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41 results for “experimental data, simulation data”
An experimental data set on the thermal and fluid dynamic performance of double skin facades (DSFs) subjected to various controlled boundary conditions through the use of a climate simulator facility
<p>Double skin facades (DSFs) are building envelope systems defined by complex phenomena and non-linear-processes that make characterizing their performance a non-trivial task. In an effort to enable the scientific community to access experimental data for further analysis or model validation purposes, we release together with the open-access paper entitled “<strong><em>Laboratory testbed and methods for flexible characterization of the thermal and fluid dynamic behavior of double skin facades” (</em></strong><a href="https://doi.org/10.1016/j.buildenv.2021.108700"><strong><em>https://doi.org/10.1016/j.buildenv.2021.108700</em></strong></a><strong><em>)</em></strong>, a set of experimental data collected during tests carried out with the use of the newly developed testbed. The data contains the results of a series of tests where various configurations of a full-scale DSF mock-up that have been subjected to different boundary conditions replicated in a climate simulator. The database contains a guide in the form of the file ‘Guide.pdf’, which explains how to read data, presents a schematic drawing of sensor layout, and provides more information on sensors’ positions. Further information on the original aims of the experiments, methods, and other data can be found in the article mentioned above, which becomes an essential tool to understand how to read and interpret the experimental data fully. The following collection of experimental data are provided:</p> <ul> <li>32 steady-state measurements where the following factors were changed: ventilation mode (indoor and outdoor air curtain), solar irradiance (0, 400, 600, and 800 Wm<sup>-2</sup>), outdoor chamber temperature (10, 20, 30, and 40 ℃), cavity depth (20, 30, 40 and 60 cm) and venetian blinds position (no blinds, closed blinds, θ=45 º, and open blinds) [file names: ‘Taguchi_4Lx4F_L16_I-I.csv’ and ‘Taguchi 4Lx4F_L16_O-O.csv’],</li> <li>Dynamic profile measurements corresponding to a typical hot summer day [Dynamic_profile_measurements.csv] and</li> <li>Calibration data [Callibration.csv].</li> </ul> <p>Any inquires on the experimental data<em> can be sent </em>to: aleksandar.jankovic@ntnu.no</p>
Coherent vortex dynamics in a strongly-interacting superfluid on a silicon chip: Experimental and simulation data sets
<p>This data set collates the experimental and simulation data for the research paper "Coherent vortex dynamics in a strongly-interacting superfluid on a silicon chip".</p>
Experimental data, analysis scripts and simulations for "Emittance preservation in a plasma-wakefield accelerator"
<p>This dataset presents the experimental data, the analysis scripts and the accompanying simulations for the article <em>"Emittance preservation in a plasma-wakefield accelerator"</em> by C. A. Lindstrøm <em>et al</em>. [<a href="https://doi.org/10.1038/s41467-024-50320-1">Nat. Commun. 15, 6097 (2024)</a>].</p> <p>The data was collected at the FLASHForward facility at DESY (Hamburg, Germany). Simulations were performed using <a href="https://doi.org/10.5281/zenodo.5639467" target="_blank" rel="noopener">HiPACE++ v23.11</a>.</p> <p><strong>Folder structure:</strong></p> <ul> <li>Folders containing experimental data: <ul> <li>Folder <code>1A_DATA__OBJECT_PLANE_SCANS</code> contains all data from object-plane scans (emittance measurements).</li> <li>Folder <code>1B_DATA__SPECTRUM_MEASUREMENT</code> contains all data from energy-spectrum measurements.</li> <li>Folder <code>1C_DATA__TWO_BPM_TOMOGRAPHY</code> contains all data from two-BPM tomography measurements.</li> <li>Folder <code>1D_DATA__BEAM_RECONSTRUCTION</code> contains all data from beam-reconstruction measurements (including longitudinal-phase-space measurements).</li> <li>Folder <code>1E_DATA__PLASMA_DENSITY</code> contains all data from plasma-density measurements (spectral-line broadening).</li> </ul> </li> <li>Folder <code>2_ANALYSIS</code> contains all the data-analysis scripts, required for plotting experimental figures.