0b).</p> <p>&nbsp;</p> <p>##&nbsp;Data&nbsp;files</p> <p>&nbsp;</p> <p>The&nbsp;datafiles&nbsp;are&nbsp;in&nbsp;standard&nbsp;Matlab&nbsp;.mat&nbsp;format.&nbsp;A&nbsp;recent&nbsp;version&nbsp;of&nbsp;[Matlab](https://www.mathworks.com/products/matlab.html)&nbsp;(2018a&nbsp;or&nbsp;newer)&nbsp;is&nbsp;needed&nbsp;to&nbsp;read&nbsp;these&nbsp;files&nbsp;.</p> <p>&nbsp;</p> <p>Datafiles&nbsp;are&nbsp;subdivided&nbsp;into&nbsp;two&nbsp;groups&nbsp;(1D&nbsp;and&nbsp;2D).</p> <p>&nbsp;</p> <p>In&nbsp;the&nbsp;1D&nbsp;group,&nbsp;simulations&nbsp;for&nbsp;the&nbsp;first&nbsp;part&nbsp;of&nbsp;the&nbsp;paper&nbsp;are&nbsp;contained.&nbsp;These&nbsp;are&nbsp;simulations&nbsp;along&nbsp;a&nbsp;single&nbsp;(1D)&nbsp;magnetic&nbsp;line.&nbsp;There&nbsp;are&nbsp;7&nbsp;files:</p> <p>1.&nbsp;line_J0.mat</p> <p>2.&nbsp;line_phiinfty5.mat</p> <p>3.&nbsp;line_phiinfty6.mat</p> <p>4.&nbsp;line_phiinfty7.mat</p> <p>5.&nbsp;line_phiinfty8.mat</p> <p>6.&nbsp;line_phiinfty9.mat</p> <p>7.&nbsp;line_phiinfty10.mat&nbsp;</p> <p>Each&nbsp;of&nbsp;these&nbsp;files&nbsp;has&nbsp;an&nbsp;identical&nbsp;structure,&nbsp;with&nbsp;the&nbsp;following&nbsp;Matlab&nbsp;variables&nbsp;in&nbsp;them.&nbsp;All&nbsp;variables&nbsp;are&nbsp;normalized&nbsp;as&nbsp;explained&nbsp;in&nbsp;the&nbsp;paper:</p> <p>*&nbsp;h:&nbsp;a&nbsp;vector&nbsp;containing&nbsp;the&nbsp;value&nbsp;of&nbsp;B&nbsp;(magnetic&nbsp;field&nbsp;strength)&nbsp;at&nbsp;each&nbsp;point&nbsp;in&nbsp;the&nbsp;magnetic&nbsp;line</p> <p>*&nbsp;phi:&nbsp;a&nbsp;vector&nbsp;containing&nbsp;the&nbsp;value&nbsp;of&nbsp;phi&nbsp;(electric&nbsp;potential)&nbsp;at&nbsp;each&nbsp;point&nbsp;in&nbsp;the&nbsp;magnetic&nbsp;line</p> <p>*&nbsp;electrons:&nbsp;a&nbsp;structure&nbsp;with&nbsp;all&nbsp;the&nbsp;moments&nbsp;and&nbsp;all&nbsp;the&nbsp;properties&nbsp;of&nbsp;the&nbsp;electrons</p> <p>*&nbsp;ions:&nbsp;a&nbsp;structure&nbsp;with&nbsp;all&nbsp;the&nbsp;moments&nbsp;and&nbsp;all&nbsp;the&nbsp;properties&nbsp;of&nbsp;the&nbsp;ions</p> <p>&nbsp;</p> <p>In&nbsp;the&nbsp;2D&nbsp;group,&nbsp;simulations&nbsp;for&nbsp;the&nbsp;second&nbsp;part&nbsp;of&nbsp;the&nbsp;paper&nbsp;are&nbsp;contained.&nbsp;These&nbsp;are&nbsp;2D&nbsp;simulations.&nbsp;A&nbsp;total&nbsp;of&nbsp;5&nbsp;files&nbsp;exist,&nbsp;corresponding&nbsp;to&nbsp;each&nbsp;simulation&nbsp;case&nbsp;in&nbsp;the&nbsp;paper:</p> <p>1.&nbsp;F.mat</p> <p>2.&nbsp;PHID.mat</p> <p>3.&nbsp;PHII.mat</p> <p>4.&nbsp;TD.mat</p> <p>5.&nbsp;TI.mat</p> <p>Each&nbsp;of&nbsp;these&nbsp;files&nbsp;has&nbsp;an&nbsp;identical&nbsp;structure,&nbsp;with&nbsp;the&nbsp;following&nbsp;Matlab&nbsp;variables&nbsp;in&nbsp;them.