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669 results for “ATOM”
Atom probe tomography nomad-FAIR demonstrator dataset R76-20231-v01.epos.apth5
<p>This is the dataset of an atom probe tomography experiment which is provided open source for testing the possibility of implementing an open source encyclopedia for experimental materials science datasets, including techniques to begin with such as Scanning Transmission Electron Microscopy (STEM), Multidimensional Photo Emission Spectroscopy (MPES), and Atom Probe Tomography (APT) / Field Ion Microscopy (FIM).</p> <p><strong>This repository serves three aims:</strong></p> <p>1. The dataset is of scientific interest. Specifically, it captures the result of a cutting-edge APT experiment detailed exemplarily in DOI 10.1017/S1431927616012654 Fig. 1d by Zirong Peng and coworkers.</p> <p>2. The dataset contributes to tests of an extension to "The NOMAD Laboratory" (https://nomad-coe.eu/): nomad-FAIR. Specifically, to test various aspects of an automatized metadata parsing and processing pipeline to enable the extraction of domain-specific JSON metadata files into a NOMAD-conformant JSON file, ultimately aiming for searchable and repurposable dataset documentation. This serves two purposes: on the one hand to contextualize each dataset within NOMAD. On the other hand to serve as a starting point to parse potential interesting content from the heavy data HDF5 file to reduce unnecessary file access.</p> <p>The implementation of nomad-FAIR is coordinated by Markus Scheidgen.<br> The APT domain-specific parser is developed by Markus Kühbach.</p> <p>3. The dataset constitutes further a test of an open format specification for storing atom probe tomography data using the Hierarchical Data Format (HDF5). This is a recent initiative of the International Field Emission Society's (IFES) atom probe tomography technical committee. In this repository it is detailed an exemplar proposal of how to store acquisition-side relevant results and context of an APT experiment into a HDF5 file and complementary metadata files such as JSON. Implementation of this HDF5-based storage solution for APT data is lead by Markus Kühbach.</p> <p><br> <strong>The organization of this repository with respect to above aims is as follows:</strong></p> <p>-The original EPOS file of the measured is contained in the compressed *.epos.tar.gz archive.</p> <p>-The *.apth5 file is a transcoded version of the EPOS file. Therein, x,y,z data columns are stripped.</p> <p>-The correspondingly named *.json file is the file which nomad-FAIR parses metadata from.</p> <p>-Other files constitute logs of the transcoding process.</p> <p><strong>Funding:</strong><br> The work was partially supported by BiGmax, the Max Planck Society's Research Network on Big-Data-Driven Materials-Science.</p>
Atomic energy densities from the multiple radii functional (MRF)
<p>This dataset contains exchange-correlation energy densities in the gauge of the electrostatic potential for various atomic systems, all in atomic units. The first column represents the distance from the nucleus in bohr, while the remaining columns represent the energy densities. The headings for the columns are specified in the first row of the dataset. The dataset includes the exact energy densities "w_0 [exact]" and "w_1 [exact]" which are taken from reference [Phys.Chem.Chem.Phys., 2017, 19, 6169]. These densities are calculated at the zero and full coupling strengths, respectively. The densities used to calculate the MRF functional are also taken from the same reference, where the computational details can be found. "w_1 [mrf original]" represents the MRF energy densities calculated using the original fluctuation function developed in reference [J. Phys. Chem. Lett. 2017, 8, 2799−2805]. "w_1 [mrf new]" represents the MRF energy densities calculated using a newly developed fluctuation function, specifically designed to satisfy the high-density limit, non-negativity of the correlation part of the energy densities, and the uniform electron gas limit. Files are given in the XLSX format and different file names represent different atoms (ions). Wolfram Mathematica 13.1.0.0. has been used for data curation. </p> <p> </p>
