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308 results for “electronic structure”
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
Dataset for: Anniés et al., "Accessing structural, electronic, transport and mesoscale properties of Li-GICs via a complete DFTB-model with machine-learned repulsion potential"
<p>GPrep training data, GPrep jupyter notebook, .skf files.</p> <p>The GPrep code is available at https://doi.org/10.5281/zenodo.3697913</p>
Dataset for paper entitled, 'Tailoring equiaxed β-grain structures in Ti-6Al-4V coaxial electron beam wire additive manufacturing'
<p>Dataset for paper entitled, 'Tailoring equiaxed β-grain structures in Ti-6Al-4V coaxial electron beam wire additive manufacturing'. Abstract: High-deposition-rate, directed-energy-deposition additive manufacturing (DED-AM) processes typically produce Ti-6Al-4V (Ti64) components with coarse columnar β-grain structures that lead to undesirable mechanical anisotropy, as well as a fine heterogeneous lamellar transformation microstructure, which is very different to that seen standard wrought products. This arises because of the intrinsic lack of constitutional undercooling at the solidification front, and the subsequent high cooling rates and rapid thermal cycling experienced by the deposited material. In this work, the more refined primary β-grain solidification structures and textures seen in components built with the novel coaxial electron beam wire DED AM (CEWAM) process have been characterised in detail, for the first time, with the aim of investigating the potential for this technology to directly replicate the β-annealed damage-tolerant microstructure used in large Ti64 aerospace forgings. Due to its different lower energy density solidification conditions, it has been confirmed, by electron backscatter diffraction (EBSD) analysis and β-grain reconstruction in three orthogonal cross-sections, that the CEWAM process changes the melt conditions to promote β-grain nucleation ahead of the solidification front, which can result in a highly refined, equiaxed, β-grain structure. However, the conditions for refinement were marginal and a mixed grain structure was commonly observed in thicker sections. Additionally, the subsequent grain-growth stability during β-annealing was investigated. It is shown that an equivalent microstructure can be achieved to that seen in a standard β-forged component, by grain structure homogenisation and slow cooling through the β transus, to promote α colony nucleation, allowing direct part substitution. This was made possible by the refined primary β-grain structure achieved during deposition with the CEWAM solidification conditions which, importantly, are also shown to lead to a weaker texture than in a typical forging.</p> <p>Paper doi: https://doi.org/10.1016/j.mtla.2021.101202</p>
Data of the protocol paper: Protein Structural Modeling for Electron Microscopy Maps Using VESPER and MAINMAST
<p>The archived file contains data of the test cases used used in the protocol paper. For each protocol, there's a folder containing input files the protocol takes, and a folder for the protocol output files.</p>
Crystal structure of natural product Argyrin-D determined by 3D electron diffraction
<p>360° rotation of the Argyrin D model (stick mode with carbon, yellow; nitrogen, blue; oxygen, red; sulfur, gold and hydrogen, white) defined by a 2Fo-Fc map contoured at 1.2 sigma (grey mesh). The model was refined at a resolution of 1.1Å in Phenix using implemented electron scattering factors and restraints to R and Rfree values of 17.3 and 18.6%, respectively.</p>
BIR-MicroED: selected area electron diffraction tilt series datasets used to determine representative structures of biotin, Cu(II)-serine, Zn(II)-methionine, Zn(II)-histidine, and Co(II)-porphyrin
<div> <div> </div> </div> <div> <p>This deposition contains a series zip files each containing electron diffraction datasets in .mrc file format (except for the data collected from Co(II) porphyrin, which are 300 kV data in .tvips file format). Each folder collects data acquired from crystals of a particular compound under the same conditions (electron energy, temperature), where the reduced data from each were merged to determine a single representative structure of the compound by microED. Zip files are named according to the format: <em>"CompoundName</em>_<em>AcceleratingVoltage</em>_<em>Temperature_</em>structuredatasets.zip"</p> <p>Diffraction datasets within each folder are named according to the format: <em>CompoundName</em>_structuretiltseries_<em>AcceleratingVoltage</em>_<em>Temperature</em>_crystal#.mrc (or .tvips).</p> <p>All 200 kV datasets were collected with a rotation speed of 1 degree/second and an effective frame rate of 1 frame/second, with the exception of two Zn(II) methionine datasets collected with a frame rate of 3 frames/second. These are noted by the presence of "3fps" in the file name.</p> <p>All 300 kV datasets were collected with a rotation speed of 0.03 degrees/second and a frame rate of 0.5 frames/second.</p> </div>
