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308 results for “Electronic structure”
Dataset of "Electronic structure and defect states in bismuth and antimony sulphides identified by energy-resolved electrochemical impedance spectroscopy"
Understanding the nature of the defects in the absorber materials, namely point defects, their formation mechanism and the contribution to the properties is essential for the photovoltaic device performance improvement. They are one the reasons why chalcogenide-based solar cells do not yet meet expected high power conversion efficiencies. Here we identify and present energy distribution of defects in Bi2S3 and Sb2S3, and their (SbxBi(100-x))2S3 alloys (with x = 0, 10, 33, 50, 67, 90, 100 at% Sb content) chalcogenides, being explored for emerging photovoltaic applications as they are earth-abundant and highly absorbing in the visible light range. We show that their density of states (DOS) and related parameters can be obtained experimentally by energy-resolved electrochemical impedance spectroscopy (ER-EIS) in a technically simple and quick way, where ER-EIS data are well correlated with theoretical DFT calculations. ER-EIS reveals that in Bi2S3 there are only shallow defects at CBM. In Sb2S3, ER-EIS reveals also midgap states which can be the cause of low electrical conductivity of Sb2S3. We also explain the discrepancy in the reported values of ionisation potentials and the bandgaps of the Bi- and Sb-chalcogenides. Dominant sulphur vacancy defect was identified in Bi- and Sb-chalcogenides whereas in ternary (SbxBi(100-x))2S3 system, merely 10 at.% of Bi transforms the midgap sulphur defects to shallow ones. This provides novel strategy for healing the midgap defects in Sb2S3, which is crucial for boosting the PV performance and tuning the electrical conductivity in Sb2S3.
Dataset of "Sensitivity analysis in photodynamics: How the electronic structure controls cis-stilbene photodynamics?"
<p>The techniques of computational photodynamics are increasingly employed to unravel reaction mechanisms and interpret experiments. However, inaccuracies in nonadiabatic dynamics can lead to misinterpretations, particularly when calculated observables exhibit low sensitivity to the underlying dynamics. This issue is exemplified in the photochemistry of cis-stilbene, where similar experimental outcomes have been differently interpreted based on the electronic structures supporting nonadiabatic dynamics. This study examines the predictions of cis-stilbene photochemistry using trajectory surface hopping methods coupled with various electronic structures (OM3-MRCISD, SA2-CASSCF, XMS-SA2-CASPT2, and XMS-SA3-CASPT2) and assesses their ability to interpret experimental observations. Although the excited-state lifetimes show consistency, ranging from 360 fs to 295 fs, the reaction quantum yields vary significantly. The quantum yield for cyclization ranges from nearly zero to 35% while the photoisomerization channel can either exceed 50% or be entirely suppressed completely in the second case. Intriguingly, the calculated photoelectron signal is not strikingly different for different reaction scenarios, making the methods seemingly reliable when treated separately Furthermore, analyzing stationary points on the potential energy surface does not reliably predict simulation outcomes, nor does it aid in selecting a specific method before simulations. Therefore, we advocate for incorporating sensitivity analyses in the simulation protocol. While employing an ensemble of methods is impractical, nonadiabatic simulations with external bias present a resource-efficient approach to achieve this goal.</p>
Rapid structure determination of microcrystalline molecular compounds using electron diffraction (nanoArgovia Project A3EDPI)
<p>The are the data linked to the publication "Rapid structure determination of microcrystalline molecular compounds using electron diffraction", <a href="https://doi.org/10.1002/anie.201811318">10.1002/anie.201811318</a>. Electron Diffraction data collected with an EIGER X 1M detector (DECTRIS Ltd.).</p> <p>Each tar file contains the raw files in HDF5 format, together with the XDS.INP file used for data integration. Images of the respective crystals have '_img_' in their file names. The log files for recording the stage alpha angle are included with the same name and suffix .txt. See publication for details.</p> <p>NB: The meta-data in the HDF5 files have no meaning, please refer to the respective XDS.INP file for respective information.</p> <p>The crystallographic data (CIF-files) have been uploaded to the ICSD (High--throughput Structural Chemistry with Electron Diffraction) and CSD (https://www.ccdc.cam.ac.uk/) respectively:</p> <p>Paracetamol from Grippostad CCDC 1856579<br> electron structure of MBBF4 CCDC 1856580</p> <p>ZSM-5 x227 CSD 1856581</p> <p>ZSM-5 x331 CSD 1856582</p> <p>ZSM-5 x79 CSD 1856583<br> ZSM-5 x811 CSD 1856584</p> <p> </p>