&nbsp;All&nbsp;variables&nbsp;are&nbsp;normalized&nbsp;as&nbsp;explained&nbsp;in&nbsp;the&nbsp;paper:</p> <p>*&nbsp;Z,R:&nbsp;position&nbsp;of&nbsp;points</p> <p>*&nbsp;B,ALPHA,KAPPA:&nbsp;magnetic&nbsp;field&nbsp;strength,&nbsp;angle,&nbsp;and&nbsp;curvature.&nbsp;B_B0&nbsp;is&nbsp;B&nbsp;normalized&nbsp;with&nbsp;the&nbsp;upstream&nbsp;value&nbsp;on&nbsp;each&nbsp;line.</p> <p>*&nbsp;PHI,&nbsp;EZ,&nbsp;ER:&nbsp;electric&nbsp;potential&nbsp;and&nbsp;field&nbsp;components</p> <p>*&nbsp;J,&nbsp;J0:&nbsp;current&nbsp;density,&nbsp;and&nbsp;the&nbsp;integral&nbsp;current&nbsp;in&nbsp;the&nbsp;magnetic&nbsp;nozzle</p> <p>*&nbsp;N,&nbsp;N1,&nbsp;N2,&nbsp;N4:&nbsp;density&nbsp;of&nbsp;the&nbsp;full&nbsp;electron&nbsp;population&nbsp;and&nbsp;subpopulations&nbsp;1&nbsp;(free),&nbsp;2&nbsp;(reflected),&nbsp;4&nbsp;(doubly-trapped)</p> <p>*&nbsp;TE,&nbsp;TE1,&nbsp;TE2,&nbsp;TE4:&nbsp;average&nbsp;temperature&nbsp;of&nbsp;the&nbsp;full&nbsp;electron&nbsp;population&nbsp;and&nbsp;subpopulations&nbsp;1&nbsp;(free),&nbsp;2&nbsp;(reflected),&nbsp;4&nbsp;(doubly-trapped)</p> <p>*&nbsp;TPARE,&nbsp;TPARE1,&nbsp;TPARE2,&nbsp;TPARE4:&nbsp;parallel&nbsp;temperature&nbsp;of&nbsp;the&nbsp;full&nbsp;electron&nbsp;population&nbsp;and&nbsp;subpopulations&nbsp;1&nbsp;(free),&nbsp;2&nbsp;(reflected),&nbsp;4&nbsp;(doubly-trapped)</p> <p>*&nbsp;TPERE,&nbsp;TPERE1,&nbsp;TPERE2,&nbsp;TPERE4:&nbsp;perpendicular&nbsp;temperature&nbsp;of&nbsp;the&nbsp;full&nbsp;electron&nbsp;population&nbsp;and&nbsp;subpopulations&nbsp;1&nbsp;(free),&nbsp;2&nbsp;(reflected),&nbsp;4&nbsp;(doubly-trapped)</p> <p>*&nbsp;UE,&nbsp;UE1,&nbsp;UI:&nbsp;velocity&nbsp;of&nbsp;electrons,&nbsp;free&nbsp;electrons,&nbsp;ions</p> <p>&nbsp;</p> <p>##&nbsp;Citation</p> <p>&nbsp;</p> <p>Works&nbsp;using&nbsp;this&nbsp;dataset&nbsp;or&nbsp;any&nbsp;part&nbsp;of&nbsp;it&nbsp;in&nbsp;any&nbsp;form&nbsp;shall&nbsp;cite&nbsp;it&nbsp;as&nbsp;follows.</p> <p>&nbsp;</p> <p>The&nbsp;preferred&nbsp;means&nbsp;of&nbsp;citation&nbsp;is&nbsp;to&nbsp;reference&nbsp;the&nbsp;publication&nbsp;associated&nbsp;to&nbsp;this&nbsp;dataset,&nbsp;of&nbsp;DOI&nbsp;10.1088/1361-6595/ac2a0b.</p> <p>&nbsp;</p> <p>Optionally,&nbsp;the&nbsp;dataset&nbsp;may&nbsp;be&nbsp;cited&nbsp;directly&nbsp;by&nbsp;referencing&nbsp;the&nbsp;DOI:&nbsp;10.5281/zenodo.5557592.</p> <p>&nbsp;</p> <p>##&nbsp;Acknowledgments</p> <p>&nbsp;</p> <p>This&nbsp;dataset&nbsp;was&nbsp;created&nbsp;by&nbsp;the&nbsp;[ERC-ZARATHUSTRA&nbsp;project](https://erc-zarathustra.uc3m.es/).</p> <p>&nbsp;</p> <p>The&nbsp;ERC-ZARATHUSTRA&nbsp;project&nbsp;has&nbsp;received&nbsp;funding&nbsp;from&nbsp;the&nbsp;European&nbsp;Research&nbsp;Council&nbsp;(ERC)&nbsp;under&nbsp;the&nbsp;European&nbsp;Union&rsquo;s&nbsp;Horizon&nbsp;2020&nbsp;research&nbsp;and&nbsp;innovation&nbsp;programme&nbsp;(grant&nbsp;agreement&nbsp;No&nbsp;950466).&nbsp;</p>