Data of publication: "Collective atom-cavity coupling and nonlinear dynamics with atoms with multilevel ground states"
<p>The uploaded files contain the raw data of the measurements and simulations presented in <a href="https://doi.org/10.1103/PhysRevA.107.023714">https://doi.org/10.1103/PhysRevA.107.023714</a></p>
Dataset for visualizing the atomic-scale origin of metallic behavior in Kondo insulators
<p>This dataset contains the raw data files and analysis steps used to produce the figures in the manuscript "Visualizing the atomic-scale origin of metallic behavior in Kondo insulators" Science 379, 1214–1218 (2023)</p>
Data and code for "Single-Atom Dopants in Plasmonic Nanocatalysts"
<p>The data includes atomic structures, photoabsorption spectra, densities of states, and hot-carrier distributions of the systems modeled in the article "Single-Atom Dopants in Plasmonic Nanocatalysts" by Daniel Sorvisto <em>et al</em>.</p> <p>The input scripts for reproducing the data are also included.</p> <p>See <em>README.md</em> in the archive for a detailed description.</p>
Dataset for: All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor
<p>This dataset contains relevant structures, input and other files that are associated with our article "<em>All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor", available at https://pubs.acs.org/doi/full/10.1021/acs.jcim.3c00249</em></p>
Initial Conditions for ATOM-COBALT dynamic N:P model simulations in GBC paper
<p>Adjustment of standard initial conditions file for COBALT simulations to add dynamic phytoplankton P fields. </p>
Dataset for Quantitative description of metal center organization in single-atom catalysts
<p>Dataset for <strong>Quantitative description of metal center organization in single-atom catalysts </strong>by by K. Rossi, A. Ruiz-Ferrando, D. Faust Akl, V. Gimenez Abalos, J. Heras-Domingo, R. Graux, X. Hai, J. Lu, D. Garcia-Gasulla, N. López, J. Pérez-Ramírez, and S. Mitchell.</p> <p>The data is structured as follows:</p> <ul> <li>01_Micrographs: all micrographs employed in .tif and .png format. An <a href="https://imagej.net/">imageJ </a>macro to overlay coordinate files with images is attached.</li> <li>02_Ground_truth: contains the manually-labeled and predicted xy-coordinates of atomic positions including probabilities.</li> <li>03_All_detection_data: contains all automated predictions of atomic positions in the images of this study (uhd), and of Mitchell et. al in <em>JACS</em>, <strong>144</strong>, 8018-8029 (2022) (jacs_train, jacs_test). This folder further contains model weights and area segmentations needed to estimate the surface atomic densities.</li> <li>04_Trimetallic_analysis: Figures complementing Supplementary Figure S21.</li> </ul> <p> </p>
Optimized stationary points on the potential energy surface of the reaction of atomic oxygen O(3P) with acrylonitrile
<p>This Zip file contains the cartesian coordinates of optimized stationary points of the O(<sup>3</sup>P) + acrylonitrile potential energy surface (PES).</p> <p>The PES has been published in our article “A Computational Analysis of the Reaction of Atomic Oxygen O(<sup>3</sup>P) with Acrylonitrile”</p> <p>(<em>Lecture Notes in Computer Science</em> <strong>2021</strong>, 12958, 339-350), that can be found in https://doi.org/10.1007/978-3-030-87016-4_25 .</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.</p>
Bose-Einstein condensation of non-ground state caesium atoms
<p>We report the Bose-Einstein condensation of caesium atoms in the Zeeman-excited<br> mf = 2 state. As the magnetic field is varied, we identify two regions in which the<br> dipolar relaxation rate is sufficiently suppressed so that condensation becomes possible.<br> We characterize the phase transition and quantify the loss processes, finding unusually<br> high three-body losses in one of the two regions. Our experimental results otherwise<br> agree well with the theoretical expectation. In particular, we confirm the presence of<br> a narrow Feshbach resonance near a zero crossing in the background scattering length.<br> Our results open up new possibilities for the mixing of quantum-degenerate gases and<br> the study of impurity transport in strongly correlated one-dimensional quantum wires.</p>
