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4,230 results for “Energie”
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>
Data Set For Efficient Calculation of Dispersion Energy for Multireference Systems with Cholesky Decomposition. Application to Excited-state Interactions
<p>Data Set to Accompany:</p> <p>"Efficient Calculation of Dispersion Energy for Multireference Systems with Cholesky Decomposition. Application to Excited-state Interactions"</p>
Datasets for ``Electromagnetic conversion into kinetic and thermal energies''
<pre>This directory contains an index.html file with links to the run directories and idl plotting routines with secondary data for the other figures for the paper "Electromagnetic conversion into kinetic and thermal energies" by A. Brandenburg and N. Protiti. If anything turns out to be incomplete, please email brandenb@nordita.org. </pre>
Input files for the MD simulations and free energy calculations for the article "Water Dissolved in a Variety of Polymers Studied by Molecular Dynamics Simulation and a Theory of Solutions"
<p>Article:<em> </em><a href="https://pubs.acs.org/doi/10.1021/acs.jpcb.1c04818">J. Phys. Chem. B. 125, 9357–9371 (2021) [DOI: 10.1021/acs.jpcb.1c04818]</a></p> <p>The structures of the homopolymers and copolymers simulated are shown in Figures 1 and S1 and Tables 2 and 3. All-atom MD simulation was carried out using GROMACS, and this repository provides the input files with the GAFF/RESP force and initial coordinate files. The free energy of water dissolution was obtained with <a href="https://sourceforge.net/projects/ermod/">ERmod</a>, and the input files for the free-energy calculations are also contained. See the README files for details.</p>
Analysing the effects of 24/7 Carbon-free Energy procurement strategies on the electricity system
<p>This dataset contains results of simulations performed as part of a master's thesis project at Kungliga Tekniska Högskolan (KTH) in Stockholm, Sweden.</p> <p>Title: Analysing the effects of 24/7 Carbon-free Energy procurement strategies on the electricity system. <em>Case Study of </em><em>commercial and industrial</em><em> sector in the Netherlands</em></p> <p>Programme: Sustainable Energy Systems, spec. Combined Energy Systems.</p> <p>Part of EIT InnoEnergy double master's degree SELECT programme.</p>
Benthic d18O records Earth's energy imbalance
<p>Data include previously published data that were used to produce reconstructions of global energy anomalies and Earth's energy imbalance, as well as the aforementioned reconstructions. Previously published data include 1) a global reconstruction of benthic d18O for the last 150,000 years, 2) ice core noble gas - based reconstructions of mean ocean temperature and the atmospheric noble gas ratios used for these reconstructions for the last 25,000 years, and 3) two eustatic sea level reconstructions from coral and tidal indicators combined with glacio-isostatic adjustment models for the last 25,000 years. From these previously published data we derive 1) the estimated contributions of temperature (or the equilibrium isotope effect) and ice volume (or d18O of seawater) to the total benthic d18O signal, 2) reconstructions of global energy change, and 3) reconstructions of Earth's energy imbalance.</p>
Figures 2–5 in One size doesn′t fit all: Singularities in bat species richness and activity patterns in wind-energy complexes in Brazil and implications for environmental assessment
Figures 2–5. Bat activity based on the pooled number of echolocation pulses per hour in four wind-energy complexes in northeastern Brazil, from September 2015 to January 2017: (2) Curva dos Ventos, municipality of Caetité, state of Bahia; (3) Cristal, municipality of Morro do Chapéu, state of Bahia; (4) Modelo, municipality of João Câmara, state of Rio Grande do Norte; (5) Fonte dos Ventos, municipality of Tacaratu, state of Pernambuco.
Figure 1 in One size doesn′t fit all: Singularities in bat species richness and activity patterns in wind-energy complexes in Brazil and implications for environmental assessment
Figure 1. Wind-energy complexes in northeastern Brazil studied for the presence and activity of insectivorous bats from September 2015 to January 2017.
