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.
92
datasets available to search
ShareScore release 0.9.0
Dataset results
92 results for “Energy surface”
Dataset supporting the paper "Superconducting Scanning Tunneling Microscope Tip to Reveal Sub-millielectronvolt Magnetic Energy Variations on Surfaces. J. Phys. Chem Lett. 12, 2983 (2021)"
<p>Dataset corresponding to theoretical calculations in the supporting information of the paper "Superconducting Scanning Tunneling Microscope Tip to Reveal Sub-millielectronvolt Magnetic Energy Variations on Surfaces" J. Phys. Chem Lett. 12, 2983 (2021), <a href="https://doi.org/10.1021/acs.jpclett.1c00328">https://doi.org/10.1021/acs.jpclett.1c00328</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the supporting information. They contain:</p> <ul> <li>.siesta files: STM images in WsXM format (http://www.wsxm.eu/) simulated using STMpw (<a href="https://doi.org/10.5281/zenodo.3581159">https://doi.org/10.5281/zenodo.3581159</a>).</li> <li>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>).</li> <li>.agr files: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).</li> </ul>
Optimized structures of the stationary points on the potential energy surface of the OH(2Π) + C2H4 reaction
<p>This Zip file contains the cartesian coordinates of optimized stationary points of the OH(<sup>2</sup>Π) + C<sub>2</sub>H<sub>4</sub> potential energy surface published in our article “OH(<sup>2</sup>Π) + C<sub>2</sub>H<sub>4</sub> Reaction: A Combined Crossed Molecular Beam and Theoretical Study” (P<em>hys. Chem. A</em> 2023, 127, 21, 4609–4623), that can be found in <a href="https://doi.org/10.1021/acs.jpca.2c08662">https://doi.org/10.1021/acs.jpca.2c08662</a>.</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.</p>
Optimized structures of the stationary points on the potential energy surface of the O(3P, 1D) + HCCCN(X1Σ+) reaction
<p>This Zip file contains the cartesian coordinates of optimized stationary points of the O(<sup>3</sup>P, <sup>1</sup>D) + HCCCN(X<sup>1</sup>Σ<sup>+</sup>) potential energy surface published in our article “Reactions O(<sup>3</sup>P, <sup>1</sup>D) + HCCCN(X<sup>1</sup>Σ<sup>+</sup>) (Cyanoacetylene): Crossed-Beam and Theoretical Studies and Implications for the Chemistry of Extraterrestrial Environments” (<em>J. Phys. Chem. A</em> 2023, 127, 3, 685–703), that can be found in <a href="https://doi.org/10.1021/acs.jpca.2c07708">https://doi.org/10.1021/acs.jpca.2c07708</a>.</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.</p>
Optimized structures of the stationary points on the potential energy surface of the dissociation of the CH3OH˙+ cation
<p>This Zip file contains the optimized stationary points structures of the potential energy surface (PES) for the dissociation of the CH3OH˙+ cation.</p> <p>The PES has been published in our paper “Fragmentation of interstellar methanol by collisions with He˙<sup>+</sup>: an experimental and computational study” (<em><strong>Phys. Chem. Chem. Phys.</strong></em>, 2022, <strong>24</strong>, 22437-22452), that can be found in https://doi.org/10.1039/D2CP02458F .</p> <p>All calculations have been performed with Gaussian 09, Revision D.01 and the structures were optimized at ωB97X-D/aug-cc-pVTZ level of theory.</p>
Surface carbon, water and energy fluxes measured by eddy covariance at 3 sites within the Alaska Peatlands Experiment and Bonanza Creek Experimental Forest
These data are simultaneous and continuous measurements of carbon, water and energy fluxes of the terrestrial landscape. These fluxes are major regulatory drivers of the boreal climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. At the APEX project site, within Bonanza Creek Experimental Forest, this monitoring is repeated across a chronosequence of permafrost degradation; the Black Spruce site is an area of stable permafrost with intact black spruce forest (APEX gamma site), the Thermokarst site is an active thermokarst zone with considerable tree mortality (APEX betaSW site), the Fen site is within a stable treeless fen with deep active layer depth (APEX apexcon,low, and ele sites). The main variables being monitored are the instananeous fluxes of CO2, water vapor and surface energy (shortwave, longwave and net radiation), secondary variables included photosynthetically active radiation (PAR), air and soil temperatures, rainfall, snow depth, soil moisture content, wind direction and speed, and average atmospheric concentrations of CO2 and H2O through the year.