Quantitative electronic structure and work-function changes of liquid water induced by solute - data
<p>Data set pertaining to the article "Quantitative electronic structure and work-function changes of liquid water induced by solute" | Physical Chemistry Chemical Physics, 24, 1310 (2022).</p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard v2022.07 using the NXmpes user contributed format suggested by the Fairmat consortium, see<br> https://www.nexusformat.org/<br> https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html<br> A few extensions specific to liquid jet-experiments were added to the standard, and are explained in the notes-group on the top level of each file.<br> NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br> * nexpy (distributed with python)<br> * https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are shown:<br> 1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data').<br> 2. As-measured data ('raw').</p> <p>Files with extension .txt are comma-separated ascii-files.<br> The following files are provided:</p> <p>Photoemission data pertaining to solute measurements using the cut-off as energy reference:<br> NaI_data.h5<br> tbai_data.h5</p> <p>Biased spectra were typically recorded in the following order:<br> [cut-off (fine), cut-off (coarse), (valence band)*(N repeats)]*(M repeats)<br> To avoid the saving of overly complex hdf5-files, these data were saved in a different order, namely:<br> [cut-off (fine)*(M repeats), cut-off (coarse)*(M repeats), (valence band)*(N*M repeats)].</p> <p>Numeric representations of the traces shown in the article's figures:<br> Figure_1a-data.txt<br> Figure_1b-data.txt<br> Figure_2a-data.txt<br> Figure_2b-data.txt<br> Figure_2c-data.txt<br> Figure_3-data.txt<br> Figure_4-data.txt<br> Figure_5a-data.txt<br> Figure_5b-data.txt<br> Figure_6a-data.txt<br> Figure_6b-data.txt<br> Figure_6c-data.txt<br> Figure_7_diff_spectra-data.txt<br> Figure_8-data.txt</p> <p>Traces shown in several figures are included only in the data file pertaining to the figure in which they occur first.</p> <p> </p> <p>Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
Unveiling the atomistic and electronic structure of NiII–NO adduct in a MOF-based catalyst by EPR spectroscopy and quantum chemical modelling
<p><strong>Description of the dataset: </strong></p> <ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements, computer simulation and analysis</li> <li>Files are with filename extensions: <strong>DSC</strong>, <strong>DAT</strong>, <strong>m</strong>, <strong>txt</strong></li> <li>Information on <strong>origin of the data</strong>:</li> </ul> <ul> <li>EPR spectroscopic measurements with filename extensions <strong>DSC</strong>, <strong>DTA.</strong></li> <li>EPR spectroscopic simulation and analyses with filename extension <strong>m</strong>.</li> <li>EPR spectra are exported as <strong>txt</strong> files in ASCII format.</li> </ul> <ul> <li>X-band CW-EPR spectroscopic measurements were generated by EMX spectrometer equipped with SHQ cavity produced by Bruker.</li> <li><strong>If the dataset includes multiple files that relate to each other:</strong> <ul> <li>Files in <strong>PARACAT_WP4_20230706_01_CW_Xband </strong>folder includes X-band CW-EPR spectroscopic measurements; original data are in DTA/DSC and txt formats.</li> <li>Files in <strong>PARACAT_WP4_20230706_02_HYSCORE </strong>and <strong>PARACAT_WP4_20230706_03_ENDOR </strong>folders include X-band HYSCORE and ENDOR data; original data are in DTA/DSC and txt formats.</li> <li>Files in <strong>PARACAT_WP4_20230706_ 04_MATLAB</strong> and<strong> PARACAT_WP4_20230706_ 05_Modelling</strong> folders include matlab and computer simulations/analyses of the EPR measurements; data are in m and txt formats.</li> <li>File <strong>PARACAT_WP4_20230706_ 06_Origin</strong> include origin plotted data</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>Information on</strong>: <ul> <li>specialized abbreviations: <strong>MFU– </strong>MFU-4l:NO<sub>2</sub> MOF material</li> <li>NiNO – NO adsorbed MFU-4l:NO<sub>2</sub> MOF</li> <li>@10K – measured at 10 K</li> <li>definitions of variables: <strong>Magnetic field, Temperature.</strong></li> <li>units of measurement: <strong>Gauss (G), K, degree (°), milliTesla (mT)</strong>.</li> </ul> </li> </ul>
Research Data Supporting "Understanding Structural and Electronic Properties of Bismuth Trihalides and Related Compounds"
<p>Research Data Supporting "Understanding Structural and Electronic Properties of Bismuth Trihalides and Related Compounds"</p> <p>DOI: 10.1021/acs.inorgchem.9b03214</p>
Dataset: Electronic Spectra of Ytterbium Fluoride from Relativistic Electronic Structure Calculations
<p>This is the dataset for the manuscript entitled: "Electronic Spectra of Ytterbium Fluoride from Relativistic Electronic Structure Calculations" by J. V. Pototschnig, K. G. Dyall, L. Visscher and A. S. P. Gomes. It contains output files of various calculations and scripts to process them.</p>