Figures: Vortex model of the aerodynamic wake of airborne wind energy systems
<p>Figures in .pdf, .png and .fig format.</p><p>Figures in .fig format can be opened with MATLAB or other open source programming languages (e.g., Python thought the command scipy.io.loadmat or Octave)</p><p>Figures were updated after: Trevisi, F., Croce, A., and Riboldi, C. E. D.: Corrigendum to "Vortex model of the aerodynamic wake of airborne wind energy systems", published in Wind Energ. Sci., 8, 999–1016, 2023, https://doi.org/10.5194/wes-8-999-2023-corrigendum"</p>
Scripts and datas for "Global Estimation of the Eddy Kinetic Energy Dissipation from a Diagnostic Energy Balance"
<p>Input and output datasets used for a global reconstruction of the eddy kinetic energy (EKE) dissipation rate in relation to a submitted work :</p> <p><strong>R. Torres, R. Waldman, J. Mak and R. Séférian </strong>: <em>Global Estimation of the Eddy Kinetic Energy Dissipation from a Diagnostic Energy Balance</em>.</p> <p>Inputs datas include a merge of 2 datasets from the World Ocean Atlas 2018 (WOA18, Garcia et al., 2019) and cover the 1995-2017 (95B7) period. Folder structure for the surface altimetry L4 datasets from the EU-Copernicus Marine Services (2021) is kept empty in order to limit the archive size. Datas can be download <a href="https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_L4_MY_008_047/services">here</a>.</p> <p>Optional datasets include CMEMS MDT product (<em>CMEMS/SEALEVEL_GLO_PHY_MDT_008_063/P20Y</em>) downloaded <a href="https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_MDT_008_063/">here</a> and ocean masks (<em>misc/basins/doi_10.5281</em>) from Martinez-Moreno et al. (2021).</p> <p>In addition, simulation outputs from the NEMO-OMIP2 model runned with the GEOMETRIC parameterization are processed (mainly time-averaged) and stored in <em>CNRM/runs/omip2_LR.Geom_Emin0-alpha01_1cyc-trd/post</em>. These files are used in the uncertainties and errors quantification.</p> <p>Outputs and published results are stored in each individual product post-processing folder while final EKE dissipation computation are located in the <em>EKE_dissipation_rate</em> folder since it results from a combination of multiple products.</p> <p>IPython notebooks for computing and plotting global maps are also provided :</p> <ul> <li><em>1-post_process_climato.ipynb</em> : compute from the climatology (e.g. WOA18 datas) the EKE dissipation timescales (units in days) and the surface modes with rough topography (LaCasce and Groeskamp, 2020).</li> <li><em>2-post_process_altimetry.ipynb</em> : compute from altimetry (CMEMS) datasets the EKE at surface and eventually coarsen the grid from 0.25 to 1 degree in order to match the climatology grid.</li> <li><em>3-compute_global_eke_dissipation.ipynb</em> : combine both outputs from the two above scripts to compute the global EKE dissipation. The script also plots new maps.</li> <li><em>0-plot_global_maps.ipynb</em> : plot the global maps for climatology and altimetry products.</li> <li><em>0-plot_lbekedis_ogcm.ipynb</em> : plot and analyse EKE timescale errors from the NEMO-OMIP2 simulation outputs.</li> </ul> <p>Note however that these scripts use the author python library XOCE availbale on GitHub: https://github.com/torresr-cnrm/xoce. All the scripts have been runned using the version 0.2 of XOCE. Feel free to contact (romain.torres@meteo.fr) for any help in installing and using this library.</p>
Fish can use coordinated fin motions to recapture their own vortex wake energy
<p>This data repository includes all the fish swimming data and metadata used to investigate how fish can recapture their own wake to improve swimming efficiency. Custom Matlab scripts developed to compute kinematics, pressure fields, and forces are available here.</p> <p><strong>Matlab scripts:</strong> The custom Matlab scripts developed to compute and analyze kinematics, velocimetry, pressure, and force data are in separate folders, including the master script and secondary functions. Pressure calculations from PIV data use the queen2 Matlab package available at ( <a href="http://dabirilab.com/software">http://dabirilab.com/software</a>).