Find research datasets worth reusing

opencc-by-sa-4.0Dec 2022View details →

Energy Climate dataset consitent with ENTSO-E TYNDP2020 studies (CSV & NetCDF) for ACDC-ESM

Energy Climate dataset consistent with ENTSO-E Pan-European Climatic Database (PECD 2021.3) in CSV and netCDF format TL;DR: this is a tidy and friendly version of a recreation of ENTSO-E's PECD 2021.3 data by using ERA5: hourly capacity factors for wind onshore, offshore, solar PV and hourly electricity demand are provided. All the data is provided for 28-71 climatic years (1950-2020 for wind and solar, 1982-2010 for demand). Description Country averages of energy-climate variables generated using the Python scripts, based on the <a href="https://2020.entsos-tyndp-scenarios.eu/">ENTSO-E's TYNDP 2020 study</a>. For the following scenario's data is available <ul> <li>National trends 2025 (NT 2025)</li> <li>National trends 2030 (NT 2030)</li> <li>National trends 2040 (NT 2040)</li> <li>Distributed Energy 2030 (DE 2030)</li> <li>Distributed Energy 2040 (DE 2040)</li> <li>Global Ambitions (GA 2030)</li> <li>Global Ambitions (GA 2040)</li> </ul> The time-series are at hourly resolution and the included variables are: <ul> <li>Generation wind offshore (aggregated for all years per scenario in a .zip)</li> <li>Generation wind onshore (aggregated for all years per scenario in a .zip)</li> <li>Generation solar photovoltaic (aggregated for all years per scenario in a .zip)</li> <li>Total energy demand (all zones combined in single file per scenario)</li> </ul> The Files are provided in CSV (.csv) & NetCDF (.nc). The data is given per ENTSO-E's bidding zone as used within the TYNDP2020.   DISCLAIMER: the content of this dataset has been created with the greatest possible care. However, we invite to use the original data for critical applications and studies.

Atomic energy densities from the multiple radii functional (MRF)

This dataset contains exchange-correlation energy densities in the gauge of the electrostatic potential for various atomic systems, all in atomic units. The first column represents the distance from the nucleus in bohr, while the remaining columns represent the energy densities. The headings for the columns are specified in the first row of the dataset. The dataset includes the exact energy densities "w_0 [exact]" and "w_1 [exact]" which are taken from reference [Phys.Chem.Chem.Phys., 2017, 19, 6169]. These densities are calculated at the zero and full coupling strengths, respectively. The densities used to calculate the MRF functional are also taken from the same reference, where the computational details can be found. "w_1 [mrf original]" represents the MRF energy densities calculated using the original fluctuation function developed in reference [J. Phys. Chem. Lett. 2017, 8, 2799−2805]. "w_1 [mrf new]" represents the MRF energy densities calculated using a newly developed fluctuation function, specifically designed to satisfy the high-density limit, non-negativity of the correlation part of the energy densities, and the uniform electron gas limit. Files are given in the XLSX format and different file names represent different atoms (ions). Wolfram Mathematica 13.1.0.0. has been used for data curation.

Electron Energy Regression in High-Granularity Calorimeter Prototype

The dataset consists of simulations of calibrated reconstructed hits produced by a positron passing through the HGCAL test beam prototype. For the simulations, Monte Carlo method is used to produce the positrons with energy ranging from 20 to 350 GeV. The dataset contains the coordinates of the calibrated reconstructed hits in the prototype along with the calibrated energy in units of MIP. The HDF5 files can be extracted from the gzip files.