Data for "Low-Energy Electronic Structure in the Unconventional Charge-Ordered State of ScV6Sn6"
<p>The files contain the data for the paper "Low-Energy Electronic Structure in the Unconventional Charge-Ordered State of ScV6Sn6". For data Fig1c+d_topography.gwy, the data has been well plotted in a free and commonly used software Gwyddion. The raw data can also be found in Fig1_c_topography.txt and Fig_1c_FFT.txt. For the 2D data, the scales for each axes can be obtained either normalized to Bragg peaks or can be found in the published manuscript online. Any question on the data, please contact the authors.</p>
Electronic structure orientation as a map of in-plane antiferroelectricity in beta'-In2Se3
<p>Matlab data files and metadata files for experimental data as described in the paper titled "Electronic structure orientation as a map of in-plane antiferroelectricity in beta'-In2Se3". </p>
Role of intercalated cobalt in the electronic structure of Co1/3NbS2
<p><span>Experimental data sets for figures in the article entitled “Role of intercalated cobalt in the electronic structure of Co1/3NbS2” published in Phys. Rev. B 105, 155114 (2022). The file name of each xlsx file corresponds to the figure number in the published article. The files can be opened by using Excel program. The data of subfigures is stored in separate sheets within one xlsx file.</span></p>
FAIRmat Tutorial 10: FAIR electronic-structure data in NOMAD
<p>The FAIRmat consortium aims to extend the current NOMAD-Lab (meta)data structure to a large variety of materials-science data. Given our strong foundation in computational data, especially DFT, we are now extending our scope. In this tutorial, we will explain the (meta)data structure for <em>ab initio</em> calculations, with an emphasis on precision and on going beyond the accuracy limits of DFT.</p> <p>This tutorial is suitable for new and experienced researchers who want to learn about the latest features in treating DFT and beyond DFT methodologies. We will give a brief introduction to the NOMAD Lab and the FAIRmat consortium, followed by a guided tutorial where we will:</p> <ol> <li>Show you how you can upload, publish, and explore <em>ab initio</em> computational data.</li> <li>Show you how to define your own complex workflows, linking between DFT and beyond DFT calculations.</li> <li>Give you examples of the post-processing capabilities of the NOMAD Lab.</li> </ol> <p>In more detail: Precision settings are now searchable, allowing for “data-quality” filtering over the NOMAD data. Using simple queries, we will show how to generate a sampling that extrapolates towards the basis set limit. For those already familiar with their code of choice, there is also the native tier quick filter that matches recommended developer settings. Moreover, for ease in navigating the density-functional space, we will be presenting a new, knowledge-based categorization system that is more refined and semantically richer than Jacob’s ladder. Finally, we will show the latest developed schemas which try to cover computational techniques that go beyond DFT and which are useful to treat excited-state and advanced many-body properties: the <em>GW</em> approximation, Bethe-Salpeter equation (BSE) solutions, tight-binding-based modeling (using Wannier projections or Slater-Koster fittings), and Dynamical Mean-Field Theory (DMFT). </p> <p><strong>Disclaimer: </strong>NOMAD is being continuously developed based on input and feedback from the scientific community. Hence the features, services or interface may have changed since the time of recording of this video. For up-to-date information please consult our latest tutorials and the NOMAD documentation <a href="https://nomad-lab.eu/prod/v1/docs/">https://nomad-lab.eu/prod/v1/docs/</a></p>
Electronic Supplement to Structural configuration of the Otates fault (southern Basin-and-Range Province) and its rupture in the 3 May 1887 MW = 7.5 Sonora, Mexico earthquake
<p>Electronic supplement to "Structural configuration of the Otates fault (southern Basin-and-Range Province) and its rupture in the 3 May 1887 MW = 7.5 Sonora, Mexico earthquake" (Seismological Society of America Bulletin, v. 98, no. 6, p. 2879-2893, 2008) with color-coded elevation model, satellite image of major Basin andRange normal faults in the study area, color version of geologic map, and additional photographs.</p> <p>High-resolution files of these figures are also available without restriction from </p> <p>http://www.seismosoc.org/Publications/BSSA_html/bssa_98-6/2008129-esupp/</p>
Data and Code For : "The Hierarchical Structure of Organic Mixed Ionic Electronic Conductors and Its Evolution in Water."