openodc-byOct 2021View details →
zenodo40/100

Supplementary Material for Automated Kinetic Models to Predict the Flame Speeds of Halocarbons

<p>Supplementary material to accompany the paper &quot;Automated Kinetic Models to Predict the Flame Speeds of Halocarbons&quot; by&nbsp;Nora Khalil, Sevy Harris, Richard H. West, submitted to the&nbsp;13th U. S. National Combustion Meeting,&nbsp;Organized by the Central States Section of the Combustion Institute,&nbsp;March 19&ndash;22, 2023,&nbsp;College Station, Texas.</p> <p>RMG input files.</p> <p>&nbsp;</p>

opencc-by-4.0Jan 2023View details →
zenodo40/100

Data for Coupling Covariance Matrix Adaptation with Continuum Modeling for Determination of Kinetic Parameters Associated with Electrochemical CO2 Reduction

<p>This data set contains digitized and tagged polarization and partial current density data for 18 datasets of CO<sub>2</sub> reduction to H<sub>2</sub> and CO over Ag catalysts, as well as 8 datasets of CO<sub>2</sub> reduction to HCOO<sup>-</sup>, CO, and H<sub>2</sub> over Sn catalysts. We analyze this data using a coupled continuum modeling and covariance matrix adaptation approach for which the codebase is provided in DOI:&nbsp;10.5281/zenodo.7866195.</p>

opencc-by-4.0Apr 2023View details →
dryad40/100

Analytical kinetic model of native tandem promoters in E. coli

Open the record for dataset details and reuse information.

publicMar 2022View details →
zenodo36/100

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>

opencc-zeroSep 2016View details →
zenodo36/100

Data accompanying the paper "Regime-dependent turbulence length scale formulation for NWP models based on turbulence kinetic energy, shear and stratification", submitted to Monthly Weather Review

<p>This repository contains the outputs of MicroHH LES (van Heerwaarden et al., 2017) and ALADIN-CZ single-column model simulations of four idealized cases:</p> <p>1) The continental cumulus case utilizing measurements from the Atmospheric Radiation Measurement (ARM) program, and Cloud and Radiation Testbed (CART) site in Oklahoma (Brown et al. 2002; Lenderink et al. 2004)</p> <p>2) The trade wind cumulus case from the Barbados Oceanographic and Meteorological Experiment (BOMEX; Siebesma et al. 2003)</p> <p>3) A drizzling stratocumulus case based on the first research flight data of the second period of the Dynamics and Chemistry of Marine Stratocumulus (DYCOMS-II) campaign (Stevens et al., 2005)</p> <p>4) A stable planetary boundary layer case based on the Global Energy and Water Cycle Experiment (GEWEX) Atmospheric Boundary Layer Study (GABLS1) data (Beare et al. 2006; Cuxart et al. 2006; Holtslag 2006)</p> <p>The MicroHH LES outputs are taken from Reilley et al. (2022) study and can be also found at https://doi.org/10.5281/zenodo.6372434. Additionally, we provide case study outputs from the ALADIN-CZ 3D NWP model, wherein the fields roughly match those verified/shown in Fig. 9.</p> <p>&nbsp;</p> <p>The files are organized in the following way:</p> <p>1) MicroHH LES model configuration files (.ini) and output files (NetCDF format) are stored in the file "LES.zip" within "conf" and "data" folders, respectivelly. Additionally, a sample script to plot LES-derived Turbulence Length Scales (TLS) and those based on NWP formulations (using LES data as input) is provided (plot.py).</p> <p>2) The vertical profiles of (i) conserved variables and (ii) turbulent fluxes from the ALADIN-CZ single-column model for four idealized cases are provided in the file "single-column_simulations.zip", consisted of individual ASCII files (per case and TLS formulation). A detailed description of its content can be found in the associated README file.</p> <p>3) Chosen surface and upper-air fields for (i) 23 November 2019 inversion and (ii) 24 June 2022 mesoscale convection system cases are provided in the file "case_studies.zip" and consisted of individual GRIB files per field and prognostic hour. &nbsp;A detailed description of its content can be found in the associated README file.</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2024View details →
zenodo36/100

