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308 results for “electronic structure”
Rigorous results in electronic structure calculations
<p>The provided dataset contains rigorous error bounds for the <a href="http://mf.c.titech.ac.jp/mituhiro/software.html">ESC</a> and <a href="http://nakatamaho.riken.jp/rdmsdp/sdp_rdm.html">RDM</a> libraries computed before <strong>2016-11-17</strong>.</p> <p>The data is used in the publication "Rigorous results in electronic structure calculations" by Denis Chaykin, Christian Jansson, Frerich Keil, Marko Lange, Kai Torben Ohlhus, and Siegfried M. Rump (<a href="http://www.optimization-online.org/DB_HTML/2016/11/5730.html">http://www.optimization-online.org/DB_HTML/2016/11/5730.html</a>).</p> <p>This ZIP-archive is organized as follows:</p> <ul> <li><code>data</code> Computed error bounds for 47 ESC and 8 RDM test cases.</li> <li><code>log</code> Log files of the computations.</li> <li><code>src</code> Auxiliary MATLAB/GNU Octave code.</li> <li><code>tables</code> Exported tables for the publication.</li> <li><code>STEPx.m</code> Four MATLAB/GNU Octave functions to reproduce the data.</li> </ul> <p>In general all scripts are executed and the results attached. The scripts are only provided for the purpose of reproducing the given data.</p> <ul> <li><code>STEP1_setup.m</code> Adapt all paths to your local setup and run this function. In particular, the paths of <a href="http://www.ti3.tu-harburg.de/rump/intlab/">INTLAB</a>, <a href="https://github.com/sqlp/sdpt3">SDPT3</a>, and <a href="https://github.com/vsdp/vsdp-2012">VSDP-2012</a> and the data paths of <a href="https://github.com/vsdp/ESC">https://github.com/vsdp/ESC</a> and <a href="https://github.com/vsdp/RDM">https://github.com/vsdp/RDM</a> must be set. This function <strong>must</strong> be run before any other of the following functions!</li> <li><code>STEP2_prepare_data.m</code> This function extracts the original test data and stores it in VSDP-2012 format inside a MAT-file. Those MAT-files can be found in the <code>data</code> subdirectory.</li> <li><code>STEP3_run.m</code> This function actually performs all VSDP computations again. Thus it may take <strong>a few days</strong> to complete. Only consider to run this function for reproducing data. It is strongly recommended to adapt the code for relevant parts or test cases only. Logs are written to the <code>log</code> subdirectory.</li> <li><code>STEP4_export_tables.m</code> This function exports the published tables. Those can be found in the <code>tables</code> subdirectory.</li> </ul>
Supporting Data for the Manuscript "Anionic Disorder and its Impact on the Surface Electronic Structure of Oxynitride Photoactive Semiconductors"
<p>This data repository provides additional data for the manuscript "Anionic disorder and its impact on the surface electronic structure of oxynitride photoactive<br>semiconductors". The data sets comprise the PES raw data files in *.h5 format, the results from RBS/ERDA measurements, and quantification of the surface N:O ratios using TEM in EDX mode.</p> <ul> <li>"BT8c" labels the BTON sample before PEC.</li> <li>"BT8a" labels the BTON sample after PEC.</li> </ul>
Dataset for "Generalizing deep-learning electronic structure calculation to plane-wave basis"
<div> <div>This is the dataset for the paper "Generalizing deep-learning electronic structure calculation to plane-wave basis". For details, please see README.md.</div> </div>
FIGURES D30–D39 in The morphological diversity of Mymaridae (Hymenoptera): an atlas of scanning electron micrographs. Part 3. Structure of the metasoma
FIGURES D30–D39. Mymaridae metasomas, ventral (iop = inner plate of ovipositor, ovs= ovipositor sheaths, vf = valvifer; vv = valvula).
FIGURES 9–12 in The morphological diversity of Mymaridae (Hymenoptera): an atlas of scanning electron micrographs. Part 3. Structure of the metasoma
FIGURES 9–12. Apex of gaster. 9, Stephanodes septentrionalis, female, lateral; 10, S. septentrionalis male, lateral; 11, Steganogaster, male, posterior; 12, Stephanodes septentrionalis, male, posterior. Acronyms explained in Appendix 1.