</li> <li>Folder <code>3_SIMULATION</code> contains all simulation scripts, required for generating 6D beam phase spaces and plotting simulation figures.</li> <li>Folder <code>4_FIGURES</code> contains all figure-plotting scripts (17 figures total).</li> </ul> <p><br><strong>Dataset structure:</strong></p> <ul> <li>Each dataset is identified by a 5-digit number (e.g., <code>14275</code>)</li> <li>Metadata and beam-synchronous scalar values are contained in a <code>.mat</code> dataset file (e.g., <code>14275.mat</code>).</li> <li>The dataset file has the following fields: <ul> <li><code>.metadata</code> containing all the generic metadata</li> <li><code>.state</code> containing all the <em>non-beam-synchronous</em> data (once per dataset; magnet settings etc.)</li> <li><code>.scalars</code> containing all the <em>beam-synchronous scalar</em> data (once per shot; BPM readings etc.)</li> <li><code>.vectors</code> containing all the <em>beam-synchronous vector</em> data (once per shot; scope traces etc.)</li> <li><code>.images</code> containing all the <em>beam-synchronous image</em> data, with relative URLs (once per shot; spectrometer images etc.)</li> </ul> </li> <li>The corresponding images (linked from the <code>.mat</code> file) are contained in the <code>images</code> folder, sorted by scan step.</li> </ul> <p><br><strong>Instructions for plotting all figures*:</strong></p> <ol> <li>Change directory to <code>4_FIGURES/</code></li> <li>In MATLAB, run <code>plot_all_figures();</code></li> <li>The 4 main figures and 13 supplementary figures will be plotted</li> </ol> <p><strong>Instructions for generating the 6D phase space for simulations*:</strong></p> <ol> <li>Change directory to<code> 3_SIMULATION/input_beam_generation/</code></li> <li>In MATLAB, run <code>generate_beam_and_plasma();</code></li> <li>The full analysis will up to several minutes (the files are stored in the <code>_files</code> folder)</li> </ol> <p><strong>Instructions for performing HiPACE++ simulations*:</strong></p> <ol> <li>Change directory to e.g. <code>3_SIMULATION/simulations/experimental_cell_50mm/</code></li> <li>The HiPACE++ input file is called <code>input_file</code></li> <li>This file refers to the plasma profile (<code>plasma_short.csv</code>) and beam files (<code>beam.h5</code> and <code>driver.h5</code>) found in <code>3_SIMULATION/run_notebooks/inputs/</code></li> </ol> <p><strong>Instructions for re-performing all the analysis*:</strong></p> <ol> <li>Change directory to <code>2_ANALYSIS/</code></li> <li>In MATLAB, run <code>run_all_analyses();</code></li> <li>The full analysis will up to several hours (the files are stored in various <code>_files</code> folders)</li> </ol> <p><em>* The scripts use UNIX system calls and are only compatible with Linux and Mac, but not Windows.</em></p>
Experimental and model data for "Nitrogen oxide production in laser-induced breakdown simulating impacts on the Hadean atmosphere"
<p>This is raw data and supporting figures associated with the publication: Heays, A. N., Kaiserová, T., Rimmer, P. B., Knížek, A., Petera, L., Civiš, S., et al. (2022). Nitrogen oxide production in laser-induced breakdown simulating impacts on the Hadean atmosphere. <em>Journal of Geophysical Research: Planets</em>, 127, e2021JE006842. <a href="https://doi.org/10.1029/2021JE006842">https://doi.org/10.1029/2021JE006842</a></p> <p>Two data files contain model output of the ARGO atmospheric photochemistry code that was used to generate figures for Sec. 3 of the paper:</p> <ul> <li>ARGO_model_data_neutral_case.txt</li> <li>ARGO_model_data_reducing_case.txt</li> </ul> <p>The following data files contain a tabulation of laboratory-measured and modelled photoabsorption spectra as described in Sec. 2 of the paper. The A-G letter-encoding of these files follows Table 1 of the paper, and the spectral ranges correspond to the strongest bands of NO, N2O, and