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116 results for “Solar cell”
Raw data for Ultrathin wide-bandgap a-Si:H based solar cells for transparent photovoltaic applications
<p>In the following the raw data lying the foundation of the paper “Ultrathin wide-bandgap a-Si:H based solar cells for transparent photovoltaic applications” (Lopez-Garcia et al.) published in Solar Rapid Research Letters, DOI: 10.1002/solr.202100909 (2021), are described. They were obtained under the funding provided by the European Union H2020 Framework Programme under Grant Agreement no. 826002 (Tech4Win) and by the Mater-One (Refs. PID 2020-116719RB-C42 and PID 2020-116719RB-C41) and SCALED (Ref. PID 2019-109215RB-C4) projects funded by the Spanish MCIN/AEI/10.13039/5011000110033.</p> <p>UV–vis measurements were acquired with a dual-beam spectrophotometer setup (Perkin Elmer Lambda L35) in transmittance mode (light source and detector normal to sample’s surface (i.e., 0<sup>o</sup>)) and in reflectance mode (with an Integrating sphere) scanning from 300 to 800 nm.</p> <p>J–V measurements under illumination were carried out using a homemade setup consisting on a AAA solar simulator calibrated using a NREL-certified Si reference solar cell (Abet Technologies, Model 15150). Electrical measurements were carried out with a source-measure unit (Keithley 2400) in four-wire sense mode, controlled by the software Tracer (ReRa solutions) using a IEEE 488 GPIB Instrument Control Device (National Instruments GPIB-USB-HS).</p>
A Comparison of Different Textured and Non-Textured Anti-Reflective-Coatings for Planar Monolithic Silicon-Perovskite Tandem Solar Cells
<p>Figure data for the paper: A Comparison of Different Textured and Non-Textured Anti-Reflective-Coatings for Planar Monolithic Silicon-Perovskite Tandem Solar Cells. Submitted to ACS Applied Energy Materials.</p>
Figure 1 in High Efficiency All-Polymer Solar Cells
Figure 1. – Location (✱) of the catch of Desmodema polystictum in the Northwestern Indian Ocean waters.
Data for device simulation in the article "Analysing the impact of the hole transport layer on the space charge distribution and hysteresis in perovskite solar cells using capacitance-voltage profiling"
<p>This repository contains the data used to perform device simulation in the article "Analysing the impact of the hole transport layer on the space charge distribution and hysteresis in perovskite solar cells using capacitance-voltage profiling", submitted in September 2024 to the journal Sustainable Energy and Fuels.</p> <p><br>The authors of this data and the article are E. Regalado-Pérez, Evelyn B. Díaz-Cruz, and J. Villanueva-Cab </p> <p><br>The scripts (.m) and input files (.csv) hosted here are based on the files created by the authors of the Driftfusion code, which can be found in the GitHub repository "barnesgroupICL/Driftfusion" at https://github.com/barnesgroupICL/Driftfusion.</p> <p> </p>
Raw data for UV-Selective Optically Transparent Zn(O,S)-Based Solar Cells
<p>In the following the raw data lying the foundation of the paper “UV-Selective Optically Transparent Zn(O,S)-Based Solar Cells” (Lopez-Garcia et al.) published in Solar Rapid Research Letters Vol. 4, 2000470, 2020, are described. They were obtained under the funding provided by the European Union H2020 Framework Programme under Grant Agreement no. 826002 (Tech4Win) and by the Basque Country PI2018-08 (PISCES).</p> <p>UV–vis measurements were acquired with a dual-beam spectrophotometer setup (Perkin Elmer Lambda L35) in transmittance mode (light source and detector normal to sample’s surface (i.e., 0<sup>o</sup>)) scanning from 300 to 800 nm.</p> <p>Raman spectroscopy was performed with a FHR640 Horiba Jobin–Yvon spectrometer coupled to a Raman probe developed at Institut de Recerca en Energia de Catalunya (IREC) and a cryogenically cooled charge coupled device detector. Measurements were carried out in backscattering configuration and with a 325 nm UV laser as the excitation wavelength. An excitation power density of about 25W/cm<sup>2</sup> was used to inhibit thermal effects on the samples. The Raman shift was calibrated using a Si monocrystal reference and adjusting the Raman shift for the main Si band at 520 cm<sup>-1</sup>.</p> <p>FE-SEM images were acquired with a ZEISS Auriga Series system. The images were acquired at 5 kV, aperture of 20 μm, and working distance of around 4mm with the InLens detector.</p> <p>J–V measurements under illumination were carried out using a homemade setup consisting on a 150W xenon broadband arc Lamp (Thorlabs SLS401) calibrated using a NREL-certified Si reference solar cell (Abet Technologies, Model 15150). Electrical measurements were carried out with a source-measure unit (Keithley 2400) in four-wire sense mode, controlled by the software Tracer (ReRa solutions) using a IEEE 488 GPIB Instrument Control Device (National Instruments GPIB-USB-HS).</p> <p>EQE curves were obtained using a spectral response system (Bentham PVE300) calibrated with a Si photodiode.</p>