</p> <p><strong>Respirometry data (supplementary data): </strong>We provide the oxygen consumption data used in statistical analysis of the COT of each specimen in separate sheets in a single xlsx file. In addition to raw oxygen consumption data, each sheet includes metadata relative to experimental conditions and the magnitude of the relative flow speeds in body length per second tested during steady swimming trials. We also provide the rpm to flow velocity calibration used with our flume. Scaled original pictures of the fish used for respirometry experiments are available in .jpg format and include morphological information such as standard body length (BL) and fork length.</p> <p><strong>PIV data:</strong> High-resolution videos and velocity fields computed using DaVis are sorted by fish specimen and swimming speed. Additional metadata relative to the fish and experimental parameters (i.e., salinity, temperature) are included. Scaled original pictures of the fish used to conduct top-down PIV experiments are available in .jpg format and include morphological information such as standard body length (BL) and fork length.</p>
Machine Learning-based Energy Optimisation in Smart City Internet of Things
<p>Dataset for the paper Machine Learning-based Energy Optimisation in Smart City Internet of Things accepted for publication at The First International Workshop on the Integration between Distributed Machine Learning and the Internet of Things, ACM MobiHoc 2023.</p> <p>The dataset is collected from a real-world deployment of environmental sensors in the city of Bern, Switzerland. Our proposed approach can be applied to determine the tradeoff between the accuracy of temperature measurements and reducing the energy consumption for a single sensor; hence, without loss of generality, the evaluation is conducted on a dataset from a single sensor. Overall, we acquired 3697 measurements, each long 138 seconds. To correct the measurements, we set the maximum ventilation duration of 138 seconds, during which the multivariate time series of humidity and temperature sensor values are recorded together with their corresponding timestamps. The sensor values are recorded at a fixed frequency.</p> <p>From this raw data, we created the training and test sets through data augmentation to simulate time series of different lengths. Namely, for each measurement, we generated 136 samples with the increasing length of measurement time-series, padding the residual time-series length with zeros until reaching a time-series length of 137.</p> <p>We released the source code and trained models on the following GitHub repository https://www.github.com/ricsamikwa/ml-iot-smartcitytemp</p>
Plane waves versus correlation-consistent basis sets: A comparison of MP2 non-covalent interaction energies in the complete basis set limit
<p>Supporting data and analysis scripts for the work</p> <p><a href="https://doi.org/10.26434/chemrxiv-2023-203z9">Plane waves versus correlation-consistent basis sets: A comparison of MP2 non-covalent interaction energies in the complete basis set limit</a></p>
Why The Perfectly Symmetric Cobalt-Pentapyridyl Loses the H2 Production Challenge: Theoretical Insight into Reaction Mechanism and Reduction Free Energies
<p>Abstract</p> <p>Researchers have extensively investigated photo-catalytic water reduction utilizing Cobalt-based catalysts with poly-pyridyl ligands. While catalysts exhibiting distorted poly-pyridyl ligand demonstrate higher H2 production yields, those with ideal octahedral coordination display poor performance. This outcome suggests the crucial role of ligand framework in catalytic activity, yet reasons behind the disparity in H2 production rates for catalysts with octahedral geometries remain unclear. We theoretically examined the water reduction mechanism of Co-based poly-pyridyl catalyst, CoPy5, having perfect octahedral coordination. We clarified the effect of octahedral coordination by utilizing each intermediate step of ECEC mechanism. We determined spin states, solvent response, electronic structures, and reduction free energies. CoPy5 with perfect octahedral coordination, alongside its distorted counterparts, exhibit similar spin states as the reaction progresses through each intermediate step. However, the first reduction free energy obtained for the CoPy5 is slightly higher than that of its distorted counterparts. Following the second protonation, resulting H2 molecule experiences limited diffusion from the Co center due to the compact structure of the CoPy5, which blocks the Co center for the next H2 production cycle. Catalysts having distorted octahedral geometries facilitate fast removal of H2 into the solvent. Thus, the reaction center becomes immediately available for subsequent H2 production.