Atom probe tomography data collection from DIN 1.4970 (15-15Ti) austenitic stainless steel irradiated with Fe ions
<p>This dataset comprises a large collection of atom probe tomography datasets collected from DIN 1.4970 alloy that was irradiated with Fe ions at different conditions. The DIN 1.4970 alloy is an austenitic stainless steel with 15 wt% Cr, 15 wt% Ni, a small addition of Ti. The full composition and characterization of our material can be found published elsewhere [1,2].</p> <p>Some of our material was subjected to ageing heat treatments at different temperatures for different times. Small samples of our original material and aged material was irradiated at the Michigan Ion Beam Laboratory in 2017 with 4.5 MeV Fe ions up to 40 dpa at an average dose rate of <span class="math-tex">\(2 \times 10^{-4}\)</span> dpa/s. This was done at three different temperatures: 300, 450, and 600 ºC. Atom probe samples were made of the irradiated layers (approximately 1.5 micron deep) with focused ion beam and mounted on Microtip coupons. APT measurements took place on three CAMECA LEAP-HR systems located at CAES in Idaho Falls, USA (files beginning with R33), at Montanuniversität Leoben in Leoben, Austria (R21) and at Friedrich–Alexander University in Erlangen, Germany (R56).</p> <p>The contents of this archive are:</p> <ul> <li>A folder containing the raw RHIT files</li> <li>A folder containing all the reconstructions and miscelaneous analysis files made by the author</li> <li>An excel file which indicates which measurement number stands for what material</li> <li>A suggested range file</li> </ul> <p>The RHIT files can only be used if one has access to the full IVAS 3.x version in order to make new reconstructions.</p> <p>The reconstructions and analysis folder can be useful to anyone. The folder buildup structure is similar to a project folder created by IVAS and should be directly importable into IVAS. Most folders are simply named after the RHIT file they were constructed from, though some have slightly modified names to include date of creation, extra information,... Inside all these folders you will find the recons folder and inside multiple reconstructions. At the deepest level you will find .pos files which can be read into free software such as python or <a href="http://threedepict.sourceforge.net/">3depict</a>. The range file that will give decent results on all these measurements is given at the top level; slight modifications may need to be applied for each measurement. Inside all folders you will also find numerous files (csv, png, jpg, ...) that were created by analyzing the data in IVAS. Sometimes the file names are very descriptive, sometimes less so. Sometimes these files were not saved to the default analysis folder but elsewhere on my drive. To be complete, I have moved all of these files into the top level folder. Therefore, besides the imagoAnalysis and recons folders, you will sometimes find additional folders and files in the folder. By different merging procedures, there may be multiple copies of the same files present as well. Unfortunately, the reconstructions and analysis folder is rather chaotic, as is the nature of file creation by IVAS.</p> <p>It is most instructive to start with the excel file at the top level of the archive. The first sheet contains some information, mostly the same as mentioned here. The second sheet pertains to the ion irradiations that were performed. The table colunms are self explanatory. Each irradiated sample was given a particular alias (first column), which relates it to the slot in the storage box in which it is stored. 5 different materials appear in the irradiations:</p> <ul> <li>T24 = tube, 24% cold worked. This represents the material as it was received from the manufacturer.</li> <li>T24-800C2h = the as-received material with an ageing heat treatment of 2 hours for 800 ºC applied.</li> <li>T24-600C4h = the as-received material with an ageing heat treatment of 4 hours for 600 ºC applied.</li> <li>T24-600C2868h = the as-received material with an ageing heat treatment of 2868 hours for 600 ºC applied.