Dyall dz, tz, and qz basis sets for relativistic electronic structure calculations
<p>This archive contains the Dyall basis sets for relativistic atomic and molecular electronic structure calculations. They are given in the format required by the DIRAC program (see <a href="http://diracprogram.org">diracprogram.org</a>), which is essentially a list of the exponents for each angular momentum for each element. The basis sets are of double-, triple-, and quadruple-zeta quality. For each quality, there are three basis set types: valence (v<em>N</em>z), core-valence (cv<em>N</em>z) and all-electron (ae<em>N</em>z). These basis sets include correlating functions for the relevant shells (valence, valence+outer core, all shells). In addition, for each of these basis sets there is another set that contains diffuse functions for the s, p, and d elements, optimized for the anion or extrapolated from neigboring elements where the anion is unbound or weakly bound. These sets are labeled av<em>N</em>z, acv<em>N</em>z, and aae<em>N</em>z. References for the basis sets are included in the basis set files.</p> <p>The archive files containing descriptions and recommendations for each basis set, as well as SCF coefficients and lists of exponents, are available <a href="https://doi.org/10.5281/zenodo.7606546">here</a>.</p>
Background optimization of powder electron diffraction to implement e-PDF technique and study the local structure of iron oxide nanocrystals
<p>The local structural characterization of iron oxide nanoparticles is explored using a total scattering analysis method known as Pair Distribution Function (PDF) (also known as Reduced Density Function) profiles derived from background corrected powder electron diffraction patterns. Due to the strong coulombic interaction between the electron beam and the sample, electron diffraction generally leads to multiple scattering, causing redistribution of intensities towards higher scattering angles and an increased background in the diffraction profile. In addition to this, the electron-specimen interaction gives rise to an undesirable inelastic scattering signal that contributes primarily to the background. The present work demonstrates the efficacy of a pre-treatment of the underlying complex background function, which is a combination of both incoherent multiple and inelastic scatterings that cannot be identical for different electron beam energies. Therefore, two different background subtraction approaches are proposed for the electron diffraction patterns acquired at 80 kV and 300 kV beam energies. From the least square refinement (small-box modelling), both approaches are found to be very promising, leading to a successful implementation of the e-PDF technique to study the local structure of the considered nanomaterial.</p>
A small dataset for analyzing spectroscopic parameters from low-cost electronic structure methods
<p>This dataset comprises two files: `lee_bayesian_dataset.csv` and `raw_outputs.tar.xz`. The former corresponds to an aggregated table of data used for subsequent analysis, and the latter are raw output files from Gaussian '09. This dataset corresponds to 6916 calculations of 76 representative molecules with high-resolution gas-phase rotational constants.</p> <p> </p> <p>This version corresponds to the data used for our publication:</p> <p>Bayesian Analysis of Theoretical Rotational Constants from Low-Cost Electronic Structure Methods</p> <p>https://pubs.acs.org/doi/10.1021/acs.jpca.9b09982</p>
Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part II: Post Acquisition Data Processing, Visualisation, and Structural Characterisation
<p>Scanning transmission electron microscopy data related to paper "Scanning transmission electron microscopy data related to paper "Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part II: Post Acquisition Data Processing, Visualisation, and Structural Characterisation", <a href="https://doi.org/10.1017/S1431927620024307">https://doi.org/10.1017/S1431927620024307</a>.</p>
Fig. 3 in Sensory Structures On The Antenniform Legs Of Whip Spider Phrynichus Phipsoni (Arachnida, Amblypygi) From The Indian State Of Goa: Scanning Electron Microscopic Elucidation
Fig. 3. Sensory assembly on the whip (Antenniform leg) of Phrynichus phipsoni from Goa, India: 8 — rod sensilla within groove, 9 — plate organ, 10 — slit sensilla, 11 — trichobothria, 12 — sockets of trichobothria
Fig. 1 in Sensory Structures On The Antenniform Legs Of Whip Spider Phrynichus Phipsoni (Arachnida, Amblypygi) From The Indian State Of Goa: Scanning Electron Microscopic Elucidation
Fig. 1. Resting captive specimen of whip spider Phrynichus phipsoni (Pocock, 1894). Note the whip like configuration, position, and length of the antenniform first pair of non-ambulatory leg. The various segments have been marked for reference: 1 — vertically raised femur; 2 — femur-patella-tibia joint; 3 — tibia; 4 — tibio-tarsal articulation; 5 — tarsus; 6 — distal tarsal tip.