A Terrylene Bisimide based Universal Host for Aromatic Guests to Derive Contact Surface-Dependent Dispersion Energies
<p>Additional data to report <a href="https://doi.org/10.1002/anie.202318451">https://doi.org/10.1002/anie.202318451</a>:<br><br>π–π interactions are among the most important intermolecular interactions in supramolecular systems. Here we determine experimentally a universal parameter for their strength that is simply based on the size of the interacting contact surfaces. Toward this goal we designed a new cyclophane based on terrylene bisimide (TBI) π-walls connected by <em>para</em>-xylylene spacer units. With its extended π-surface this cyclophane proved to be an excellent and universal host for the complexation of π-conjugated guests, including small and large polycyclic aromatic hydrocarbons (PAHs) as well as dye molecules. The observed binding constants range up to 10<sup>8</sup> M<sup>−1</sup> and show a linear dependence on the 2D area size of the guest molecules. This correlation can be used for the prediction of binding constants and for the design of new host–guest systems based on the herewith derived universal Gibbs interaction energy parameter of 0.31 kJ/molÅ<sup>2</sup> in chloroform.</p>
Estimating surface water availability in high mountain rock slopes using a numerical energy balance model
<p>Model output, forcing data and physical parameters used to estimate water and energy balance. The model was calibrated with field measurements from a study site in the Mont-Blanc massif, at 3842 m a.s.l, at a slope of 55 deegrees and aspect azimut of 150 degrees (south-east). The different ModelOutput files are from simulations at different elevastions (from 4800 m to 2700 m at steps of 300 m). We used the CryoGrid community model (version 1.0) toolbox (Westermann et al., 2022) to simulate the 1D ground thermal regime and ice/water balance, and estimate the availability of surface water and its potential for infiltration in rock fractures. The S2M-SAFRAN dataset combines output from a numerical weather prediction model and <em>in situ</em> observations, and was originally developed for operational needs to estimate avalanche hazard in mountainous areas (Durand et al., 1993). The S2M-SAFRAN dataset that we used is available for various mountain areas, at elevation steps of 300 m, and with an hourly resolution between the years 1958 to 2021 (Vernay et al., 2022). It includes most parameters that are required for modeling with CryoGrid: Relative humidity, air T, incoming long wavelength radiation, incoming short wavelength solar radiation, and wind speed. To complete the forcing data we used top of the atmosphere incident solar radiation from ERA5 global reanalysis dataset (Hersbach et al., 2020).</p>
The microclimate, surface energy flux and human skin burn risks of artificial turf as compared to natural turf
<p>This dataset contains the measured hourly mean microclimate and surface energy flux data from a field experiment. The experiment consisted of three treatments: unirrigated artificial turf, unirrigated natural turf, and irrigated natural turf (4 mm/day, 13:00-13:23 local time). The experiment was conducted from 2024-01-28 to 2024-03-18 in Burnley, Melbourne, Australia.<br><br>For each treatment, the measured hourly mean data included albedo, soil moisture content, air temperature, vapour pressure of water, wind speed, black globe temperature, mean radiant temperature, universal theraml climate index, wet-bulb globe temperature, soil temperature, turf surface temperature, incoming and outgoing longwave and shortwave radiant fluxes, sensible heat flux, latent heat flux, and ground heat flux. <br><br>Turf surface temperature, and incoming and outgoing longwave and shortwave radiant fluxes were measured at 1.5 m above ground surface.<br>Air temperature and vapour pressure of water were measured at 0.6 and 1.1 m above ground surface.<br>Wind speed, black globe temperature, mean radiant temperature, universal thermal climate index, and wet-bulb globe temperature were measured at 1.1 m above ground surface.<br>Soil moisture content, soil temperature and ground heat flux were measured at 0.1 m below ground surface.<br>Sensible heat flux and latent heat flux were calculated using the Bowen ratio-energy balance method.<br><br>Additionally, the hourly mean background weather conditions (air temperature and cloud amount) from the nearest public climate station in the study period were included in 'ReferenceClimateStation.csv'. Hourly total rainfall data measured at the study site was also included. <br><br>The aims of this study was to:<br>1. Compare the microclimate and human heat stress among the three treatments.<br>2. Assess and compare the human skin burn risks of the three treaments from their turf surface temperatures.<br>3. Analyse the surface energy fluxes of the three treatments to identify the mechanisms by which artificial turf develops any microclimate, human heat stress and turf surface temperature differences.<br><br>This study was published in:</p> <p><span>Cheung, P. K., & Livesley, S. J. (2025). The microclimate, surface energy flux and human skin burn risks of artificial turf as compared to natural turf. <em>Building and Environment</em>, 112679. https://doi.org/10.1016/j.buildenv.2025.112679<br></span><br>Contact person: Dr Paul Cheung (cheung.p@unimelb.edu.au)</p>