</p> <p>Computational Details</p> <p>AIMD simulations have been performed for modeling intermediate states of the ECEC mechanisms of H2 production through water splitting. Open source CP2K simulation package have been used in all simulations. PBE density functional in general gradient approximation (GGA) formalism was employed for the AIMD simulations. Goedecker-Teter-Hutter (GTH) potentials were applied for the estimation of core electron interactions with the valence shell and nucleus. Valence electrons were modeled explicitly and valence shells of Co, N, C, O and H contain 17, 5, 4, 6 and 1 electrons, respectively. DZVP-MOLOPT basis set was used for all atomic kinds. For auxiliary plane wave basis set, a cutoff of 400 Ry was utilized. Dispersion interactions were taken into consideration by applying Vydrov and Van Voorhis vdW density functional, in the revised form (rVV10). Periodic boundary<br> conditions and spin polarization were always applied. For the CoPy5 complex, AIMD simulations were carried out in a box defined as cubic with explicit water environment. The CoPy5 catalyst was first solvated in 215 water molecules and the simulation volume was relaxed by performing AIMD simulations for approximately 20 ps in the isothermal-isobaric ensemble (NPT). Cubic simulation box volume was determined as 6163.28 ̊A3. Following the determination of the simulation box size, each intermediate step were modeled by applying AIMD simulations in the canonical ensemble (NVT) for approximately 20 ps. Time step was set to 0.5 fs. Canonical sampling through velocity rescaling (CSVR) thermostat with a time constant of 100 fs was applied in order to keep<br> the simulation temperature at 300 K.</p> <p>Please see the corresponding article for more details.</p>
Data and code for "Revealing the free energy landscape of halide perovskites: Metastability and transition characters in CsPbBr3 and MAPbI3"
<p>This record contains a neuroevolution potential (NEP) model (<code>nep-MAPI-SCAN.txt</code> ) for MAPbI3 used in the linked publication. The model can be used in conjunction with the <a href="https://gpumd.org">GPUMD package</a>. The <a href="https://calorine.materialsmodeling.org">calorine package</a> provides a Python interface to GPUMD.<br> Several primitive structures in extended xyz format can be found in the <code>*.xyz</code> files. These structures have been relaxed using the NEP model included here. The <code>demo-for-using-structures-and-model.py</code> script illustrates how to access the structures and model.</p>
Indian energy: Archive materials
<p>This collection houses a number of reports and datasets concerning India's energy situation. In many cases these reports have been difficult to obtain, so I am releasing them here to make similar work easier for others. Note that many of the PDF documents here have already been scraped, and key data are available in machine-readable format here: <a href="https://robbieandrew.github.io/india/">https://robbieandrew.github.io/india/</a></p> <p>The collection includes:</p> <ul> <li>Monthly reports by the Ministry of Coal to Cabinet, from April 2015</li> <li>Monthly summary reports by the Ministry of Coal to Cabinet, from September 2014</li> <li>Monthly statistical reports by the Ministry of Coal to Cabinet, from April 2020</li> <li>Coal India Ltd's monthly reports, from February 2013</li> <li>SCCL's monthly reports, from April 2016</li> <li>Energy Statistics Yearbooks, from 2007</li> <li>Monthly Gas reports from PPAC, from December 2015</li> <li>Annual Provisional Coal Statistics reports, from 2005-06</li> <li>Annual Coal Directory reports, from 2007-08</li> <li>Monthly trade by principal commodities from DGCIS, from April 2004</li> <li>CEA annual reports, from 2010</li> <li>CEA daily renewable generation reports, from January 2021</li> <li>CEA monthly OPM01 reports, from January 2008</li> <li>CEA monthly OPM16 reports, from January 2008</li> <li>CEA monthly Executive Summary reports, from January 2006</li> <li>CEA daily DGR17 reports, from January 2013 (there are gaps)</li> </ul> <p>The collection is grouped into ZIP archives, and within each ZIP archive the files are named to indicate the time period to which they apply. This might be the fiscal year, such as "2012-13", or the month in YYYYMM format, such as "200110".</p> <p>Related datasets:</p> <ul> <li>"Background data for: Timely estimates of India's annual and monthly fossil CO2 emissions" <a href="https://doi.org/10.5281/zenodo.3894394">https://doi.org/10.5281/zenodo.3894394</a></li> <li>"Monthly, state-level electricity generation (from 2007) and capacity (from 2008) in India: Thermal, Natural Gas, Nuclear, and Large Hydro" <a href="https://zenodo.org/record/4542834">https://zenodo.org/record/4542834</a></li> </ul> <p> </p>