Insights from Transient Absorption Spectroscopy into Electron Dynamics Along the Ga-Gradient in Cu(In,Ga)Se2 Solar Cells: Data
<p>Excel file with data to all figures published in our article found at https://doi.org/10.1002/aenm.202003446 (Advanced Energy Materials), Synopsis user manual, Matlab code to analyse and fit data</p> <p> </p>
Dopant Engineering for Spiro-OMeTAD Hole-Transporting Materials towards Efficient Perovskite Solar Cells
<p>Optoelectronic, photovoltaic, and supplementary characterization data for “Dopant Engineering for Spiro-OMeTAD Hole-Transporting Materials towards Efficient Perovskite Solar Cells”, DOI:10.1002/adfm.202102124</p> <ul> <li>CV.zip: Data (cyclic voltammograms) described in Figures S3–S5 in Origin (*opj) file format.</li> <li>EPR.zip: Data (EPR spectra) described in Figure 5, Figure S2, and Table S2 in Origin (*opj) file format.</li> <li>Optical.zip: Data (UV-vis, PL, and TRPL spectra) described in Figure 4 and Table S1 in Origin (*opj) file format.</li> <li>PV.zip: Data (photovoltaic characteristics) described in the Figures 2–3, Table 1, Figure S1, and Figure S6 in Origin (*opj) file format.</li> </ul>
Dataset for the paper "Low-Cost Three-Quadrant Single Solar Cell I-V Tracer"
<p>Dataset related to the publication "Low-Cost Three-Quadrant Single Solar Cell I-V Tracer" in Applied Sciences 2022, <em>12</em>(13), 6623; <a href="https://doi.org/10.3390/app12136623">https://doi.org/10.3390/app12136623</a></p>
Nanocrystalline Flash Annealed Nickel Oxide for Large Area Perovskite Solar Cells
<p>Dataset supporting the manuscript "Nanocrystalline Flash Annealed Nickel Oxide for Large Area Perovskite Solar Cells" published in Advanced Science (DOI:10.1002/advs.202302549)</p> <p>Datasets are named according to the corresponding figures, with data related to each panel named according to the panel. Further complementary information about the data can be found in the README files.</p>
Perovskite Solar Cells Ageing Dataset
<p>This dataset contains cleaned 2,245 ageing test traces (time vs. MPPT PCE/ maximum power point tracking power conversion efficiency) for perovskite solar cells with various device stacks and architectures in the pickle (.pkl) format.</p> <p>The dataset can be loaded with the following commands on Python.</p> <pre><code class="language-python">import pickle5 as pickle import pandas as pd import numpy as np with open('20230303_mySeriesDrop.pkl', "rb") as fh: mySeriesDrop = pickle.load(fh)</code></pre> <p>The following command can be used to call a specific row (row 0) within the dataset.</p> <pre><code class="language-python">mySeriesDrop[0]</code></pre> <p>The next steps to use the dataset is using scaling/ normalisation (for instance using sklearn.preprocessing.MaxAbsScaler) and smoothing (for instance using Savitzky-Golay filter).</p> <p>The code to run the complete analysis, including self-organising map clustering, can be accessed here: <a href="https://doi.org/10.5281/zenodo.8181602">https://doi.org/10.5281/zenodo.8181602</a>.</p>
Tuning CH3NH3Pb(I1-xBrx)3 Perovskite Oxygen Stability in Thin Films and Solar Cells
<p>The rapid development of organic-inorganic lead halide perovskites has resulted in high efficiency photovoltaic devices. However the susceptibility of these devices to degradation under environmental stress has so far hindered commercial development, requiring for example expensive device encapsulation. Herein, we have investigated the stability of CH3NH3Pb(I1-xBrx)3 [x = 0..1] thin film and solar cells under controlled humidity, light, and oxygen conditions. We show that higher bromide ratios increases tolerance to moisture, with x = 1 thin films being stable to 120 hr of moisture stress. Under light and dry air, partial bromide (x < 1) subsitution does not enhance film stability significantly, with the corresponding solar cells degrading within two hours. In contrast CH3NH3PbBr3 films show excellent stability, with device stability being limited by the organic interlayer. For these x = 1 films we show charge carriers are quenched in the presence of oxygen and form superoxide; however in contrast to perovskites containing iodide, this superoxide does not degrade the crystal. Our observations show that iodide limits the oxygen and light stability of CH3NH3Pb(I1-xBrx)3 perovskites, but that CH3NH3PbBr3 provides an opportunity to develop inherently stable high voltage photovoltaic devices and 4-terminal tandem solar cells.</p>
