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669 results for “ATOM”
Tuning the transport properties of biomolecules atom by atom.
<p>Data presented in the CECAM Conference: BioMolecular Electronics -- BIOMOLECTRO ( link: <a href="https://www.cecam.org/workshop-details/246">https://www.cecam.org/workshop-details/246</a>). </p> <p>Here we discuss how point mutations can result in abrupt changes of the electron transfer properties of proteins, and the findings are rationalized using a combination of Ab-Initio and Molecular dynamics simulations. This is intended to provide an overview of the results published in several peer-reviewed freely available papers:</p> <p>J. Am. Chem. Soc. 139, 15337-15346 (2017) [DOI: 10.1021/jacs.7b06130]<br> Phys. Chem. Chem. Phys. 20, 30392 (2018) [DOI:10.1039/C8CP06862C]<br> Biomolecules 9, 611 (2019) [DOI:10.3390/biom9100611]<br> Biomolecules 9, 506 (2019) [DOI: 10.3390/biom9090506]</p>
All-atom 500-nano seconds 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 500 nano-seconds (ns) production run was performed for the simulation.</p>
Uncovering the Triplet Ground State of Triangular Graphene Nanoflakes Engineered with Atomic Precision on a Metal Surface
<p>OPEN DATA related to the research publication:</p> <p>J. Li, S. Sanz, J. Castro-Esteban, M. Vilas-Varela, N. Friedrich, T. Frederiksen, D. Peña, and J. I. Pascual, <em>Uncovering the triplet ground state of triangular graphene nanoflakes engineered with atomic precision on a metal surface</em>, Phys. Rev. Lett. <strong>124</strong>, 177201 (2020) [arXiv:1912.08298]</p> <p>Abstract: Graphene can develop large magnetic moments in custom-crafted open-shell nanostructures such as triangulene, a triangular piece of graphene with zigzag edges. Current methods of engineering graphene nanosystems on surfaces succeeded in producing atomically precise open-shell structures, but demonstration of their net spin remains elusive to date. Here, we fabricate triangulenelike graphene systems and demonstrate that they possess a spin S=1 ground state. Scanning tunneling spectroscopy identifies the fingerprint of an underscreened S=1 Kondo state on these flakes at low temperatures, signaling the dominant ferromagnetic interactions between two spins. Combined with simulations based on the meanfield Hubbard model, we show that this S=1 π paramagnetism is robust and can be turned into an S=1/2 state by additional H atoms attached to the radical sites. Our results demonstrate that π paramagnetism of high-spin graphene flakes can survive on surfaces, opening the door to study the quantum behavior of interacting π spins in graphene systems.</p>
Data for "Atomic structure of solute clusters in Al-Zn-Mg alloys"
<p>This dataset contains the data used in the publication entitled "<a href="https://www.sciencedirect.com/science/article/abs/pii/S1359645420310119"><strong>Atomic structure of solute clusters in Al-Zn-Mg alloys</strong></a>", published in Acta Materialia 17. December 2020.</p> <p>The data contained herein are:</p> <ul> <li>As-acquired transmission electron microscopy (TEM) images.</li> <li>Atom probe tomography data.</li> <li>All structural models used in density functional theory (DFT) calculations.</li> <li>Structures used for simulating scanning-TEM (STEM) images and nanobeam diffraction (NBD) patterns.</li> </ul> <p> </p> <p>The TEM images includes high angle annular dark field (HAADF) images and selected area diffraction patterns. These are given in .dm3/.dm4 files, and can be opened in e.g. the "<a href="https://www.gatan.com/products/tem-analysis/gatan-microscopy-suite-software">Gatan Microscopy Suite" </a>software. The images are also given as .tif images. The files are names after the "Figx_alloy_condition_xxx". "Figx" refers to the figure in the main article, "alloy" describes the alloy used and "condition" describes from what ageing condition. The uncorrected image series used for Fig. 6c (in the article) is included and requires the <a href="http://lewysjones.com/software/smart-align/">SmartAlign </a>plugin in the Gatan Microscopy Suite to analyse the dataset. SmartAlign allows for correcting rigid and non-rigid distortions in the STEM images in order to reduce effect of specimen drift and scan noise during acquisition. </p> <p>The ATP data is given as a .xlsx file. The data here is the processed data after applying the maximum separation algorithm. The data here is used to produce Figs. 2b and 2c in the paper. <br> <br> The structures used in the DFT calculations are given here as .cif files. These are separated into "Single_clusters" and "Stacked_clusters" and named according to Tabs. 1 and 2 in the Supplementary material of the paper.