Optimized stationary points on the potential energy surface of the reaction of atomic oxygen O(3P) with acrylonitrile
<p>This Zip file contains the cartesian coordinates of optimized stationary points of the O(<sup>3</sup>P) + acrylonitrile potential energy surface (PES).</p> <p>The PES has been published in our article “A Computational Analysis of the Reaction of Atomic Oxygen O(<sup>3</sup>P) with Acrylonitrile”</p> <p>(<em>Lecture Notes in Computer Science</em> <strong>2021</strong>, 12958, 339-350), that can be found in https://doi.org/10.1007/978-3-030-87016-4_25 .</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.</p>
Optimized stationary points on the potential energy surfaces of the N(2D) + CH2CHCN and CN + CH2CHCN reactions
<p>This Zip file contains the cartesian coordinates of optimized stationary points on the potential energy surfaces (PESs) of two reactions: N(<sup>2</sup>D) + CH<sub>2</sub>CHCN (acrylonitrile) and CN + CH<sub>2</sub>CHCN.</p> <p>The PES has been published in our article “A Theoretical Investigation of the Reactions of N(<sup>2</sup>D) and CN with Acrylonitrile and Implications for the Prebiotic Chemistry of Titan”</p> <p>(<em>Lecture Notes in Computer Science</em> <strong>2022</strong>, 13378, 246-259), that can be found in https://doi.org/10.1007/978-3-031-10562-3_18 .</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.</p>
Optimized stationary points on the potential energy surfaces of the N(2D)+ C2H4 and N(2D)+ CH2CHCN reactions
<p>This Zip file contains the cartesian coordinates of optimized stationary points on the potential energy surfaces (PESs) of two reactions: N(<sup>2</sup>D)+ C<sub>2</sub>H<sub>4</sub> and N(<sup>2</sup>D)+ CH<sub>2</sub>CHCN.</p> <p>The PESs have been published in our article “Computational Investigation of the N(<sup>2</sup>D)+ C<sub>2</sub>H<sub>4</sub> and N(<sup>2</sup>D)+ CH<sub>2</sub>CHCN Reactions: Benchmark Analysis and Implications for Titan’s Atmosphere”</p> <p>(<em>Lecture Notes in Computer Science</em> <strong>2023</strong>, 14105, 705-717), that can be found in https://doi.org/10.1007/978-3-031-37108-0_45 .</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.</p>
Optimized stationary points on the potential energy surfaces of the S+(4S) + SiH2(1A1) and HSiS+/SiSH+ + NH3 reactions
<p>This Zip file contains the cartesian coordinates of optimized stationary points on the potential energy surfaces (PESs) of three reactions: S<sup>+</sup>(<sup>4</sup>S) + SiH<sub>2</sub>(<sup>1</sup>A<sub>1</sub>), <sup>3</sup>HSiS<sup>+</sup> + NH<sub>3</sub> and <sup>3</sup>SiSH<sup>+</sup> + NH<sub>3</sub>.</p> <p>These PESs are part of our paper “The S<sup>+</sup>(<sup>4</sup>S)+SiH<sub>2</sub>(<sup>1</sup>A<sub>1</sub>) Reaction: Toward the Synthesis of Interstellar SiS”</p> <p>(<em>Lecture Notes in Computer Science</em> <strong>2022</strong>, 13378, 233-245), that can be downloaded in https://doi.org/10.1007/978-3-031-10562-3_17 .</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pV(T+d)Z level of theory.</p>
Optimized structures of selected stationary points on the potential energy surface of the HC3N + CN reaction
<p>This Zip file contains the cartesian coordinates of optimized stationary points of the HC<sub>3</sub>N + CN potential energy surface published in our article “Semiempirical Potential in Kinetics Calculations on the HC<sub>3</sub>N + CN Reaction” (<em>Molecules</em> <strong>2022</strong>, <em>27(7)</em>, 2297), that can be found in <a href="https://doi.org/10.3390/molecules27072297">https://doi.org/10.3390/molecules27072297</a> .</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at M06-2X/6-311+G(d,p) level of theory.</p>
Predictive simulations of core electron binding energies of halogenated species adsorbed on ice surfaces from relativistic quantum embedding calculations
<p>This dataset collects the unprocessed (= outputs from calculations) and processed (= plots, average values for orbital and ionization energies) results discussed in the paper titled "Predictive simulations of core electron binding energies of halogenated species adsorbed on ice surfaces from relativistic quantum embedding calculations" by Richard Asamoah Opoku, Céline Toubin, and André Severo Pereira Gomes.</p>
Potential energy surfaces and rovibrational line lists for beryllium dihydride
<p>Molpro restart files of the potential energy and property surfaces for water and beryllium dihydride and its deuterated isotopologue. Rovibrational line lists containing infrared and Raman intensities as reported in "Efficient and Automated Quantum Chemical Calculation of Rovibrational Nonresonant Raman Spectra" ( <a href="https://doi.org/10.1063/5.0087359">https://doi.org/10.1063/5.0087359 )</a></p>