<p>The repository contains the principal 4D-STEM datasets and code used in the paper:</p> <p>"The Hierarchical Structure of Organic Mixed Ionic Electronic Conductors and Its Evolution in Water."</p> <p> </p> <p>* The measured and analyzed material is p(g3T2).</p> <p>* The code can be adjusted and used for the analysis of other conjugated polymers.</p> <p>* It should be noted that newer py4DSTEM versions with additional capabilities were released since the paper was </p> <p>submitted. </p> <p> </p> <p><strong>Contents:</strong></p> <p><strong>1. 4D-STEM_DATA_OMIECs.zip : </strong></p> <p><strong>4D-STEM data : </strong></p> <ul> <li>Dry_CL_2p1.dm4. </li> </ul> <p>scanned area [pixels]: 100x100, step size: 20 nm, CL: 2.1, c2 ca: 10 um, alpha 0.17 mrad, bin = 2,</p> <p>exposure time: 27 ms, spot size: 6, mono: 20, E(extraction voltage): 300 kV, temprature: LN. </p> <ul> <li> Calibrant_Dry_CL_2p1.dm4</li> </ul> <p>scanned area [pixels]: 45x48, step size: 10 nm, CL: 2.1, c2 ca: 10 um, alpha 0.17 mrad, bin = 2,</p> <p>exposure time: 13 ms, spot size: 6, mono: 40, E(extraction voltage): 300 kV, temprature: LN. </p> <ul> <li>Dry_CL_2p7.dm4</li> </ul> <p>scanned area [pixels]: 100x100, step size: 20 nm, CL: 2.7, c2 ca: 10 um, alpha 0.17 mrad, bin = 2,</p> <p>exposure time: 27 ms, spot size: 6, mono: 20, E(extraction voltage): 300 kV, temprature: LN. </p> <ul> <li>Calibrant_Dry_CL_2p7.dm4</li> </ul> <p>scanned area [pixels]: 45x48, step size: 10 nm, CL: 2.1, c2 ca: 10 um, alpha 0.17 mrad, bin = 2,</p> <p>exposure time: 13 ms, spot size: 6, mono: 40, E(extraction voltage): 300 kV, temprature: LN. </p> <ul> <li>Hydrated_Water_CL_2p7.dm4</li> </ul> <p>scanned area [pixels]: 100x100, step size: 15 nm, CL: 2.7, c2 ca: 10 um, alpha 0.17 mrad, bin = 2,</p> <p>exposure time: 27 ms, spot size: 6, mono: 25, E(extraction voltage): 300 kV, temprature: LN. </p> <ul> <li>Calibrant_Hydrated_Water_CL_2p7.dm4</li> </ul> <p>scanned area [pixels]: 50x50, step size: 10 nm, CL: 2.1, c2 ca: 10 um, alpha 0.17 mrad, bin = 2,</p> <p>exposure time: 13 ms, spot size: 6, mono: 46, E(extraction voltage): 300 kV, temprature: LN. </p> <ul> <li>Hydrated_NaCl_CL_2p7.dm4</li> </ul> <p>scanned area [pixels]: 100x100, step size: 20 nm, CL: 2.7, c2 ca: 10 um, alpha 0.18 mrad, bin = 4,</p> <p>exposure time: 13 ms, spot size: 6, mono: 15, E(extraction voltage): 300 kV, temprature: LN. </p> <ul> <li>Calibrant_Hydrated_NaCl_CL_2p7.dm4</li> </ul> <p>scanned area [pixels]: 50x50, step size: 10 nm, CL: 2.1, c2 ca: 10 um, alpha 0.18 mrad, bin = 4,</p> <p>exposure time: 13 ms, spot size: 6, mono: 80, E(extraction voltage): 300 kV, temprature: LN.</p> <p> </p> <p><strong>2. Notebooks.zip : </strong></p> <p><strong>Jupyter Lab Notebooks : </strong></p> <ul> <li>1A_pg3T2_dry_LN_CL2p1.ipynb. </li> </ul> <p>Analysis of dry film using CL 2.1.</p> <p>Goes with datasets: Dry_CL_2p1.dm4 and Calibrant_Dry_CL_2p1.dm4. </p> <ul> <li>1A_pg3T2_dry_LN_CL2p7.ipynb</li> </ul> <p>Analysis of dry film using CL 2.7.</p> <p>Goes with datasets: Dry_CL_2p7.dm4 and Calibrant_Dry_CL_2p7.dm4. </p> <ul> <li>1B_pg3T2_water_LN_CL2p7.ipynb</li> </ul> <p>Analysis of hydrated in water film using CL 2.7.</p> <p>Goes with datasets: Hydrated_Water_CL_2p7.dm4 and Calibrant_Hydrated_Water_CL_2p7.dm4. </p> <ul> <li>1C_pg3T2_NaCl_LN_CL2p7. </li> </ul> <p>Analysis of hydrated in 0.1 M NaCl(aq) film using CL 2.7.</p> <p>Goes with datasets: Hydrated_NaCl_CL_2p7.dm4 and Calibrant_Hydrated_NaCl_CL_2p7.dm4.</p> <ul> <li>aux_func.py: </li> </ul> <p>Contains auxilary functions and required for running the other notebooks.</p>
Electronic Structure and Topology in Gulf-edged Zigzag Graphene Nanoribbons