FIGURES 13–15. Neomymar vierecki Crawford, female. 13 in The morphological diversity of Mymaridae (Hymenoptera): an atlas of scanning electron micrographs. Part 3. Structure of the metasoma
FIGURES 13–15. Neomymar vierecki Crawford, female. 13, metasoma, dorsal; 14 & 15, metasoma, lateral and median. Acronyms explained in Appendix 1.
FIGURES 1–8. 1–6, female metasomas. 1 in The morphological diversity of Mymaridae (Hymenoptera): an atlas of scanning electron micrographs. Part 3. Structure of the metasoma
FIGURES 1–8. 1–6, female metasomas. 1, Anagrus, dorsal; 2, Palaeoneura (Chaetomymar), dorsal; 3, Erythmelus, lateral; 4 Cosmocomoidea, lateral; 5, Stephanodes septentrionalis, lateral; 6, S. septentrionalis, ventral. 7 & 8, male gasters.7, Ooctonus, ventral; 8, Stephanodes polynemoides, anterior. Acronyms explained in Appendix 1.
FIGURES D1–D10 in The morphological diversity of Mymaridae (Hymenoptera): an atlas of scanning electron micrographs. Part 3. Structure of the metasoma
FIGURES D1–D10. Mymaridae metasomas, ventral (gt = gastral tergum, gs = gastral sternum, iop = inner plate of ovipositor, vf = valvifer; vv = valvula).
Experimental data used in the article entitled "Electron Microscopy Study of Structural Defects Formed in Additively Manufactured AlSi10Mg Alloy Processed by Equal Channel Angular Pressing"
Open the record for dataset details and reuse information.
Research Data for "Evaluating the electronic structure and stability of epitaxially grown Sr-doped LaFeO3 perovskite alkaline O2 evolution model electrocatalysts"
<p>This is the research data supporting figures and tables for the paper "Evaluating the electronic structure and stability of epitaxially grown Sr-doped LaFeO3 perovskite alkaline O2 evolution model electrocatalysts" appearing in <em>RSC Applied Interfaces </em>under DOI <a title="Link to landing page via DOI" href="https://doi.org/10.1039/D4LF00260A">https://doi.org/10.1039/D4LF00260A</a>.</p>
Research Data for "Electronic structure and stability of the active surface phase of NixCo3-xO4 spinel alkaline O2 evolution electrocatalysts: from an epitaxial model catalyst perspective"
<p>These datasets support main text and supplementary figures and tables of the paper "Electronic structure and stability of the active surface phase of NixCo3-xO4 spinel alkaline O2 evolution electrocatalysts: from an epitaxial model catalyst perspective" appearing in <em>ACS Applied Energy Materials </em>under DOI: <a href="https://doi.org/10.1021/acsaem.4c01688">https://doi.org/10.1021/acsaem.4c01688 </a></p>
Database of DNA electron density training structures v2
<p>This database contains the data for the DNA structures used to train the e3nn machine learning electron density model in the publication, “Predicting accurate <em>ab initio</em> DNA electron densities with equivariant neural networks": <a href="https://doi.org/10.1016/j.bpj.2022.08.045">https://doi.org/10.1016/j.bpj.2022.08.045</a>.</p> <p>Version 2 includes data files with the correct number of atoms. Energy and force data (which wasn't used to train the density model) was removed. </p> <p>See the file <a href="https://zenodo.org/api/files/ff345ec9-614c-4a59-ae5b-667bd1f793f2/DNA-density-database.pdf">DNA-density-database-v2.pdf</a> for details.</p>
All structures for electronic coupling for TEMPO
<ol> <li>'all_263_structures' folder contains all 263 structures' xyz files.</li> <li> 'results_all_coup_casscf_ma_tzvp.csv' contains names of all the structures with correct active space obtained using CASSCF-GMH1.</li> <li> 'results_all_coup_casscf_ma_svp.csv' contains names of all the structures with correct active space obtained using CASSCF-GMH2.</li> <li>'tddft_basis_coupling.csv' contains names of the five randomly selected structures.</li> </ol>
Structural heterogeneity of cellular K5/K14 filaments as revealed by cryo-electron microscopy