SM: Economy-wide impacts of socio-politically driven net-zero energy in Europe

Supplementary Material (SM): Economy-wide impacts of socio-politically driven net-zero energy in Europe Two zipped folders (a) Euro-Calliope.zip includes -Energy system configurations by storyline (market-driven, government-directed, people-powered) and year (2030, 2050). (b) WEGDYN.zip includes -Supplementary Material (SM_Regionaleconomiceffects.pdf) -Processed Euro-Calliope output data to WEGDYN input data (EC2WD_data.xlsx) -WEGDYN results (WEGDYN_data.xlsx) -WEGDYN resolution, nesting trees, elasticities (WEGDYN_model.xlsx)

opencc-by-4.0Feb 2023View details →

Supplying renewable energy to Central European research facilities: A techno-economic comparison of electricity and hydrogen (Dataset)

This dataset contains central input assumptions and results related to the publication "Supplying renewable energy to Central European research facilities: A techno-economic comparison of electricity and hydrogen". Result files are contained in the results.zip archive file. The file contains for each scenario, as indicated by the folder structure, the following files: <ul> <li>results.csv: Central scenario results exported as character separated value (csv) file, with a semicolon (;) as field separator. All fields are quoted using double quotation marks "...". Can be explored using standard office software like Microsoft Excel/Libre Office or other tools.</li> <li>network.nc: PyPSA network file containing the optimized scenario with all input and unprocessed outputs (results). Can be explored using the <a href="https://pypsa.readthedocs.io">PyPSA software package</a>.</li> <li>lcoes.csv: Levelised Cost of Electricity used to construct the renewable energy source (RES) based supply curve for each scenario.</li> </ul> The dataset further contains the following files which represent central input assumptions to the model and scenarios, both as CSV files: <ul> <li>efficiencies.csv: Technology process and conversion efficiencies including more details on the assumptions and information on which references the assumptions are based.</li> <li>costs_2030.csv: Technology cost assumptions for 2030 including more details on the assumptions and information on which references the assumptions are based. This data is based on this <a href="https://github.com/pypsa/technology-data">Technology Data repository</a> on GitHub.</li> </ul>

opencc-by-4.0Feb 2023View details →

Energy consumption data from an office building, waterpark and warehouse in Slovenia and energy production data from a PV Plan (900KW)

The first dataset included 9-month hourly energy data from a  waterpark, a warehouse and high-rise office buildings. The second dataset includes 10-year hourly energy production data from a PV plant (900KW). Both datasets refer to Ljubljana, Slovenia.

opencc-by-4.0Mar 2023View details →

HPC-JEEP: Energy-based charging on the ARCHER2 HPC service dataset

This package contains the data and tools used to calculate and analyse an approach to energy-based charging on the ARCHER2 UK HPC facility. This analysis was performed as part of the <a href="https://zenodo.org/record/6787599/">HPC-JEEP project</a>. HPC-JEEP is funded by the <a href="https://net-zero-dri.ceda.ac.uk/">UKRI DRI Net Zero Scoping project</a>.

opencc-by-4.0Mar 2023View details →

Energy-Saving Strategies for Mobile Web Apps and their Measurement: Results from a Decade of Research - Dataset

In 2022, over half of the web traffic was accessed through mobile devices. By reducing the energy consumption of mobile web apps, we can not only extend the battery life of our devices, but also make a significant contribution to energy conservation efforts. For example, if we could save only 5% of the energy used by web apps, we estimate that it would be enough to shut down one of the nuclear reactors in Fukushima. This paper presents a comprehensive overview of energy-saving experiments and related approaches for mobile web apps, relevant for researchers and practitioners. To achieve this objective, we conducted a systematic literature review and identified 44 primary studies for inclusion. Through the mapping and analysis of scientific papers, this work contributes: (1) an overview of the energy-draining aspects of mobile web apps, (2) a comprehensive description of the methodology used for the energy-saving experiments, and (3) a categorization and synthesis of various energy-saving approaches.

opencc-by-4.0Jan 2012View details →

Repeatability of energy metabolism and resistance to dehydration in the invasive slug Limax maximus