NO2. </p> <ul> <li>laboratory_spectrum_experiment_A_species_N2O.txt</li> <li>laboratory_spectrum_experiment_A_species_NO2.txt</li> <li>laboratory_spectrum_experiment_A_species_NO.txt</li> <li>laboratory_spectrum_experiment_B_species_N2O.txt</li> <li>laboratory_spectrum_experiment_B_species_NO2.txt</li> <li>laboratory_spectrum_experiment_B_species_NO.txt</li> <li>laboratory_spectrum_experiment_C_species_N2O.txt</li> <li>laboratory_spectrum_experiment_C_species_NO2.txt</li> <li>laboratory_spectrum_experiment_C_species_NO.txt</li> <li>laboratory_spectrum_experiment_D_species_N2O.txt</li> <li>laboratory_spectrum_experiment_D_species_NO2.txt</li> <li>laboratory_spectrum_experiment_D_species_NO.txt</li> <li>laboratory_spectrum_experiment_E_species_N2O.txt</li> <li>laboratory_spectrum_experiment_E_species_NO2.txt</li> <li>laboratory_spectrum_experiment_E_species_NO.txt</li> <li>laboratory_spectrum_experiment_F_species_N2O.txt</li> <li>laboratory_spectrum_experiment_F_species_NO2.txt</li> <li>laboratory_spectrum_experiment_F_species_NO.txt</li> <li>laboratory_spectrum_experiment_G_species_N2O.txt</li> <li>laboratory_spectrum_experiment_G_species_NO2.txt</li> <li>laboratory_spectrum_experiment_G_species_NO.txt</li> </ul> <p>The following file contains a tabulation of the full-spectral-range laboratory-measured photoabsorption spectrum of experiment A, along with a modelled spectrum.</p> <ul> <li><a href="https://zenodo.org/api/files/49f05962-9a34-4bbc-855c-1a0976f62531/laboratory_spectrum_experiment_A_full_spectrum.txt?versionId=79a70ade-63d1-4fd7-b423-176e27f8dc37">laboratory_spectrum_experiment_A_full_spectrum.txt </a></li> </ul> <p>The following file contains plots of the experimental spectra for all NxOy species in all measurements as well as the residual error of models fit to these spectra. Additional residual errors of model neglecting NxOy species indicates their contribution to the spectra.</p> <ul> <li>laboratory_spectrum_figures.pdf</li> </ul> <p> </p>
Theoretical simulations data for "Experimental observation of repulsively bound magnons"
<p>The files contain the data obtained from the theoretical simulations depicted in the figures of the article "Experimental observation of repulsively bound magnons" Nature (2024).</p> <p>The format of the data and to which figure it corresponds is described in the file "read_me_metadata.txt".</p>
Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data
<p>Files uploaded here are related to the paper titled "Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data". Here we investigate how generative adversarial networks can be used to match simulated- and experimental INS data.</p>
Experimental data of Mg WE43 fiber biocorrosion in simulated body fluid
<p>This dataset contains the experimental data used to plot Figures 4 and 6 in the paper:</p> <p>S. Kovacevic, W. Ali, E. Martínez-Pañeda, J. LLorca “Phase-field modeling of pitting and mechanically-assisted corrosion of Mg alloys for biomedical applications” published in Acta Biomaterialia (2023)</p>
Experimental data for "An open-access database for the assessment of particle damper simulation tools"
<p>Experimental data for "An open access database for the assessment of particle damper simulation tools"</p>
Experimental and Simulation Data for "Hierarchical structure formation by crystal growth-front instabilities during ice templating" (2023) PNAS
<pre>Experimental and Simulation Data for: "Hierarchical structure formation by crystal growth-front instabilities during ice templating" by Kaiyang Yin, Kaihua Ji, Louise Strutzenberg Littles, Rohit Trivedi, Alain Karma, Ulrike G.K. Wegst (2023) PNAS, DOI: 10.1073/pnas.2210242120. </pre>
Falling balls in a viscous fluid with contact: Comparing numerical simulations with experimental data
<p>The full results of the numerical computations and the source code for the rigid-body ALE and rigid-body CutFEM discretisations as presented in "H. von Wahl, T. Richter, S. Frei and T. Hagemeier. ‘Falling balls in a viscous fluid with contact: Comparing numerical simulations with experimental data’. In: <em>Phys. Fluids </em>33.3, 033304 (2nd Mar. 2021). doi: <a href="http://10.1063/5.0037971">10.1063/5.0037971</a>. <a href="https://arxiv.org/abs/2011.08691">arXiv:2011.08691</a> [physics.flu-dyn]".</p>
Supporting molecular simulations data for "A combined molecular dynamics and experimental study of two-step process enabling low-temperature formation of phase-pure α-FAPbI3"