<h1>Electronic Structure, Topology and Spin-Polarization in Gulf-edged Zigzag Graphene Nanoribbons</h1> <p>This repository collects the necessary calculation files to reproduce the results shown in our manuscript (<a title="arXiv" href="https://arxiv.org/abs/2408.14839" target="_blank" rel="noopener">arXiv</a>). It includes the following parts:<br>* A) Structure files<br>* B) TB calculations<br>* C) DFT calculations<br>* D) GW calculations<br>* E) Parametrization of TB with Hubbard-U (TB+U)<br>* F) TB+U calculations<br>* G) ZGNR systems <br>* H) Calculations for different $U$ values</p> <h1>(A) Structure files</h1> <p>ZGNR-G structures, created with a C-C (C-H) bond length of 1.4 Ang (1.1 Ang) and bond angles of 120°. Structures are given with and without saturation of dangling bonds by hydrogen atoms. The unit cells are rectangular. The GNR is periodic in the x-direction, and a vacuum gap of 20 Ang between the carbon atoms is added in the y- and z-direction. We did not perform geometry optimization. Files are given in XYZ, XSF, and CIF format. The structural parameters are varied in the following range:<br>* $N$=4...11<br>* $a$=3...10<br>* $M$=2...9 (depending on $a$)<br>* $b$=0...a/2 (depending on $a$ and whether $N$ is odd or even)<br>* S and L inversion center</p> <p>The files are named in the following way: <br>* Carbon only (used in TB calculations): $N$-ZGNR-G$M$_$a$_$b$_<inversion center>.<file format><br>* Saturated systems (used in DFT calculations): $N$-ZGNR-G$M$_$a$_$b$_<inversion center>_saturated.<file format></p> <h1>(B) TB calculations</h1> <p>Minimal calculation files for the complete set of structures:<br>* Structure file in CIF format<br>* PythTB input file (onsite energy $\alpha$=0, 1st-NN hopping element $t_1$=-1)<br>* Calculation results in JSON format</p> <p>The data files contain the calculated band gaps and Z2 topological invariants, sorted into tables by structural parameters. A table is given for each combination of $N$, $M$, and inversion center. Each table varies the parameter $a$ in the rows (value of $a$ given first in each line) and the parameter $b$ in the columns (values not explicitly given, varied from 0 (0.5) to $a$/2 for even (odd) $N$). The band gaps are given in units of the 1st-NN hopping element $t_1$. The Z2 topological invariant is calculated using the Zak phase. A value is given for metallic systems even though the equations are not applicable to these systems. Additionally, the results are given as a simple list.</p> <h1>(C) DFT calculations</h1> <p>Calculation files for the subset of systems studied on the DFT/HSE06 level with a tight tier 1 basis and a k-grid of 18x3x3 using FHI-aims. ZGNR-G systems for this subset are selected to have a maximum of 100 carbon atoms in the primitive unit cell. Calculations are performed both without and with spin polarization. Spin-polarized systems are run with both an antiferromagnetic (AFM) and ferromagnetic (FM) initial guess (by placing an initial spin moment on the zigzag edge atoms), resulting in an AFM or FM magnetic state, respectively. </p> <p>For each calculation, the following files are stored:<br>* geometry.in: input geometry<br>* control.in: input file for FHI-aims<br>* aims.out: output file for FHI-aims <br>* band1001.out: band structure file for the first spin channel<br>* band2001.out: band structure file for the second spin channel (only for spin-polarized calculations)<br>* cube_001_spin_density.cube: converged spin density in CUBE format (compressed in ZIP format to save storage space after extracting calculation