Dataset from the paper "Repeatability of energy metabolism and resistance to dehydration in the invasive slug Limax maximus" It contains metabolic rates and body mass assessed on 30 individuals of L. maximus in three different trials. Metabolic rates are in CO2 ml/m

opencc-by-4.0Nov 2022View details →

Diffuse Emission of High-Energy Neutrinos from a Global Fit to Cosmic Rays

Model of diffuse emission of high-energy neutrinos from a global fit of cosmic rays and model of high-energy neutrino emission from unresolved pulsar-powered sources. The maps presented in the form of HEALPix maps (Gorski et al 2005, ApJ, 622, 759) of per-flavor intensity in units of GeV-1 cm-2 s-1 sr-1 at 50 logarithmically spaced energies between 10 GeV and 108 GeV. We use a value of NSIDE=256 and the RING binning scheme. We here make available our fiducial model, which is calculated assuming the Ferrière 2001 cosmic ray source distribution, the AAfrag hadronic production cross sections and the GALPROP gas maps. We calculated the emission from unresolved sources following Vecchiotti et al. 2022, ApJ, 928, 19. In Version 2 of this dataset, we also make available the local cosmic ray fluxes of our fiducial model obtained from a global fit to cosmic ray data together with the corresponding 68% and 95% uncertainty bands. These are shown in figure 6 of <a href="https://arxiv.org/abs/2211.15607">arXiv:2211.15607</a>. The nuclear fluxes are in (GeV/n)-1 m-2 s-1 sr-1, the fluxes of electrons and positrons are in GeV-1 m-2 s-1 sr-1 . The fluxes are local interstellar fluxes without solar modulation. In Version 3 of this dataset, we add the fiducial diffuse gamma ray model calculated assuming the Ferrière 2001 cosmic ray source distribution, the AAfrag hadronic production cross sections as well as the GALPROP gas maps and ISRF model. We separately make available 3 maps: The hadronic emission on neutral atomic gas, the hadronic emission on molecular gas and the leptonic emission from Inverse Compton Scattering.  Similar to the dataset of the fiducial neutrino model, the maps are presented in the form of HEALPix maps (Gorski et al 2005, ApJ, 622, 759) in units of GeV-1 cm-2 s-1 sr-1. We use a value of NSIDE=256 and the RING binning scheme. For the hadronic maps, the intensity is given at 50 logarithmically spaced energies between 10 GeV and 108 GeV. For the leptonic maps from Inverse Compton Scattering, the intensity is given at 48 logarithmically spaced energies between 1 GeV and 106 GeV. The structure of the files is somewhat different from the file containing the fiducial neutrino model. This is to allow for easy use of the gamma ray maps with the gammapy package (Deil et al. 2017, <a href="https://arxiv.org/abs/1709.01751"> arXiv:1709.01751</a>). Also available in Version 3 are the full spatio-spectral cosmic ray distributions in the Milky Way as predicted by our fiducial model. The nuclear fluxes are given for each species in (GeV/n)-1 m-2 s-1 sr-1 at 63 energies between 1 GeV and 109 GeV. The leptonic fluxes are given for each species in GeV-1 m-2 s-1 sr-1 at 36 energies between 1 GeV and 105 GeV.  All fluxes are given on a spatial grid at 81 galactocentric radii from 0 kpc to 20 kpc and 61 distances perpendicular to the galactic plane between -6 kpc and 6 kpc. Finally, a word of caution about the extra component of cosmic ray leptons included in our model: This component is contained in the last HDUnit of the fits file containing the leptonic cosmic ray distributions. It is there denoted as a flux of electrons. It must, however, also be added to the flux of positrons to achieve correct results. Please refer to <a href="https://arxiv.org/abs/2211.15607">arXiv:2211.15607</a> for further details. When using these models in your research work, please refer to this Zenodo dataset and the publication.

opencc-by-4.0Apr 2023View details →

The energy landscape for R-loop formation by the CRISPR-Cas Cascade complex - Minimal Dataset

Minimal Dataset for "The energy landscape for R-loop formation by the CRISPR-Cas Cascade complex", published at <a href="https://www.nature.com/nsmb/">NSMB</a>.

opencc-by-4.0May 2023View details →

TOM.D: Taking Advantage of Microclimate Data for Urban Building Energy Modeling

Data required to rebuild the study: "TOM.D: Taking Advantage of Microclimate Data for Urban Building Energy Modeling". In this dataset of New York City, one can find building footprints, monthly energy consumption data for each of these buildings, and matching / cleaned microclimate data from a variety of data sources which are referenced in the work. Among them, thermal infrared measurements may be found, climate models from NOAA and ERA5 may be found, and preprocessed vision systems from Google are used.