<p>Supplementary data for "A combined molecular dynamics and experimental study of two-step process enabling low-temperature formation of phase-pure α-FAPbI3: <a href="https://doi.org/10.1126/sciadv.abe3326">10.1126/sciadv.abe3326</a>"</p>
Spectroscopic and Interferometric Sum-Frequency Imaging of Strongly Coupled Phonon Polaritons in SiC Metasurfaces - Experimental and Simulation Data
<p>Data repository supporting the manuscript 'Spectroscopic and Interferometric Sum-Frequency Imaging of Strongly Coupled Phonon Polaritons in SiC Metasurfaces'.</p>
Simulated and experimental data distributed to the CASP13 participants in protein structure prediction assisted with sparse NMR data
<p>All simulated and experimental data distributed to the CASP participants in protein structure prediction assisted with sparse NMR data in CASP13.</p> <p>Also available at http://predictioncenter.org/casp13/results.cgi?view=targets&model=first&tr_type=others&sub_type=N&groups_id=</p> <p> </p>
Experimental and simulated data for the article "Reassessing the role and lifetime of Qx in the energy transfer dynamics of Chlorophyll a"
<p>The .zip file contains:</p> <ul> <li>Linear absorption spectra of Chl a in EtOH, acetone, and benzonitrile (BN)</li> <li>Low-temperature emission and excitation anisotropy datasets of Chl a in isopropanol</li> <li>Transient absorption (TA) datasets of Chl a in EtOH, acetone, and BN after B- and Q-band excitation (including pump spectra)</li> <li>Transient absorption anisotropy (TAA) datasets of Chl a in acetone after B-band excitation (including a pump spectrum)</li> <li>Optimized geometries for the Q-band ESA calculations</li> <li><span>Geometries for normal modes used for PES construction</span></li> </ul>
Relative Phase Data to 'Experimental observation of curved light-cones in a quantum field simulator', arXiv:2209.09132
<p><strong>Relative phase profiles and averaged density profiles for the results shown in arXiv:2209.09132</strong></p> <p>Each file "phase_and_mean_density_scan_X.mat" contains data for a measurement presented in the manuscript, where "X" is the corresponding scan number.<br> The following table shows the relevant scan number to measurement descriptions mentioned in the manuscript (see Table S1 in the SI Appendix).</p> <table align="center"> <thead> <tr> <th scope="col">Measurement description</th> <th scope="col">Scan number</th> </tr> </thead> <tbody> <tr> <td> <p> Homogeneous (main text)</p> </td> <td> 9185</td> </tr> <tr> <td> <p> Inhomogeneous with sharp edges </p> </td> <td> 10419</td> </tr> <tr> <td> <p> Inhomogeneous with smoothed edges</p> </td> <td> 8935</td> </tr> <tr> <td> <p> Homogeneous 2 (SI Appendix)</p> </td> <td> 10455</td> </tr> </tbody> </table> <p> </p> <p><strong>File Contents</strong></p> <p>Each file contains the following variables:</p> <ul> <li>"phase": A MATLAB cell containing all the phase profiles for every time step. Thus, "phase{t_ind}" is a matrix where rows represent experimental realizations and columns the spatial grid points. For example, "phase{5}(1,:)" would be a one-dimensional phase profile, representing the first realization of the fifth time step. To learn more about the extraction of phase profiles, read Section 2 and see Fig. S5 in SI Appendix.</li> <li>"z_grid_phase_si": Vector. Grid points for phase profiles in SI units (m).</li> <li>"averaged_density_si": Vector. Averaged initial linear density in SI units (m^-1). See Fig. 1(a).</li> <li>"z_grid_density_si": Vector. Grid points for averaged density in SI units (m).</li> <li>"times_si": Vector. Time points in SI units (s).</li> </ul> <p> </p> <p><strong>Matlab script calculating the velocity field</strong></p> <p>In addition to the data, a MATLAB script (velocity_field_calculation.m) loads a data file and calculates the velocity field and its correlations following the equations in the manuscript:</p> <ul> <li>"u": MATLAB cell. Velocity field for every time step.</li> <li>"u_u_corr": MATLAB cell. Second-order correlations of the velocity field for every time step.</li> <li>"std_u_u_corr": MATLAB cell. Standard deviation of second-order correlations of the velocity field for every time-step.</li> </ul> <p>Finally, the script plots "u_u_corr" for all the time steps and plots the averaged linear density.</p>
Data from: Experimentally simulating the evolution-to-ecology connection: Divergent predator morphologies alter natural food webs