</li> <li>T46 = tube 46% cold worked. This represents another material received from the manufacturer</li> <li>AIM1 = another related material with a higher P and Si content obtained from another research institute</li> </ul> <p>All these materials were irradiated under different conditions as given in the subsequent columns. The irradiation parameters were drawn directly from reports produced by the lab, but we suspect some typos slipped into the reports. We do know for certain that the samples were irradiated up to a surface dose of 40 dpa, at least according to a <a href="http://www.srim.org/">SRIM calculation</a> with the K-P model. Atom probe results only pertain to T24 and T24-800C2h. A few measurements were conducted on T24-600C4h material but this material was not irradiated.</p> <p>The last sheet gives an overview of all the APT measurements included in this archive. The first column pertains to the sample alias in sheet 2: the irradiated disc from which the samples were made. The sample detail column details the history of the sample for convenience: T24 - <heat treatment conditions> - <irradiation conditions>. When in doubt, one can look up the sample alias in sheet 2. The filename pertains to the APT measurement RHIT file. For the 3 measurements performed in Leoben, RHIT files are not included in this archive. Finally a few details such as approximate ion count and some comments are included for some measurements.</p> <p>Funding: This work was supported by ENGIE [contract number 2015-AC-007 e BSUEZ6900]; the U.S. Department of Energy, Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07- 051D14517 as part of a Nuclear Science User Facilities experiment; and by the MYRRHA program in development at SCK-CEN, Belgium. Funding of the Austrian BMVIT (846933) in the framework of the program "Production of the future" and the "BMVIT Professorship for Industry" is gratefully acknowledged.</p> <p> </p> <p><a href="https://www.sciencedirect.com/science/article/pii/S0022311518300485">[1] N. Cautaerts, R. Delville, E. Stergar, D. Schryvers, M. Verwerft, Tailoring the Ti-C Nanoprecipitate Population and Microstructure of Titanium Stabilized Austenitic Steels, J. Nucl. Mater. 507 (2018) 177–187. doi:10.1016/j.jnucmat.2018.04.041.</a></p> <p> </p> <p><a href="https://www.sciencedirect.com/science/article/pii/S1359645418308103">[2] N. Cautaerts, R. Delville, E. Stergar, D. Schryvers, M. Verwerft, Characterization of (Ti,Mo,Cr)C Nanoprecipitates in an Austenitic Stainless Steel on the Atomic Scale, Acta Mater. 164 (2018) 90–98. doi:10.1016/J.ACTAMAT.2018.10.018.</a></p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
All Atom Molecular Dynamics Simulations of Lopinavir at the Binding Pocket of SARS-CoV2 Main Protease
<p>Data includes all of the trajectories (2000) of classical all-atom molecular dynamics (MD) simulations of lopinavir at the binding pocket of SARS-CoV2 main protease target. In order to decrease the size of the file only protein and ligand trajectories were provided. Simulation has been performed with Desmond. Protein–ligand complexes were obtained by Glide/SP docking program. Complex was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff<br> radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 500 ns production run was performed for the simulations.</p>
Data of "Deterministic creation of entangled atom–light Schrödinger-cat states"
<p>Data published in "<em>Deterministic creation of entangled atom–light Schrödinger-cat states</em>"</p> <p>Nature Photonics <strong>volume 13</strong>, pages110–115(2019)</p>
All atom simulations snapshots and contact maps analysis scripts for SARS-CoV-2002 and SARS-CoV-2 spike proteins with and without ACE2 enzyme