Foot kinematics and kinetics data for different static foot posture collected using a multi-segment foot model

<p>Dataset presented in the paper <em>"Foot kinematics and kinetics data for different static foot posture collected using a multi-segment foot model".</em></p> <p>This dataset contains human foot joints kinematics and kinetics data collected during walking, classified depending on their static foot posture. The kinematics data were recorded using a three-dimensional motion analysis system, and kinetics data were recorded through a pressure platform. The data was collected considering a multi-segment foot model that considers the ankle, midtarsal and first metatarsophalangeal joint. A total of 70 healthy subjects with different static posture (highly pronated, highly supinated and normal, as classified by the foot posture index) participated in the experiments. This dataset contains a total of 350 continuous recordings of anatomical angles and joint moments of the ankle, midtarsal, and first metatarsophalangeal joints of the right foot during walking, as well as the right foot contact pressures recorded. The recordings were collected at 100 Hz, and the resulting data are provided filtered and resampled to 100 frames evenly distributed along the stance phase. Participants&rsquo; descriptive data are also provided: age, weight, height, and foot anthropometric data and foot posture index for both feet. The data are presented as a spreadsheet file (.xlsx) and a Matlab structure file (.mat), with contact pressures provided only in the .mat file. Further details and data validation are provided in the main paper.</p>

opencc-by-4.0Mar 2024View details →
zenodo36/100

Evidence of an internal model of friction when controlling kinetic energy at impact to slide an object along a surface toward a target

<p>This repository contains zip files for data (Data.zip) and Matlab functions library (Library.zip), and the Matlab script&nbsp;(Matlab_Script_for_Cumputed_data.m) used in the Fami&eacute; et al PLOSONE study. In addition, the <em>README FIRST MATLAB program.pdf</em> file explains&nbsp;the Matlab code and data organization.&nbsp;</p>

opencc-by-4.0Nov 2021View details →
zenodo36/100

Dataset of paper "Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 – Part 1: The dark side of peroxide"

<p>Data of the experimental and predicted <em>E. coli </em>inactivation and H<sub>2</sub>O<sub>2</sub> profiles under dark conditions to study the effect of rising water temperature.</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

Dataser of paper "Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 – Part 2: Shine on you, crazy peroxide"

<p>Data of the experimental and predicted <em>E. coli </em>inactivation and H<sub>2</sub>O<sub>2</sub> profiles under different conditions of UV radiation, water temperature and initial H<sub>2</sub>O<sub>2</sub> concentration.</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

Computational models from: Allele-specific activation, enzyme kinetics, and inhibitor sensitivities of EGFR exon 19 deletion mutations in lung cancer

<p>Computational models,&nbsp;compressed molecular dynamics (MD) simulation trajectories, and sample input files&nbsp;for &quot;Allele-specific activation, enzyme kinetics, and inhibitor sensitivities of EGFR exon 19 deletion mutations in lung cancer&quot;. An early version of this manuscript is available as a preprint here:&nbsp;https://www.biorxiv.org/content/10.1101/2022.03.16.484661v1</p>

opencc-by-4.0May 2022View details →
zenodo36/100

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>&nbsp;study. In addition to the computed atmospheric hydroxyl (OH) and hydroperoxyl (HO2)&nbsp;radicals&nbsp;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&nbsp;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>

opencc-by-3.0Jun 2022View details →
zenodo36/100

Chemical kinetic model of spCas9 on-target efficiency.