Fig. 2 in Sensory Structures On The Antenniform Legs Of Whip Spider Phrynichus Phipsoni (Arachnida, Amblypygi) From The Indian State Of Goa: Scanning Electron Microscopic Elucidation
Fig. 2. Sensory assembly on the whip (Antenniform leg) of Phrynichus phipsoni from Goa, India: 1 — terminal tarsal claw; 2 — bristles; 3 — leaf like sensilla; 4 — pore sensilla; 5 — club sensilla; 6 — tarsal organ; 7 — pit organ.
Experimental data for "Exact inversion of partially coherent dynamical electron scattering for picometric structure retrieval"
Open the record for dataset details and reuse information.
Figs 11–22 in Palp sensory structures in adult caddisflies of the suborder Annulipalpia (Trichoptera): a scanning electron microscopy study
Figs 11–22. Palp sensilla of caddisflies of the suborder Annulipalpia: 11 – N. bimaculata female, long trichoid sensilla on lateral surface of the fifth maxillary palp segment; 12 – N. bimaculata female, short chaetoid sensillum on ventral surface of the fourth maxillary palp segment; 13 – Ch. marginata male, a group of long chaetoid sensilla on medial surface of the second maxillary palp segment; 14 – D. varians male, truncated chaetoid sensillum on
Figs 7–10 in Palp sensory structures in adult caddisflies of the suborder Annulipalpia (Trichoptera): a scanning electron microscopy study
Figs 7–10. Labial palps of P. apicalis (7–8) and N. bimaculata (9–10) females. 7 – first and second segments; 8, 9 – third segment; 10 – sensory field on the third segment. Abbreviations: chs-s – short chaetoid sensilla; lts – long trichoid sensilla; pes-f – flattened petaloid sensilla; sf – sensory field. Roman numerals represent segment numbers.
Figs 1–6 in Palp sensory structures in adult caddisflies of the suborder Annulipalpia (Trichoptera): a scanning electron microscopy study
Figs 1–6. Medial (1–5) and ventrolateral (6) surfaces of maxillary palp of D. robusta male (Hydropsychidae). 1 – first segment; 2 – second segment; 3 – third segment; 4 – sensory field of petaloid sensilla on the first segment; 5 – fourth segment; 6 – tip of the fifth segment. Abbreviations: cfs – campaniform sensilla; chs-l – long chaetoid sensilla; chs-s – short chaetoid sensilla; lts – long trichoid sensilla; pes-c – curved petaloid sensilla; sf – sensory field. Roman numerals represent segment numbers.
Computed data for "Structural and Electronic Impacts of the Axial Substitution at the Phosphorus Center of C(sp3)-Bridged P-Heterotriangulenes"
<p>Computed structures and TD-DFT raw data of the article "Structural and Electronic Impacts of the Axial Substitution at the Phosphorus Center of C(sp3)-Bridged P-Heterotriangulenes" published in Eur. J. Org.Chem. <a href="https://doi.org/10.1002/ejoc.202400368">https://doi.org/10.1002/ejoc.202400368</a></p>
Dataset: Assessing MP2 frozen natural orbitals in relativistic correlated electronic structure calculations
<p>This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "Assessing MP2 frozen natural orbitals in relativistic correlated electronic structure calculations", by Xiang Yuan, Luvas Visscher and Andre Severo Pereira Gomes. It also contains the figures used in the manuscript.</p>
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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.