Ionic Influences on Recombination in Perovskite Solar Cells
<p>Data for our paper: "Ionic Influences on Recombination in Perovskite Solar Cells" <strong>DOI: </strong>10.1021/acsenergylett.7b00490</p>
3D and multimodal X-ray microscopy reveals the impact of voids in CIGS solar cells
<p>Data repository for the article "3D and multimodal X-ray microscopy reveals the impact of voids in CIGS solar cells" <strong>DOI: </strong>10.1002/advs.202301873</p>
Dataset for "Effect of benzothiadiazole-based π-spacers on fine-tuning of optoelectronic properties of oligothiophene-core donor materials for efficient organic solar cells: a DFT study"
<p># Data and code for "Effect of benzothiadiazole-based π-spacers on fine-tuning of optoelectronic properties of oligothiophene-core donor materials for efficient organic solar cells: a DFT study."</p><p>## Contents</p><p>* data-{type}/*: reproducible data</p><p>* job.job : example slurm script</p><p> </p><p>## Description of the data</p><p>The data are organized in subdirectories *data-{type}/{system}/* corresponding to the considered molecules and simulation type:</p><p>* data-gs: Ground state calculations</p><p>* data-td: TD-DFT calculations</p><p>The contents of each subdirectory are:</p><p>* data-gs/{system}/structure.xyz: physical atomic structure</p><p>* data-td/{system}/td-dft/td_uvvis.txt: photoabsorption spectrum</p><p>The spectrum plots in the article correspond to the first (x values) and second (y values) columns of the spectrum files.</p><p> </p><p>## Reproduction of the data</p><p>The data were produced using Gaussian version g16.A.01</p><p>The calculation of the data of a system consists of the following steps:</p><p>1. Ground-state (gs) calculation:</p><p> * Prepare the input file for the gs by adjusting the parameters of the ground state calculations:</p><p> * "# opt b3lyp/6-311+g(d,p) scrf=(smd,solvent=chloroform) geom=connectivity empiricaldispersion=gd3bj out=wfn"</p><p> * out = wfn keyword to create a wfn file of the ground state that will be used for EDD and RDG investigations</p><p> * Submit the job.job file for the gs calculation as appropriate for the particular input file of the system</p><p> * The optimized sturctures are visualised using GaussView</p><p>2. Time-propagation calculation:</p><p> * Requires finished ground-state calculation</p><p> * Set up the TD-DFT calculation parameters as necessary:</p><p> * "# td=(nstates=6) wb97xd/6-311+g(d,p) scrf=(smd,solvent=chloroform) guess=read density out=wfn"</p><p> * density out = wfn keywords to create a wfn file of the excited state that will be used for EDD investigation</p><p> * Submit the job.job file for TD-DFT calculation as appropriate for the particular system</p><p> * The photoabsoption specta are visualised using GaussView</p><p>3. RDG calculation:</p><p> * Put the .wfn file of the gs calculation in the command window of the open source Multiwfn software and follow the sturcture in Section 3.23.1 in the manual</p><p>4. DOS calculation:</p><p> * The dos curves are plotted starting from the .fchk of the ground state geometry, select the atoms index corresponding to the diffrents subpart of the studied molecules (donor, acceptor, pi-spacer)</p><p> * Put the .fchk file of the gs calculation in the command window of the open source Multiwfn software and follow the structure in Section 4.10.1 in the manual</p><p> * the output generates .chk file which is transformed to .fchk file : formchk .chk .fch</p><p>5. TDM calculations:</p><p> * Requires finished ground-state calculation</p><p> * Set up the TD-DFT calculaton parameters as necessary</p><p> * "# td=(nstates=6) wb97xd/6-311+g(d,p) scrf=(smd,solvent=chloroform) guess=read density transition=1 iop(6/8=3) out=wfn"</p><p> * Put the .fchk file of the gs calculation in the command window of the open source Multiwfn software and follow the sturcture in Section 4.18.8 in the manual</p><p>6. EDD calculation:</p><p> * Edd plots are plotted based on the es.wfn and gs.wfn following Section 4.18.1 in the manual</p><p> </p>
Accelerated Perovskite Solar Cells Ageing Dataset
<p>The dataset contains accelerated ageing test traces (time vs. MPPT PCE/ maximum power point tracking power conversion efficiency) for perovskite solar cells with SAM (self-assembled monolayer)-based and NiOx-based hole transport layers at various temperatures in .csv format.</p> <p>The next step to process and analyze the data, can be accessed here: https://github.com/noortitan/AcceleratedCyclePSCs/.</p>
Dataset for "Understanding Wavelength-dependent Synergies between Morphology and Photonic Design in TiO2-based Solar Powered Redox Cells"
Open the record for dataset details and reuse information.