files)<br>* spin-polarization.png: plot of spin moments for carbon atoms (only for spin-polarized calculations)<br>* gap.dat: band gap, extracted from the band structure file<br>* spin_max.dat: maximum absolute spin moment, extracted from the Mulliken projection results<br>Additionally, for each structure, a plot comparing the band structure without spin polarization, the band structure of the AFM state, and the band structure of the FM state are stored. The DAT files are not stored for the FM state as those are never the magnetic ground state and thus were not further analyzed.</p> <p>In addition to the calculation files, the main results are collected in DAT files: the total energy (without spin polarization, AFM state, FM state), the band gap (without spin polarization and AFM state), and the maximum spin moment (only for the AFM state).</p> <h1>(D) GW calculations</h1> <p>Calculation files for the GW calculations, performed for 4-ZGNR, 5-ZGNR, and 6-ZGNR. They are calculated at the GW@PBE level and compared against calculations on the DFT/PBE and DFT/HSE06 level. Calculations are performed using FHI-aims with a tier 1 or tier 2 basis set and varying k-grids as visible from the file names. For each calculation, the input and output files are stored. They are sorted into subdirectories by their properties in the following order:<br>* Studied system,<br>* Method (DFT or GW),<br>* Functional, and<br>* Basis set and k-grid.</p> <h1>(E) Parametrization of TB with Hubbard-U (TB+U)</h1> <p>The parametrization of TB+U was done in two steps: (1) parametrization of the 1st NN hopping element $t_1$ and (2) the subsequent parametrization of the Hubbard-U, using the previously parametrized $t_1$.</p> <h2>(1) Parametrization of $t_1$</h2> <p>The parametrization of $t_1$ was done using the ZGNR-G systems available for DFT calculations. The TB and DFT calculations without spin polarization were used from steps B and C. Systems were excluded from the data set if the position of the DFT band gap was not reproduced in TB, leaving 372 ZGNR-G systems in the data set. The parametrization itself was done by linear regression of the DFT band gap in eV as a function of the TB band gap in units of $t_1$, resulting in y=3.328x-0.072 (R^2=0.951), giving $t_1$=3.328 eV. The TB and DFT band gaps are stored in the file "step1_parametrize_t1.dat"; the calculation files are taken directly from steps B and C.</p> <h2>(2) Parameterization of $U$</h2> <p>The parameterization of the Hubbard-U was done by first running TB+U calculations with different $U$ values. For this purpose, we varied $U$ from 0 to 5 in intervals of 0.2, using $t_1$=-1 to keep this step independent of the parametrization of $t_1$. The resulting band gaps are stored in DAT files in the subdirectory "calc_step2_variation_U" with a single file per ZGNR-G system. To save storage space, we did not upload further calculation files - the input files are equivalent to those uploaded in step F, just with different values for $t_1$ and $U$. </p> <p>Afterward, we used these results to obtain the optimal $U$ value for each system, focusing on systems that show a band gap opening in the AFM state on the DFT/HSE06 level. We performed the parametrization by identifying which value of $U$ in each system gives the best agreement of the TB+U band gap with the DFT band gap in the AFM state, using the calculations from step C and interpolating linearly between the $U$ values of the scan described above. We then ran a TB+U calculation with the obtained $U$ value to check the agreement with the DFT calculations. We generally obtained good agreement with a few