</p> <p>The two structures used for simulating STEM-HAADF and NBD patterns are given in the folder "TEM_simulations". "Mg32Zn124D_94x94" was used for NBD and "Mg32Zn124D_X_Zn4" was used for HAADF-STEM. The stack used for Supplementary Fig. 7c is labeled "Mg32Zn124D_94x94_slab_1Allayerop.cif".</p> <p> </p> <p> </p> <p> </p>
Storage enhanced nonlinearities in a cold atomic Rydberg ensemble: experimental data
<p>The data show number of input/output photons under different conditions when coherent pulses of light undergo electromagnetically induced transparency (EIT) in a cold cloud of Rubidium 87 atoms via a ladder system connecting the ground state of 87-Rubidium and different Rydberg levels via (see more details in Distante et al. Phys. Rev. Lett. <strong>117</strong>, 113001 (2016) or in the preprint https://arxiv.org/abs/1605.07478)</p> <p>This is the pre-analysed data from which the results in the paper are derived.</p> <p> </p> <ul> <li>The ODS file contains different sheets which correspond to Rydberg states with different principal quantum numbers</li> <li>The PDF contains useful information regarding the conditions of the experiment under which the data was obtained, such as the optical depth (OD) of the cloud, its dimensions, and the Rabi frequency of the coupling beam.</li> </ul>
Atomic Force Microscopy Images of Various Specimens
<p>This data set consists of ten atomic force microscopy images in MI format as well as corresponding previews in PNG format.</p> <p>The microscopy images are of various materials and have been scanned with AFM equipment from Keysight Technologies. Details on the individual images:</p> <ul> <li>image_7.mi - calibration grid with 5 µm pitch size</li> <li>image_8.mi - Celgard (a polymer membrane used in batteries)</li> <li>image_9.mi - Titanium-Tungsten film</li> <li>image_10.mi - AFM image</li> <li>image_11.mi - self-assembled monolayer of lipids on gold</li> <li>image_12.mi - capacity calibration sample for Scanning Microwave Microscopy imaging</li> <li>image_13.mi - capacity calibration sample for Scanning Microwave Microscopy imaging</li> <li>image_14.mi - PS-LDPE-12M (a polymer blend of Polystyrene and Polyolefin Elastomere)</li> <li>image_15.mi - AFM Calibration grid</li> <li>image_16.mi - AFM Calibration grid</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>
Droplet-based Microfluidics Reveals Insights into Cross-Coupling Mechanisms over Single-Atom Heterogeneous Catalysts
<p>Data set supporting the publication of : "Droplet-based Microfluidics Reveals Insights into Cross-Coupling Mechanisms over Single-Atom Heterogeneous Catalysts" (<a href="https://doi.org/10.1002/anie.202401056">https://doi.org/10.1002/anie.202401056</a>) by T. Moragues, G. Giannakakis, A. Ruiz-Ferrando, C. N. Borca, T. Huthwelker, A. Bugaev, A. J. deMello, J. Pérez-Ramírez and S. Mitchell.</p>
Dataset for "Effect of the atomic structure of complexions on the active disconnection mode during shear-coupled grain boundary motion"
<p>This repository contains the data of the simulations and theoretical<br>calculations of the paper "Effect of the atomic structure of complexions on the active disconnection mode during shear-coupled grain boundary motion".</p>
Dataset for Automated Image Analysis for Single-Atom Detection in Catalytic Materials by Transmission Electron Microscopy