Supporting molecular simulations data for "Pseudo-halide anion engineering for α-FAPbI3 perovskite solar cells"
<p>Supporting molecular simulations data for "Pseudo-halide anion engineering for α-FAPbI3 perovskite solar cells"</p>
Wind and solar capacity factor time series by year and grid cell over the contiguous U.S.
<p>This data set contains hourly capacity factor time series of wind and solar resources over the contiguous U.S.</p> <p> </p> <p>The included time series cover four individual years and 2,586 grid cells. The years range from 2016 to 2019. The grid cells correspond to the grid cells of the NASA's MERRA-2 reanalysis data set into which the contiguous U.S. is subdivided. The grid cells have a spatial resolution of 0.5° latitude x 0.625° longitude with dimensions ranging from about 55 km x 45 km to 55 km x 62 km.</p> <p> </p> <p>This data set is used to generate the results of the following journal article:</p> <p>Enrico G. A. Antonini, Tyler H. Ruggles, David J. Farnham, Ken Caldeira, "The quantity-quality transition in the value of expanding wind and solar power generation", iScience 25 (4), 104140, 2022.</p> <p> </p> <p>Code and instructions required to reproduce the results reported in the above paper are available in the GitHub repositories at <a href="https://github.com/eantonini/Distributed_wind_and_solar_generation">https://github.com/eantonini/Distributed_wind_and_solar_generation</a> and <a href="https://github.com/carnegie/MEM_public/tree/Antonini_et_al_2022">https://github.com/carnegie/MEM_public/tree/Antonini_et_al_2022</a>.</p>
Interfacial host–guest complexation for inverted perovskite solar cells
<p><span>Characterisation dataset for “Interfacial host–guest complexation for inverted perovskite solar cells</span><span>”</span><span>, doi:10.1063/5.0202163, including data for main and supporting figures provided as image (*.png, *.tiff, and *.svg), Origin (*.opju) and *.txt files. </span><span>NMR data is provided by the TopSpin software, which is available from Bruker.<span> </span></span></p>
Exploring the potential of biphenylamine and triphenylamine-based sensitizers for enhanced efficiency more than 8% in dye-sensitized solar cells
<p>Due to the world's rapidly expanding population and industrial sector, which raises the demand for energy, solar cells can address both global energy and environmental needs. With the aim to enhance the dye-sensitized solar cell (DSSC) efficiency, we designed four metal-free BPA and TPA-based dyes (RK2-RK5) by increasing the donor strength (substituting different groups such as biphenylamine (BPA) and triphenylamine (TPA) in the donor side of the dye) based on the reference dye (RK1) as such dye showed improved DSSC's power conversion efficiency. Density functional theory (DFT) was applied at the B3LYP/6-31G** level to calculate the ground-state (S<sub>0</sub>) optimized geometries of (RK1-RK5). Time-dependent DFT (TD-DFT) was utilized to compute the absorption spectra utilizing four functionals (B3LYP, CAM-B3LYP, PBE1PBE and BHandHLYP) in gas phase and solvent such as dichloromethane (DCM) and ethanol. The comprehensive analysis of RK1-RK5 as well as dyes@TiO<sub>2</sub> was performed, and light was shed on the optoelectronic properties. Frontier molecular orbitals' (FMOs') charge density distribution revealed the sensitizers' intramolecular charge transfer (ICT) from the donor to the acceptor moiety. After adsorption charge transfer was noticed from sensitizer to the TiO<sub>2</sub> semiconductor's surface in dyes@TiO<sub>2</sub>. Dyes adsorption on the TiO<sub>2</sub> cluster would be stable, as revealed by the dyes@TiO<sub>2</sub> cluster's negative binding energy. Additionally, it was found that double donor raises the electronic coupling and electron injection constants in RK4 and RK5, indicating that the charge injection in these newly designed dyes would be superior. As a result, the DSSC efficiency in newly designed derivatives has been improved to 8.05% for RK5 by substituting TPA unit at R1 and R2 position in parent compound. These well-established correlations between structure-property relationship, and performance provide profound insight into how improving the donor moiety strength in organic sensitizers affects device performance. It boosted photovoltaic performance through enhanced short-circuit current density, and light-harvesting efficiency. For high-efficiency in DSSCs, it can be a useful rational molecular designing strategy for D-π -A organic sensitizers.</p>
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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.