exceptions that were filtered out: systems that resulted in a $U$ of zero and those without a band gap opening in the AFM state of the TB+U calculation. The results of the remaining 414 ZGNR-G systems are summarized in "step2_parametrize_U.dat". The final value of $U$ was obtained by averaging over those systems, yielding an average of 1.720 $t_1$, equivalent to 5.723 eV. The calculation files used for parametrization, including those filtered out, are stored in "calc_step2_TB+U_calculations". Plots comparing the band structures on DFT/HSE06 level, TB, and TB+U are in "plots_step2_fit_agreement".</p> <h1>(F) TB+U calculations</h1> <p>Calculation files for the complete set of structures:<br>* Structure file in XYZ format<br>* PythTB input file (onsite energy $\alpha$=0, 1st-NN hopping element $t_1$=-1, $U$=1.72 $t_1$)<br>* Calculation results in JSON format<br>* Plot of the band structure from TB vs. TB+U (AFM state)<br>* Plot of spin moments as an overlay over the atomic structure</p> <p>The data files contain the band gaps on TB and TB+U level ("results_band_gaps.dat"), the position of VBM and CBM on TB and TB+U level ("results_band_edge_positions.dat"), and spin momentum quantities ("results_spin_moments.dat"). Please note that, compared to the JSON files, a factor of 2 is applied to obtain the spin moment; this corrects the PythTB calculations, which multiply the final spin-polarization by a factor of 1/2 to account for electrons being particles with spin 1/2.</p> <h1>(G) ZGNR systems</h1> <p>ZGNR systems without gulf edges are included in the data set as a reference system. Structures are included in the subdirectory "structures" with widths $N$ from 2 to 50, analogously to part A. For all ZGNRs, DFT and TB+U calculations were performed. The provided files are equivalent to parts C and F. Additionally, for the DFT calculations with spin polarization, files for the maximum, minimum, and average (over the carbon atoms) spin moments are provided, distinguished by results from Mulliken and Hirshfeld analysis. The plots of the spin moments are also given for both the Mulliken and Hirshfeld analysis results.</p> <p>The data files contain the band gaps of the AFM state on DFT and TB+U level ("results_band_gaps_AFM_state.dat"), the total energy of the DFT calculations without and with spin-polarization in the AFM and FM state ("results_total_energies_DFT.dat"), as well as the maximum, minimum, and average (averaged over the C atoms) spin moment of the TB+U and DFT calculations, distinguished by Mulliken and Hirshfeld analysis ("results_spin-moments_maximum.dat," "results_spin-moments_minimum.dat," "results_spin-moments_average.dat"). Please note that, compared to the JSON files, a factor of 2 is applied to obtain the spin moment for the TB+U calculations.</p> <h1>(H) Calculations for different $U$ values</h1> <p>TB+U calculations similar to part F were performed for ZGNR and ZGNR-G systems. The main difference is that different values of $U$ were used: 1.20, 1.50, 1.72, and 2.00 in units of $t_1$. Please note that, compared to the JSON files, a factor of 2 is applied to obtain the spin moment for the TB+U calculations.</p>
Data set related to the manuscript "Mesoscopic simulations of the in situ NMR spectra of porous carbon based supercapacitors: Electronic structure and adsorbent reorganisation effects"
<p>Graphical files in the agr format for all the figures in the manuscript entitled "Mesoscopic simulations of the in situ NMR spectra of porous carbon based supercapacitors: Electronic structure and adsorbent reorganisation effects". Examples of input files for the lattice simulations are also provided.</p>