Aerodynamic Roughness Controlled by Wind Direction, with Implications for Glacial Surface Energy Balance and Melt Rate
<p>This repository includes raw datasets, Python scripts, and output data products associated with the MRes project '<span>Aerodynamic Roughness Controlled by Wind Direction, with Implications for Glacial Surface Energy Balance and Melt Rate</span>', by Josh Abrahams, University of Leeds. </p>
Model results for `Surface pond energy absorption across four Himalayan glaciers accounts for 1/8 of total catchment ice loss'
<p>Model setup (setup.mat) and outputs (allkeyres.mat, postproc.mat) for 5000 runs of Monte Carlo supraglacial pond energy-balance modelling in the Langtang catchment of Nepal. The full set of results are included for the median model run (run_..._n1645.zip).</p> <p>Also included are flux gate results for calculation of emergence velocity (fgates...zip).</p>
Original Data for Manuscript "Energy and Momentum Distribution of Surface Plasmon-induced Hot Carriers Isolated via Spatiotemporal Separation"
<p>Raw data of the time-dependent energy density calculation and time-resolved photoemission electron microscopy (TR-PEEM) measurements used in the manuscript.</p> <p>A preprint of the manuscript is available on arXiv: <a href="https://arxiv.org/abs/2107.14277">2107.14277</a></p> <p>The manuscript was published in <em>ACS Nano</em> 2021, 15, 12, 19559-19569 <a href="https://doi.org/10.1021/acsnano.1c06586">10.1021/acsnano.1c06586</a></p> <p>The data is provided in hdf5 files, which were produced using the snomtools python package (<a href="https://github.com/hartelt/snomtools">availale on github</a>) and can be read with any <a href="https://support.hdfgroup.org/HDF5/tools5desc.html">hdf5 compatible software</a>. The calculated data was produced as described in Ref.1 with the parameters given in the manuscript. For the experimental data, each zip file contains the raw data (hdf5 Files) as well as the PEEM settings used (sav Files as output from the experiment control software) for the respective measurement.</p> <p>Parts of the manuscript that are generated from the calculated data [calculation_energy_density.zip]:</p> <ul> <li>Figure 2 A</li> <li>Figure S2</li> </ul> <p>Parts of the manuscript that are evaluated from the PEEM real space dataset [PEEM_realspace.zip]:</p> <ul> <li>Figure 2 B</li> <li>Figure 3</li> <li>Figure S1</li> <li>Figure S3</li> <li>Figure S4</li> <li>Movie S2 [timeseries_binned_fermi.avi] in the supplementary material</li> </ul> <p>Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) SPP dataset [PEEM_k-space_timesteps_SPP.zip]:</p> <ul> <li>Figure 4 (in combination with the pump pulse reference dataset)</li> <li>Figure S5 B</li> <li>Figure S6 B</li> <li>Figure S7 B</li> </ul> <p>Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) pump pulse reference dataset [PEEM_k-space_timesteps_pump.zip]:</p> <ul> <li>Figure 4 (in combination with the SPP dataset)</li> <li>Figure S5 A</li> <li>Figure S6 A</li> <li>Figure S7 A</li> </ul> <p>Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) data of the full timetrace, combining SPP dataset [PEEM_k-space_full-timetrace_SPP.zip] and pump pulse reference dataset [PEEM_k-space_full-timetrace_pump.zip]:</p> <ul> <li>Figure S8</li> </ul>
Supporting information for a multifidelity neural network formulation for molecular potential energy surfaces
<p>This is a supplementary information for our paper titled "<em>Multifidelity neural network formulations for prediction of quantum chemistry potential energy surfaces</em>"</p> <p>Supplemental information includes two data files corresponding to the complete sets of low and high fidelity training data used in numerical experiments. Format is JavaScript Object Notation (JSON).</p> <p>1. low_fidelity_training_data.json contains 74000 records</p> <p>2. high_fidelity_training_data.json contains 36988 records</p> <p>Each record consists of a numerical id ("id"), (x,y,z) position tuples ("geometry") for C5H5 ordered as 5 carbon atoms followed by 5 hydrogen atoms, and corresponding potential energy ("energy").</p> <p>Source: normal mode sampling around 2 wells, 1 transition state, and a set of IRCs as depicted in Figure 2.</p> <p>Usage: subsets of this data were used as needed to define different data amounts and different subset randomizations in Figures 5 through 8.</p>
Potential energy surfaces and rovibrational line lists for thiirane
<p>Molpro restart files (ASCII) for the XSURF program of the potential energy and dipole moment surfaces of thiirane and its fully deuterated isotopologue. Rovibrational line list (ASCII) for both molecules obtained from RVCI calculations. Data refer to the publication <em>Comprehensive quantum chemical analysis of the (ro)vibrational spectrum of thiirane and its deuterated isotopologue</em> (https://doi.org/10.1016/j.saa.2023.123083).</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.