<p>Raw and processed image data resulting from the paper "Automated Image Analysis for Single-Atom Detection in Catalytic Materials by Transmission Electron Microscopy", by S. Mitchell, F. Parés, D. Faust Akl, S. M. Collins, D. M. Kepaptsoglou, Q. M. Ramasse, D. Garcia-Gasulla, J. Pérez-Ramírez, and N. López (JACS, 2021). </p> <p>The corresponding code can be found under: <a href="https://github.com/HPAI-BSC/AtomDetection_ACSTEM">GitHub - HPAI-BSC/AtomDetection_ACSTEM</a></p>
Controlled Formation of Dimers and Spatially Isolated Atoms in Bimetallic Au-Ru Catalysts via Carbon-Host Functionalization
<p>Enclosed we report the data in the article: "Controlled Formation of Dimers and Spatially Isolated Atoms in Bimetallic Au-Ru Catalysts via Carbon-Host Functionalization" by Pérez-Ramírez et al.</p>
All-atom molecular dynamics simulations of Synechocystis halorhodopsin (SyHR)
<p>The trajectories of all-atom MD simulations of:<br> 1) Cl<sup>-</sup>-bound SyHR in the ground (GR) state (SyHR_monomer_GR_POPC_CHARMM36_200ns)<br> 2) Cl<sup>-</sup>-bound SyHR in the K state (SyHR_monomer_K_POPC_CHARMM36_200ns)<br> in the monomeric form in a POPC bilayer.<br> 3) SO<sub>4</sub><sup>2-</sup>-bound SyHR in the GR state (SyHR_trimer_GR_POPC_CHARMM36_500ns)<br> in the trimeric form in a POPC bilayer.</p> <p>Simulations have been performed using the CHARMM36 force field, running with the GROMACS 2022 package.</p>
Atomic clock dataset for 'Coherent Optical-Fiber Link Across Italy and France'
<p>Dataset of the comparison of the atomic clocks at LNE-SYRTE and INRIM via optical fibre link between October 2021 and February 2022. Results discussed in Clivati et al., Coherent Optical-Fiber Link Across Italy and France, <em>Phys. Rev. Applied, American Physical Society, </em><em> 18</em>, 054009, <strong>202<em>2</em></strong>.</p> <p>The involved atomic clocks are the Cs fountains SYRTE-F02Cs, IT-CsF2, the Rb fountain SYRTE-F02Rb and the Yb optical lattice clock IT-Yb1.</p> <p>Data is organized in folders, one for each comparison. In the folders data is separated is one file per day. Data is reported as fractional frequency ratios in bins of 864 s. Timetags are reported in modified Julian date (MJD). A validity flag is given where 0 = invalid, valid otherwise. Each folder includes a yaml file with metadata required for generalized data processing as in [Lodewyck et al., 2020]. The Python package used for data processing can be found on <a href="https://github.com/INRIM/tintervals">github.</a></p> <p> </p>
Atomic coordinates used in the solution of a TDRD2 crystal structure
<p>These coordinates were referred to as "Coordinates from [...] an unpublished TDRD2 crystal structure" in Supporting Information of our manuscript <em>Structural basis for arginine methylation-independent recognition of PIWIL1 by TDRD2</em>. This model has not been validated for any other use.</p>
Supporting data for "Fundamental limitations of cavity-assisted atom interferometry"
<p>Supporting data with code to generate Fig. 2 Cavity-induced deformation of a Gaussian input. Publication: DOI:https://doi.org/10.1103/PhysRevA.96.053820</p> <p>arXiv:1710.02448</p> <p>This dataset contains a zip file with raw data sets of all relevant measurements to plot figure 2.</p> <p>Figure 2. Envelope functions of the intracavity field for a 1 m cavity injected with<br> a 1μs pulse for different cavity finesses. All areas are normalized<br> to the input pulse area for comparison. When the pulse duration is<br> comparable to the photon lifetime of the cavity, its envelope function<br> is elongated. Inset: Envelopes without normalization.</p> <p> </p> <p>Further data and information are available from Miguel Dovale <mdovale@star.sr.bham.ac.uk> at reasonable request.</p> <p>School of Physics and Astronomy and Institute of Gravitational Wave Astronomy, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom</p>
Absolute frequency measurement of the 1 S 0 – 3 P 0 transition of 171 Yb with a link to International Atomic Time