Structure-imposed electronic topology in cove-edged graphene nanoribbons
<p><strong>Abstract</strong></p> <p>In cove-edged zigzag graphene nanoribbons (ZGNR-C), one terminal group per length unit is removed on each zigzag edge, forming a regular pattern of coves which controls their electronic structure. Based on three structural parameters that unambiguously characterize the atomistic structure of ZGNR-C, we present a scheme that classifies their electronic state, i.e., if they are metallic, topological insulators or trivial semiconductors, for all possible widths <em>N</em>, unit lengths <em>a</em> and cove position offsets at both edges <em>b</em>, thus showing the direct structure-electronic structure relation. We further present an empirical formula to estimate the band gap of the semiconducting ribbons from <em>N</em>,<em>a</em>, and <em>b</em>. Finally, we identify all geometrically possible ribbon terminations and provide rules to construct ZGNR-C with well-defined electronic structure.</p> <p>DOI: 10.1103/PhysRevLett.129.216401</p> <p><strong>Content of repository</strong></p> <p>The repository contains the inputs and outputs of tight-binding (TB) calculations of ZGNR-C based on <a href="http://www.physics.rutgers.edu/pythtb/">PythTB</a>. For each analysed structure one subdirectory is created, labelled as "N-ZGNR-C_a_b_inv_cell<span class="math-tex">\(\alpha\)</span>_termination". This corresponds to a <em>N</em>-ZGNR-C(<em>a</em>,<em>b</em>) with inversion center at the unit cell boundary <em><strong>S</strong></em> or <em><strong>L</strong></em> ("inv"), unit cell angle <span class="math-tex">\(\alpha\)</span> ("cell<span class="math-tex">\(\alpha\)</span>": 60°, 90°, or 120°) and a given unit cell termination (armchair, zigzag or bearded). Each directory contains the atomic structure in xsf and cif format, the PythTB input file, the output as a json file, and the calculated band structure as image file. The json file contains the band structure information (path and eigenvalues), the raw Zak phase in units of <span class="math-tex">\(\pi\)</span> without modulo 2, and the final <span class="math-tex">\(\mathbb{Z}_2\)</span> invariant.</p> <p> </p>
Effect of intense x-ray free-electron laser transient gratings on the magnetic domain structure of Tm:YIG
<p>Dataset for the publication "Effect of intense x-ray free-electron laser transient gratings on the magnetic domain structure of Tm:YIG" by V. Ukleev, et al.</p>
Data for manuscript "Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting"
<p>The tar file contains the input files for RADICAL augmented MDFF implementation (R-MDFF) for two protein systems, Adenylate Kinase (ADK) and Carbon Monoxide Dehydrogenase (CODH). These examples demonstrate the implementation of R-MDFF using RADICAL-Cybertools to flexibly fit biomolecules in cryo-EM density maps with on-the-fly decision making.</p> <p>All molecular simulations were performed using CUDA enabled NAMD 2.14 installed on OLCF Summit HPC resource. The CHARMM36 force field parameters were used for the proteins. Synthetic density maps were prepared at 1.8, 3 and 5 Å for ADK and 1.8 and 3 Å for CODH using VMD 1.9.3 software installed on OLCF Summit HPC resource. During the analysis stage, the cross correlation coefficients between density maps and atomic model were computed using VMD 1.9.3 on Summit HPC as part of the R-MDFF workflow.