<p class="MsoNormal">The idea that changing environmental conditions drive adaptive evolution is a pillar of evolutionary ecology. But, the opposite—that adaptive evolution alters ecological processes—has received far less attention yet is critical for eco-evolutionary dynamics. We assessed the ecological impact of divergent values in a key adaptive trait using 16 populations of the brown anole lizard (<em class="i">Anolis sagrei</em>). Mirroring natural variation, we established islands with short- or long-limbed lizards at both low and high densities. We then monitored changes in lower trophic levels, finding that on islands with short-limbed lizards at high-density<span class="inserted">,</span> web spider<span class="inserted">s</span> decreased and plants grew more via an indirect positive effect, likely through an herbivore-mediated trophic cascade. Our experiment provides strong support for evolution-to-ecology connections in nature, likely closing an otherwise well-characterized eco-evolutionary feedback loop.</p>
Experimental data and R scripts for simulations and analysis
<p>Zip file including the experimental data and R scripts for simulations and analysis used in the following article: "Colonisation debt: when invasion history impacts current range expansion by Morel-Journel, T., Haond M., Dunan L., Mailleret L. and Vercken E.</p>
Lateral interactions govern self-assembly of the bacterial biofilm matrix protein BslA (experimental and simulation data)
<p>The soil bacterium Bacillus subtilis is a model organism to investigate the formation of biofilms, the predominant form of microbial life. The secreted protein BslA self-assembles at the surface of the biofilm to give the B. subtilis biofilm its characteristic hydrophobicity. To understand the mechanism of BslA self-assembly at interfaces, here we built a molecular model based on the previous BslA crystal structure and the newly determined crystal structure of the BslA paralogue YweA. Our analysis revealed two conserved protein-protein interaction interfaces supporting BslA self-assembly into an infinite 2d lattice that fits previously determined transmission microscopy images. Molecular dynamics simulations and in vitro protein assays further support our model of BslA elastic film formation, while mutagenesis experiments highlight the importance of the identified interactions for biofilm structure. Based on this knowledge, YweA was engineered to form more stable elastic films and rescue biofilm structure in bslA deficient strains. These findings shed new light on protein film assembly and will inform the development of BslA technologies which range from surface coatings to emulsions in fast-moving consumer goods.</p>
Experimental and simulation data on magnetization and magnetization noise in tetris ice
<p>The files contain data presented in the "Deconstructing Magnetization Noise: Degeneracies, Phases, and Mobile Fractionalized Excitations in Tetris Artificial Spin Ice" paper.</p>
Speciation of aqueous solutions of iron(III)-nitrilotriacetic acid complexes - simulations and experimental data
<p>Experimental data for a paper entitled <em>Preparation and characterization of iron(III) nitrilotriacetate complex in aqueous solutions for quantitative protein binding experiments</em> (<a title="Link to landing page via DOI" href="https://doi.org/10.1039/D3AY01261A">https://doi.org/10.1039/D3AY01261A</a>).</p> <p> </p> <p>a) Speciation of aqueous solutions of iron(III)-nitrilotriacetic acid complexes - simulations</p> <p>A custom VBA script for Microsoft Excel 365 (Version 2304, build 16.0.16327.20200, 64-bit) was used to solve the 5th-order polynomial for the free ligand NTA3− as a function of all congruent association and dissociation constants and the total concentrations of iron, ligand, and hydrogen ions using the Jenkins-Traub algorithm. [1-4] For comparison, the FeNTA species distribution was also simulated using HySS software [5], which applies the Newton-Raphson algorithm to solve the mass balance equations using known equilibrium constants. [6-7]</p> <p>The Excel workbook is provided with the following information:</p> <p>Sheet 1: FeNTA-Speciation - contains all relevant equilibrium constants and corresponding equations, expressions for polynomial coefficients, polynomial roots, and equilibrium concentrations of all species. The values are calculated from the analytical concentrations provided to the HySS software and imported to Sheet 2.