opencc-by-4.0Jun 2023View details →

Dataset: Dendritic nanoarchitecture imparts ZSM-5 zeolite with enhanced adsorption and catalytic performance in energy applications

The development of zeolites possessing dendritic features represents a great opportunity for the design of novel materials with applications in a large variety of fields and, in particular, in the energy sector to afford its transition towards a low carbon system. In the current work, ZSM-5 zeolite showing a dendritic 3D nanoarchitecture has been synthesized by the functionalization of protozeolitic nanounits with an amphiphilic organosilane, which provokes the branched aggregative growth of zeolite embryos. Dendritic ZSM-5 exhibits outstanding accessibility arising from a highly interconnected network of radially-oriented mesopores (3 – 10 nm) and large cavities (20 – 80 nm), which add to the zeolitic micropores, thus showing a well-defined trimodal pore size distribution. These singular features provide dendritic ZSM-5 with sharply enhanced performance in comparison with nano- and hierarchical reference materials when tested in a number of energy related applications, such as VOCs (toluene) adsorption (improved capacity), plastics (low-density polyethylene) catalytic cracking (boosted activity) and hydrogen production by methane catalytic decomposition (higher activity and deactivation resistance).

opencc-by-4.0Jul 2023View details →

Free energy simulations of receptor-binding domain opening in the SARS-CoV-2 spike indicate a barrierless transition with slow conformational motions

This online data set accompanies the manuscript entitled "Free energy simulations of receptor-binding domain opening in the SARS-CoV-2 spike indicate a barrierless transition with  slow conformational motions." The dataset is composed of the following files: * pmf0-now.dcd -- pmf63-now.dcd : molecular dynamics trajectory frames in each of the 64 umbrella sampling windows, from which water has been removed to save space * s1am_0-now.pdb -- s1am_63-now.pdb : initial coordinates in each of the 64 umbrella sampling windows, from which water has been removed, corresponding to the trajectory data above * view -- Visual Molecular Dynamics command script to load a trajectory,  e.g., in Linux, use "vmd -e view" * s1am_0-cg.dcd -- s1am_63-cg.dcd : molecular dynamics trajectory frames in each of the 64 umbrella sampling windows, coarse-grained to 1 bead per residue. * s1am_0-cg.pdb -- s1am_63-cg.pdb : initial coordinates in each of the 64 umbrella sampling windows, corresponding to the coarse-grained trajectory data above. * viewcg -- Visual Molecular Dynamics command script to load a coarse-grained trajectory,  e.g., in Linux, use "vmd -e viewcg" * 0readme -- brief instructions on how to view the trajectories * colors.vmd -- utility script for VMD * covmacros.vmd -- VMD script to define coronavirus spike subdomains * fe.zip -- ZIP archive that contains data and Matlab analysis files to reproduce the free energy profiles * diff.zip -- ZIP archive that contains data and Matlab analysis files to reproduce the diffusion and mean first passage times calculations * pca-qha.zip -- ZIP archive that contains the data and Matlab analysis files to compute the autocorrelation functions of trajectory displacements along principal/quasiharmonic modes Each ZIP archive contains a "0readme" file with brief instructions, and also the  results of the calculations

EnergyPROSPECTS Energy Citizenship Factsheet Series, Part 5: Aspects of ENCI I.: Hybridity, private/public, passive/active forms

This document is Part 5 of the EnergyPROSPECTS Factsheet Series. We have created the Series to publish the results of a mapping of energy citizenship in Europe, along with the first stage of our analysis of the respective data. The EnergyPROSPECTS consortium mapped 596 cases of energy citizenship (ENCI) between November 2020 and May 2021 using desk research, collecting data on many aspects of the cases. Although the analysis is a work in progress, we believe it is important to share our data and, through doing this, contribute to the understanding of energy citizenship in Europe. EnergyPROSPECTS (PROactive Strategies and Policies for Energy Citizenship Transformation), a H2020 project between 2021-2024, works with a critical understanding of energy citizenship that is grounded in state-of-the-art social sciences and humanities (SSH) insights.