</p> <p>The source code is publicly available on GitHub: <a href="https://github.com/radical-collaboration/MDFF-EnTK">https://github.com/radical-collaboration/MDFF-EnTK </a></p> <p>The preprint of this research is submitted on bioRxiv, doi: <a href="https://doi.org/10.1101/2021.12.07.471672">https://doi.org/10.1101/2021.12.07.471672 </a></p> <p>To obtain maximum compression of the data, the tar command used to generate this tarball was:</p> <pre><code class="language-bash">GZIP=-9 tar --exclude='last.pdb' --exclude='*last_from_prev_iter.pdb' --exclude='*old' --exclude='*log' --exclude='*coor' --exclude='*vel' --exclude='*xsc' --exclude='*dcd' --exclude='lastframepdbs_fix' --exclude='*out' --exclude='*sl' --exclude='*rs' --exclude='*prof' --exclude='*err' --exclude='*dx' --exclude='*grid.pdb' --exclude='*txt' -cvzf rmdffv2.tar.gz rmdff-zenodo/</code></pre> <p> </p>
Datesets and images of the publication "Probing crystallinity and grain structure of 2D materials and 2D-like van der Waals heterostructures by low-voltage electron diffraction" - DOI: 10.1002/pssa.202300148
<p>Datasets and images of the publication "Probing crystallinity and grain structure of 2D materials and 2D-like van der Waals heterostructures by low-voltage electron diffraction" - DOI: <a href="https://www.doi.org/10.1002/pssa.202300148">10.1002/pssa.202300148</a></p> <p>The Jupyter Notebooks for analyzing the datasets and generating all the figures are available at <a href="https://gitlab.com/JohMu/tds_hios_manuscript">https://gitlab.com/JohMu/tds_hios_manuscript</a>.</p> <p><strong>MoS<sub>2</sub> 4D-STEM dataset:</strong></p> <ul> <li>192x192 scan pixels</li> <li>200x200 camera pixels</li> <li>Acceleration voltage: 20kV</li> <li>Camera length: 10.56 mm</li> <li>Camera pixel size: 4x5.86 µm = 23.44 µm (original dataset with 4x4 binning)</li> <li>File location: Figure 2_3_S1.zip -> 230101205338_20kV_hexz0_camz-10_posi_003_good\scan_data_bin2_centered_crop-imgNx200.h5</li> <li>The original raw dataset (23 GB, 192x192 scan pixels, 800x800 camera pixels, camera pixel size: 5.86 µm), the scan reference dataset and the Jupyter Notebook for the shift-compensation is available from the author. The dataset uploaded here is binned by a factor of 4 and shift-compensated.</li> </ul> <p><strong>C60/MoS<sub>2</sub> 4D-STEM dataset:</strong></p> <ul> <li>113x113 scan pixels</li> <li>512x512 camera pixels</li> <li>Acceleration voltage: 20kV</li> <li>Camera length: 20.56 mm</li> <li>Camera pixel size: 5.86 µm</li> <li>File location: Figure 4.zip -> scan_data_scan113x113_gzip.h5</li> </ul> <p> </p>
Data from: Insights into chemical and structural order at planar defects in Pb2(MgW)O6 using multislice electron ptychography
Open the record for dataset details and reuse information.
Geometric structure and electronic properties of boron-substituted silicene
<p>The essential properties of monolayer silicene greatly enriched by boron substitutions are thoroughly explored through first -principles calculations. Delicate analyses are conducted on the highly non-uniform Moire superlattices, atom-dominated band structures, charge density distributions and atom- & orbital-decomposed van Hove singularities. The hybridized 2pz-3pz and [2s, 2px, 2py]-[3s, 3px, 3py] bondings, with orthogonal relations, are obtained from the developed theoretical framework. The red-shifted Fermi level and the modified Dirac cones/π bands/σ bands are clearly identified under various concentrations and configurations of guest atoms. Our results demonstrate that the charge transfer leads to the non-uniform chemical environment that creates diverse electronic properties.<br> </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.
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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.