</p> <p>Sheet 2: HySS-Import - contains the values obtained from the HySS software (the HySS model file is also included for reference). The values in the columns headed 'total Fe', 'total NTA' and 'p(H)' are used for the calculation in Sheet 1.</p> <p>Sheet 3: Examples - contains plots for the FeNTA species distribution obtained by solving the 5th-order polynomial in Excel and HySS software: Top: Fe:NTA = 0.15 M:0.15 M, Bottom: Fe:NTA = 0.15 M:0.30 M.</p> <p>Sheet 4: Polynomial-Procedure - contains the details of using the VBA script in Excel. [1]</p> <p> </p> <p>b) UV-Vis spectrophotometric titration of human serum transferrin (hTf) with FeNTA - experimental data and results</p> <p>Additional files containing the experimental data for the UV-Vis spectrophotometric titration of human serum transferrin (hTf) with FeNTA and the obtained equilibrium constants for binding of the first and second iron(III) ion to hTf, obtained using HypSpec software [8-9], are also included.</p> <p>The files contain the HypSpec model and the summary of the results in Excel, including the concentrations of all species for each titration point, the observed and calculated absorbance, and the values and errors for the molar absorption coefficients in the range from 445 to 800 nm.</p> <p> </p> <p>For more details, please visit: <a href="https://glymech.pharma.hr//GlyMech.html">https://glymech.pharma.hr//GlyMech.html</a>.</p> <p> </p> <p>References:</p> <p>[1] Jenkins D (2014) Solving Quadratic, Cubic, Quartic and higher order equations; examples. In: Newton Excel Bach, not (just) an Excel Blog. <a href="https://newtonexcelbach.wordpress.com/2014/01/14/solving-quadratic-cubic-quartic-and-higher-order-equations-examples/">https://newtonexcelbach.wordpress.com/2014/01/14/solving-quadratic-cubic-quartic-and-higher-order-equations-examples/</a>. Accessed 18 May 2017</p> <p>[2] Jenkins MA, Traub JF (1972) Algorithm 419: zeros of a complex polynomial [C2]. Commun ACM 15:97–99. <a href="https://doi.org/10.1145/361254.361262">https://doi.org/10.1145/361254.361262</a></p> <p>[3] Jenkins MA (1975) Algorithm 493: Zeros of a Real Polynomial [C2]. ACM Trans Math Softw 1:178–189. <a href="https://doi.org/10.1145/355637.355643">https://doi.org/10.1145/355637.355643</a></p> <p>[4] Ralston A, Rabinowitz P (1978) A first course in numerical analysis, 2d ed. McGraw-Hill, New York ISBN: 9780486414546 <a href="https://www.worldcat.org/title/44883559">https://www.worldcat.org/title/44883559</a></p> <p>[5] Alderighi L, Gans P, Ienco A, Peters D, Sabatini A, Vacca A (1999) Hyperquad simulation and speciation (HySS): a utility program for the investigation of equilibria involving soluble and partially soluble species. Coordination Chemistry Reviews 184:311–318. <a href="https://doi.org/10.1016/S0010-8545(98)00260-4">https://doi.org/10.1016/S0010-8545(98)00260-4</a></p> <p>[6] Motekaitis RJ, Martell AE (1994) The Iron(III) and Iron(II) Complexes of Nitrilotriacetic Acid. Journal of Coordination Chemistry 31:67–78. <a href="https://doi.org/10.1080/00958979408022546">https://doi.org/10.1080/00958979408022546</a></p> <p>[7] Hegenauer J, Saltman P, Nace G (1979) Iron(III)-phosphoprotein chelates: stoichiometric equilibrium constant for interaction of iron(III) and phosphorylserine residues of phosvitin and casein. Biochemistry 18:3865–3879. <a href="https://doi.org/10.1021/bi00585a006">https://doi.org/10.1021/bi00585a006</a></p> <p>[8] Gans P, Sabatini A, Vacca A (1996) Investigation of equilibria in solution. Determination of equilibrium constants with the HYPERQUAD suite of programs. Talanta 43:1739–1753. <a href="https://doi.org/10.1016/0039-9140(96)01958-3">https://doi.org/10.1016/0039-9140(96)01958-3</a></p> <p>[9] Gans P, Sabatini A, Vacca A (1999) Determination of equilibrium constants from spectrophometric data obtained from solutions of known pH: The program pHab. Annali di Chimica 89:45–49.</p> <p> </p>
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.