<p>Data for the article &quot;Chemical kinetic model of spCas9 on-target efficiency&quot;. The preprint is live on <a href="https://doi.org/10.21203/rs.3.rs-2113695/v1">ResearchSquare</a>. DOI: 10.21203/rs.3.rs-2113695/v1.</p> <p>Video Abstract: <a href="https://youtu.be/qG10zxP1zUM">https://youtu.be/qG10zxP1zUM</a></p> <p>Code Demo: <a href="https://youtu.be/ltG5Rb7swXw">https://youtu.be/ltG5Rb7swXw</a></p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Dataset to accompany publication "Precision of Radiation Chemistry Networks: Playing Jenga with Kinetic Models for Liquid-Phase Electron Microscopy"

<h2>Dataset description</h2> <p>This dataset displays the raw data for the manuscript "Precision of Radiation Chemistry Networks: Playing Jenga with Kinetic Models for Liquid-Phase Electron Microscopy"<strong> </strong>published in <em>Precision Chemistry&nbsp;</em>on 06 December 2023 (DOI: <a title="DOI URL" href="https://doi.org/10.1021/prechem.3c00078">10.1021/prechem.3c00078</a>).</p> <p>&nbsp;</p>

opencc-by-4.0Jun 2024View details →
zenodo36/100

Physiological parameters for four fish species (rainbow trout, zebra fish, fathead minnow and three-spined stickleback) as the basis for the development of generic physiologically-based kinetic models

<p>This excel file (DOI: 10.5281/zenodo.1414332) provides physiological parameters and their inter-individual variability (mean, coefficient of variation, sample size) for four fish species: rainbow trout (<em>Onchorhynchus mykiss</em>), zebrafish (<em>Danio rerio</em>), fathead minnow (<em>Pimephales promelas</em>), and three-spined stickleback (<em>Gasterosteus aculeatus</em>).&nbsp; These physiological parameters were estimated based on the results of extensive literature searches and specific experimental data described in Grech et al., (2018). &nbsp;</p> <p>This file is associated with R codes (DOI: 10.5281/zenodo.1414332) for generic PB-K models, partition coefficient Quantitative Structure Activity Relationship (QSAR) models for each fish species and parameterisation of model for males and females of each species separately.</p> <p>The full data collection and implementation of the models using case studies are described in Grech et al., 2018 (<a href="https://doi.org/10.1016/j.scitotenv.2018.09.163">https://doi.org/10.1016/j.scitotenv.2018.09.163</a>)</p>

opencc-by-4.0Sep 2018View details →
zenodo36/100

Electrochemical data shown in A. Fasano, C. Baffert, C. Schumann, G Berggren, J. Birrell, V. Fourmond, C. Léger, "Kinetic modeling of the reversible or irreversible electrochemical responses of FeFe-hydrogenases", J. Am. Chem. Soc 146, 2, 1455–1466 (2024) doi: 10.1021/jacs.3c10693

Open the record for dataset details and reuse information.

opencc-by-4.0Sep 2024View details →
zenodo36/100

Lattice kinetic Monte Carlo model to simulate RNA polymerase II clusters

<p>This data set includes Python scripts (numerical simulation and analysis)&nbsp;and already generated simulation data for RNA polymerase II clusters. RNA polymerase II particles as single lattice sites and chromatin with regulatory region as connected polymer.</p>

opencc-by-4.0Jun 2021View details →
zenodo36/100

Supporting information for "Kinetics of CN(v=1) reactions with butadiene isomers at low temperature by cw-Cavity Ringdown in a pulsed Laval flow with theoretical modelling of rates and entrance channel branching

<p>This file contains the master equation inputs for all the reactions studied, as well as all the details on stationary points and VRC-TST fluxes necessary to reproduce the simulations.&nbsp;</p>

opencc-by-4.0Mar 2023View details →
zenodo36/100

Variability of Eddy Kinetic Energy in the Eurasian Basin of the Arctic Ocean inferred from a Model Simulation at 1-km Resolution (data)

<p>Data for&nbsp;&quot;Variability of Eddy Kinetic Energy in the Eurasian Basin of the Arctic Ocean inferred from a Model Simulation at 1-km Resolution&quot;</p>

opencc-by-4.0Apr 2023View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record