Optimization procedure of low frequency vibration energy harvester based on magnetic levitation: Datasets and scripts
<p>****** Please view the README.txt file for detailed documentation of data. ******</p> <p> </p> <p>Title: Optimization procedure of low frequency vibration energy harvester based on magnetic levitation: Datasets and scripts<br>Version: 2.0<br>Date of Release: 2023/08/23<br>Identifier: doi:10.5281/zenodo.8317223<br>Permalink: http://dx.doi.org/10.5281/zenodo.8317223</p> <p><br>Associated publication: I. Royo-Silvestre, J. J. Beato-López, C. Gómez-Polo "Optimization procedure of low frequency vibration energy harvester based on magnetic levitation", Applied Energy, Volume 360, 15 April 2024, 122778</p> <p>Link to publication: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.apenergy.2024.122778" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.apenergy.2024.122778</span></a></p> <p><br>Suggested citation: Please reference the associated publication above when using any datasets or materials described in the README file.</p> <p> </p> <p>Contact information: Isaac Royo Silvestre, Universidad Pública de Navarra, Pamplona, Spain., isaac.royo@unavarra.es<br>Co-authors: juanjesus.beato@unavarra.es, gpolo@unavarra.es</p> <p> </p> <p>Dates of data collection: 2023/03<br>Geographic location: Pamplona, Spain</p> <p> </p> <p>This directory contains the following datasets and scripts:</p> <p>SCRIPTS</p> <p>- harvester_op.m: Matlab script to automate the design and optimize a magnetic spring based vibration energy harvester (more information in the associated paper)</p> <p>- harvester_op_par.m: Matlab script, a version of harvester_op.m modified for parallel computing and shorter execution time in multicore computers (file added in v 2.0 of the data upload).</p> <p>DATASETS<br>- data.zip: Experimental data recorded by the datalogger as well as tabular data required to plot curves (compressed zip file) in csv format</p> <p> </p> <p>Specific documentation of each file is described in readme files.</p> <p> </p> <p>Refer to the original manuscript (see above) and the text of the Supplementary Materials published alongside this manuscript for additional information regarding the collection and generation of these data.</p>
Norway energy policy optimization results
<p>These files contain the raw results from master thesis on Norwegian energy policy directions. The each folder has a html file (with basic plots), a netcdf file and a series of csv files. The four scenarios uploaded are the unconstrained (model is free to install capacity as it wants) and base case (current norwegian policy direction), for both a beyond 2030 and beyond 2050 timeline. These results are part of a Master thesis work. Additional results related to transmission and onshore wind policy available upon request to h.guddingsmo@outlook.com.</p>
Artifact Description/Artifact Evaluation/Computational Artifact for "SPEChpc 2021 Benchmarks on Ice Lake and Sapphire Rapids Infiniband Clusters: A Performance and Energy Case Study"
<p>We provide reproducibility initiative dependencies (Artifact Description or Artifact Evaluation or Computational Results Analysis) appendix at https://github.com/RRZE-HPC/PMBS23-AD. To allow a third party to duplicate the findings, this article provides our extensive performance data artifact and describes further details regarding the software environments, experimental design, and methodology employed for the results shown in the paper, entitled "SPEChpc 2021 Benchmarks on Ice Lake and Sapphire Rapids Infiniband Clusters: A Performance and Energy Case Study". The computational artifacts will enable experienced performance engineers to reproduce and interpret the data shown in the paper in the appropriate way and to follow the conclusions we draw from it.</p>
The potential impact of climate change on European renewable energy droughts
<p>The file contains a supplementary material for an article entitled <em>The potential impact of climate change on European renewable energy droughts</em> (currently under review):</p> <p>The projected change of the total number of drought days for a wind, solar and hybrid generator in relation to the reference period as predicted by the models considered</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.