<p><strong>The dataset contains a total of 40 snapshots of the four trajectories (10 snapshots each system = two per replica x 5 replicas/system):</strong></p> <ol> <li>SARS-CoV-2002 spike protein without ACE2</li> <li>SARS-CoV-2 spike protein without ACE2</li> <li>SARS-CoV-2002 spike protein with ACE2</li> <li>SARS-CoV-2 spike protein with ACE2</li> </ol> <p>Molecular dynamics simulation trajectories (320ns each) have been performed using the Amber ff14SB force field running with the Amber18 package at the the NSF-funded (OAC-1826915, OAC-1828163) ELSA high performance computing cluster at The College of New Jersey. Under the following simulation methodology:</p> <p><em>All-atom simulations were carried out with Amber18 (<a href="https://slack-redir.net/link?url=http%3A%2F%2Fambermd.org">ambermd.org</a>), and system components (protein, ions, water) were modeled with the included FF14SB and TIP3P parameter sets. Energy minimization used CPU pmemd, while later simulation stages used GPU pmemd. CoV2 and CoV1 systems with one RBD up (with/without ACE2) were solvated in 12 angstrom water shells. Cysteine residues identified in the initial models as having a disulfide bond (DB) were bonded using tLeap. All simulations used 0.150 M NaCl. Hydrogen mass repartitioning was applied only to the protein to enable a 4 fs timestep (<a href="https://slack-redir.net/link?url=https%3A%2F%2Fpubs.acs.org%2Fdoi%2Fabs%2F10.1021%2Fct5010406">https://pubs.acs.org/doi/abs/10.1021/ct5010406</a>). The SHAKE algorithm was applied to hydrogens, and a real-space cutoff of 8 angstroms was used. Periodic boundary conditions were applied and PME was used for long-range electrostatics. Minimization was by steepest descent (2000 steps) followed by conjugate gradient (3000 steps). Heating used two stages: (1) NVT heating from 0 K to 100 K (50 ps), and (2) NPT heating from 100 K to 300 K (100 ps). Restraints of 10 kcal mol<sup>-1</sup> angstrom<sup>-2</sup> were applied during minimization and heating to C-alpha atoms. During 6 ns of equilibration at 300 K C-alpha restraints were gradually reduced from 10 kcal mol<sup>-1</sup> angstrom<sup>-2</sup> to 0.1 kcal mol<sup>-1</sup> angstrom<sup>-2</sup>. Finally, restraints were released and 320 ns unrestrained production simulations were carried out for CoV2 and CoV1 systems. Production simulations began from the final equilibrated snapshots, and five copies of each system were simulated. As unrestrained systems can freely rotate we monitored simulations for any close contacts and found that in one copy of the CoV1 simulation without ACE2 and one RBD up that a few contacts close to 8 angstrom occur near the end of the 320 ns between the RBD and a different subdomain of the spike complex in a periodic image. However this did not influence analyzed structural properties which is verified by comparing results across simulations. The Monte Carlo barostat was used to maintain pressure (1 atm), and the Langevin thermostat was used to maintain 300 K temperature (collision frequency 1 ps<sup>-1</sup>), as implemented in Amber18. In aggregate, nearly 7 microseconds of simulation of systems ranging from 396,147 to 879,100 atoms was carried out for this work.</em><br> For further details on the trajectories, please contact Joseph Baker (bakerj@tcnj.edu).</p> <p><strong>Regarding the contact map analysis scripts (contactMaps_Analysis.tar.gz), they contain the following workflow:</strong></p> <p>contactmap --> source files from contact_map executable<br> process_nc.sh --> convert raw data from all-atom simulation to numbered PDB files and get the contact maps<br> frequency.lua --> read a set of PDB files and output the frequency count for each contact<br> consensus.fasta --> align sequence of Covid19 and SARS from Chimera<br> consensus.lua --> read data previously generated and compute the frequency per residue, among other things.<br> consensus.sh --> input information to consensus.lua<br> consensus.gp --> gnuplot script to plot figures</p> <p>This dataset and the code is part of tripartite collaboration between:</p> <ul> <li>The Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland (supported by the National Science Centre, Poland, under grant No. 2017/26/D/NZ1/0046)</li> <li>Department of Chemistry, The College of New Jersey, New Jersey, United States (supported by National Science Foundation under grant numbers OAC-1826915 and OAC-1828163).</li> <li>Jozef Stefan Institute, Ljubljana, Slovenia (supported by the Slovenian Research Agency (Funding No. P1-0055)).</li> </ul>
Raw Data to "Density functional theory study of CO formation through reactions of polycyclic aromatic hydrocarbons with atomic oxygen (O(3P))"