<p>Keratin intermediate filaments are an essential and major component of the cytoskeleton in epithelial cells. They form a stable yet dynamic filamentous network extending from the nucleus to the cell periphery, which provides resistance to mechanical stresses. Mutations in keratin genes are related to a variety of epithelial tissue diseases. Despite their importance, the molecular structure of keratin filaments remains largely unknown. In this study, we analyzed the structure of keratin 5/keratin 14 filaments within ghost keratinocytes by cryo-electron microscopy and cryo-electron tomography. By averaging a large number of keratin segments, we have gained insights into the helical architecture of the filaments. Two-dimensional classification revealed profound variations in the diameter of keratin filaments and their subunit organization. Reconstitution of filaments of substantial length uncovered a high degree of internal heterogeneity along single filaments, which can contain regions of helical symmetry, regions with less symmetry and regions with significant diameter fluctuations. Cross section views of filaments revealed that keratins form hollow cylinders consisting of multiple protofilaments, with an electron dense core located in the center of the filament. These findings shed light on the complex and remarkable heterogenic architecture of keratin filaments, suggesting that they are highly flexible, dynamic cytoskeletal structures.</p>
Planar slow wave structures for millimeter-wave vacuum electron devices
<p>Underlying data corresponding to the conference paper: G. Ulisse, V. Krozer, "Planar slow wave structures for millimeter-wave vacuum electron devices", 47th European Microwave Conference (EuMC), Nuremberg, Germany, October 2017</p>
Experimental and Computational data related to research on ``Investigating the Electronic Structure of Prospective Water-splitting Oxide BaCe0.25Mn0.75O3−δ Before and After Thermal Reduction''
<p>Data files and gnuplot scripts for the figures included in the submission titled ``<strong>Investigating the Electronic Structure of Prospective Water-splitting Oxide BaCe<sub>0.25</sub>Mn<sub>0.75</sub>O<sub>3−δ </sub>Before and After Thermal Reduction''</strong></p>
Dataset for deep-learning electronic-structure calculation of magnetic superstructures
<p>Dataset files of atomic structures, magnetic configurations and Hamiltonian matrices of monolayer NiBr<sub>2</sub>, monolayer CrI<sub>3</sub> and bilayer CrI<sub>3</sub>. The dataset file of bilayer CrI<sub>3</sub> exceeds the file size limit of Zenodo and can be downloaded in <a href="https://cloud.tsinghua.edu.cn/f/53b2c86b785442ae8916/?dl=1">this link</a> (115 GB).</p>
Electronic Structure and Optical Properties of Tin Iodide Solution Complexes
<p>(TD)DFT+PCM study on the structural, electronic, and optical properties of 14 tin-iodide-solution complexes with the chemical formula SnI<sub>2</sub>M<sub>4</sub>, with M one of 14 common solvent molecules.</p>
FIGURES 19–21. Mymaridae head structures. 19a in The morphological diversity of Mymaridae (Hymenoptera): an atlas of scanning electron micrographs. Part 1. General overview and structure of the head
FIGURES 19–21. Mymaridae head structures. 19a, head, posterior; 19b, tentorium; 20, tentorium; 21a, section through transverse trabecula; 21b, enlargement of 21a. Acronyms explained in Appendix 1.
Supplementary materials for "Machine Learning Electronic Structure Methods Based On The One-Electron Reduced Density Matrix"
<p><strong>Supplementary materials for "Machine Learning Electronic Structure Methods Based On The One-Electron Reduced Density Matrix"</strong></p> <p>by X. Shao, L. Paetow, M. E. Tuckerman and M. Pavanello</p> <p><strong>The QMLearn software</strong></p> <p>A current snapshot of the QMLearn software is available on GitLab at https://gitlab.com/pavanello-research-group/qmlearn. Video tutorials and other examples (including Jupyter Notebooks) are available at http://qmlearn.rutgers.edu</p> <p><strong>Data availability</strong></p> <p>We share all training/test sets and notebooks needed to reproduce Table II and Figures 1-7. For all figures, we provide Jupyter notebooks and the needed data to exactly reproduce the figures. Trajectory files for all IR spectra are shared. The collection of all materials is available in this dataset.</p> <p>The QMLearn version used for this work is 0.0.1.</p> <p>Specific QMLearn dependencies and their version used for all calculations are listed as follows:<br> - ase (3.22.1)<br> - h5py (3.7.0)<br> - numpy (1.23.1)<br> - pyscf (2.0.1)<br> - scikit-learn (1.1.1)<br> - scipy (1.8.1)</p>
ScienceDex guides
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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.