EnergyPROSPECTS Energy Citizenship Factsheet Series, Part 4: Funding

This document is Part 4 of the EnergyPROSPECTS Factsheet Series. We have created the Series to publish the results of a mapping of energy citizenship in Europe, along with the first stage of our analysis of the respective data. The EnergyPROSPECTS consortium mapped 596 cases of energy citizenship between November 2020 and May 2021 using desk research, collecting data on many aspects of the cases. Although the analysis is a work in progress, we believe it is important to share our data and, through doing this, contribute to the understanding of energy citizenship in Europe. EnergyPROSPECTS (PROactive Strategies and Policies for Energy Citizenship Transformation), a H2020 project between 2021-2024, works with a critical understanding of energy citizenship that is grounded in state-of-the-art social sciences and humanities (SSH) insights.

EnergyPROSPECTS Energy Citizenship Factsheet Series, Part 2: Motivations and objectives

This document is Part 2 of the EnergyPROSPECTS Factsheet Series. We have created the Series to publish the results of a mapping of energy citizenship in Europe, along with the first stage of our analysis of the respective data. The EnergyPROSPECTS consortium mapped 596 cases of energy citizenship between November 2020 and May 2021 using desk research, collecting data on many aspects of the cases. Although the analysis is a work in progress, we believe it is important to share our data and, through doing this, contribute to the understanding of energy citizenship in Europe. EnergyPROSPECTS (PROactive Strategies and Policies for Energy Citizenship Transformation), a H2020 project between 2021-2024, works with a critical understanding of energy citizenship that is grounded in state-of-the-art social sciences and humanities (SSH) insights.

EnergyPROSPECTS Energy Citizenship Factsheet Series, Part 7: Aspects of ENCI III.: Towards social sustainability

This document is Part 7 of the EnergyPROSPECTS Factsheet Series. We have created the Series to publish the results of a mapping of energy citizenship in Europe, along with the first stage of our analysis of the respective data. The EnergyPROSPECTS consortium mapped 596 cases of energy citizenship (ENCI) between November 2020 and May 2021 using desk research, collecting data on many aspects of the cases. Although the analysis is a work in progress, we believe it is important to share our data and, through doing this, contribute to the understanding of energy citizenship in Europe. EnergyPROSPECTS (PROactive Strategies and Policies for Energy Citizenship Transformation), a H2020 project between 2021-2024, works with a critical understanding of energy citizenship that is grounded in state-of-the-art social sciences and humanities (SSH) insights.

EnergyPROSPECTS Energy Citizenship Factsheet Series, Part 9: Aspects of ENCI V.: Contesting the current system

This document is Part 9 of the EnergyPROSPECTS Factsheet Series. We have created the Series to publish the results of a mapping of energy citizenship in Europe, along with the first stage of our analysis of the respective data. The EnergyPROSPECTS consortium mapped 596 cases of energy citizenship (ENCI) between November 2020 and May 2021 using desk research, collecting data on many aspects of the cases. Although the analysis is a work in progress, we believe it is important to share our data and, through doing this, contribute to the understanding of energy citizenship in Europe. EnergyPROSPECTS (PROactive Strategies and Policies for Energy Citizenship Transformation), a H2020 project between 2021-2024, works with a critical understanding of energy citizenship that is grounded in state-of-the-art social sciences and humanities (SSH) insights.

Data deposit accompanying Accurate Energy Barriers for Catalytic Reaction Pathways: An Automatic Training Protocol for Machine Learning Force Fields

Dataset accompanying the paper: "Accurate Energy Barriers for Catalytic Reaction Pathways: An Automatic Training Protocol for Machine Learning Force Fields". Contains the training sets curated during active learning as well as .xyz files used for creating the Figures.  The paper highlights that the computational efficiency of ML force fields not only results in decreased computational costs for routine catalytic investigations but also facilitates more comprehensive exploration of catalytic pathways. Published in NPJ Computational Materials: <a href="https://www.nature.com/articles/s41524-023-01124-2">https://www.nature.com/articles/s41524-023-01124-2</a> Formerly on Arxiv: <a href="https://arxiv.org/abs/2301.09931">https://arxiv.org/abs/2301.09931</a>