<p>This data is a supplement to the publication <a href="https://doi.org/10.1016/j.fuel.2018.12.047">https://doi.org/10.1016/j.fuel.2018.12.047</a>. The data includes Turbomole input and output files. The calculations are performed using DFT/TPSSh-D3/TZVP method and Turbomole version 7.2. The equilibrium structures for the reactions of polyaromatics are named as following:<br> C<sub>X</sub>H<sub>Y</sub> (<strong>S1</strong>) + O -> C<sub>X</sub>H<sub>Y</sub>O (<strong>S2</strong>) -> C<sub>X</sub>H<sub>Y-1</sub>O (<strong>S3</strong>) + H (i) O addition and H abstraction<br> C<sub>X</sub>H<sub>Y-1</sub>O (<strong>S3</strong>) [-> <strong>S4</strong> -> <strong>S5</strong> ] -> CX-1HY-1 (<strong>S6</strong>) + CO (ii) Single, two, or three step CO elimination</p> <p>The transition state structures are named according to the naming of the corresponding reactant and product. For example, the transition state connecting the structure S3 to S5 is named as T35. Under some of the transition state directories, intrinsic reaction coordinate calculation output can be found under the directories named as "IRC".<br> <br> </p> <p><br> The LibreOffice Calc spreadsheet "SUPPINFO.ods" includes the activation and reaction energies to the reaction steps.</p>
Computational atomic coordinate files for Quantification of Ni-N-O bond angles and NO activation by X-ray emission spectroscopy
<p>Geometry optimized coordinates and other atomic coordinate files in xyz format used to calculate X-ray emission spectra of beta-diketiminate nickel nitrosyl complexes.</p>
All-atom Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 100 ns production run was performed for the simulation.</p>
Modeling sympathetic cooling of molecules by ultracold atoms: supporting data
<p>Data used in preparation of the paper "Modeling sympathetic cooling of molecules by ultracold atoms", authored by Jongseok Lim, Matthew D. Frye, Jeremy M. Hutson and M. R. Tarbutt.</p> <p>There are four different types of data:</p> <p>(1) Tables of total cross sections versus collision energy for collisions of CaF with Li and Rb for various values of s-wave scattering length (see figure 1)</p> <p>(2) Tables of differential cross sections versus energy for collisions of CaF with Li and Rb for various values of s-wave scattering length. The differential cross sections are given as cumulative distribution functions.</p> <p>(3) Simulated kinetic energy distributions at 1s intervals for sympathetic cooling of CaF with Li and Rb for various values of s-wave scattering length (see figures 5 and 6).</p> <p>(4) Simulated kinetic energy distributions at 1s intervals for sympathetic cooling of CaF with Rb with various evaporative cooling ramps applied to the Rb (see figure 13).</p>
Atomic Force Microscopy Images of Cell Specimens
<p>This data set consists of seven atomic force microscopy images in MI format as well as corresponding previews in PNG format.</p> <p>The microscopy images are of cell material and have been scanned with AFM equipment from Keysight Technologies. Details on the individual images:</p> <ul> <li>image_0.mi - Chinese hamster ovary cells</li> <li>image_1.mi - Chinese hamster ovary cells</li> <li>image_2.mi - human bladder carcinoma cells</li> <li>image_3.mi - human bladder carcinoma cells</li> <li>image_4.mi - Chinese hamster ovary cells</li> <li>image_5.mi - Chinese hamster ovary cells</li> <li>image_6.mi - Chinese hamster ovary cells</li> </ul> <p>The images can be opened using, e.g. Gwyddion: http://gwyddion.net/<br /> The Python package Magni can be used to load the images into Python (using the magni.afm.io module): https://github.com/SIP-AAU/Magni</p> <p>The images are provided as-is without warranty of any kind.</p>
Atomic resolution X-ray diffraction images for methanol dehydrogenase from Methylobacterium extorquens.
<p>Atomic resolution X-ray diffraction images for methanol dehydrogenase from <em>Methylobacterium extorquens</em> collected at ESRF (Grenoble, France) using beamline ID29 in May 2002 with an ADSC detector. The diffraction resolution for the first pass is approximately 1.1 - 1.2 Angstroms and a second pass was collected to recoup the reflections that were overloaded in the first pass. More details of the data collection are in the included scanned notes and log files. </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.