<p>Dataset of the INRIM Yb clock measured respect to TAI collected between October 2018 to February 2019.<br> </p> <p>YbvsSIm-viaEAL.dat: montly data with columns</p> <pre><code>MJDstart: start date in MJD MJDstop: stop date in MJD MJDmed: mid point date in MJD MJDbaro: baricenter date in MJD Ybduty: Yb clock duty time y0=Yb/HM3: ratio between Yb clock and H Maser 03 u0: statistical uncertainty of y0 uB0: systematic uncertainty of y0 y1=extrap.: extrapolation over HM3 udead1: uncertainty of y1 from dead times udrift1: uncertainty of y1 from HM3 drift HM3drift/d: HM3 drift per day udrift/d: uncertainty of HM3 drift y2=HM3/UTCit: ratio between HM3 and UTC(IT) u2: uncertainty of y2 y3=UTCit/TAI: ratio between UTC(IT) and TAI u3: uncertainty of y3 y4=EALext.: extrapolation over EAL udead4: uncertainty of y4 from dead times udrift4: uncertainty of y4 from EAL drift y5=-d: ratio between TAI and the SI second from Circular T u5: uncertainty of y5 uA5: statistical uncertainty of y5 uB5: systematic uncertainty of y5 y=Yb/SI: final ratio beween the Yb clock and the Si second uA: not used uB: not used u: uncertainty of y </code></pre> <p>YbvsTAId.dat: data every 5 days with columns:</p> <pre><code>MJDstart: start date in MJD MJDstop: stop date in MJD MJDmed: mid point date in MJD MJDbaro: baricenter date in MJD Ybduty: Yb clock duty time y0=Yb/HM3: ratio between Yb clock and H Maser 03 u0: statistical uncertainty of y0 uB0: systematic uncertainty of y0 y1=extrap.: extrapolation over HM3 udead1: uncertainty of y1 from dead times udrift1: uncertainty of y1 from HM3 drift HM3drift/d: HM3 drift per day udrift/d: uncertainty of HM3 drift y2=HM3/UTCit: ratio between HM3 and UTC(IT) u2: uncertainty of y2 y3=UTCit/TAI: ratio between UTC(IT) and TAI u3: uncertainty of y3 y=Yb/TAI: final ratio beween the Yb clock and TAI uA: not used uB: not used u: uncertainty of y </code></pre> <p> </p>
Dataset of the article Optical Tweezer Arrays of Erbium Atoms
<p>Datasets of the experimental data of the article Optical Tweezer Arrays of Erbium Atoms. The dataset is organized in folders, one for each figure. The data is written as tables in text files and it includes theoretical curves and fits of the same figure. A Python script is included to reproduce the figures.</p>
Nature of GaOx Shells Grown on Silica by Atomic Layer Deposition
<p>Raw data for the article "Nature of GaOx Shells Grown on Silica by Atomic Layer Deposition", already published in Chemistry of Material.</p>
Data for "Constraints on the Observability of Energetic Neutral Atoms from the Magnetosphere-Atmosphere Interactions at Callisto and Europa" by Haynes et al.
<p>Accompanying data products for publication entitled "Constraints on the Observability of Energetic Neutral Atoms from the Magnetosphere-Atmosphere Interactions at Callisto and Europa". The manuscript was submitted to JGR Space Physics shortly after upload.</p> <p>Data includes all simulation outputs that are depicted in this work, both for the AIKEF hybrid model (i.e., Figure 4) and the model used to produce synthetic ENA images (Figures 3, 6, 8, 9, 11, A1, and B1). All other figures in the work are used for illustrative purposes and were not generated with simulation output. </p> <p>Information regarding the organization and file structure can be found in H24_data_readme.txt , as well as which dataset corresponds to which figure. Any inquiries, questions, or comments may be addressed through the email associated with this data publication.</p>
Enhanced Catalytic Performance of a Single-Atom Cu on Mo2C toward the CO2/CO Hydrogenation to Methanol: A First-Principles Study_dataset
<p>Dataset of inputs and outputs concerning mechanisms, bader charge analysis, frequency analysis and model used in the study namely: Enhanced Catalytic Performance of a Single-Atom Cu on Mo2C toward the CO2/CO Hydrogenation to Methanol: A First-Principles Study published on <em>Cat. Sci. Technol. </em>(DOI: 10.1039/d4cy00703d).</p>
Supplementary Materials for "Depolarization of MgH Solar Lines by Collisions with Hydrogen Atoms"
<p>The files "MgHH_Potential_Singlet" and "MgHH_Potential_Triplet" respectively hold results of ab initio calculation of the potential energy surfaces (PESs), V(R,θ) in units of cm^-1, for the singlet (1A') and triplet (3A') states of the MgH-H system. Here R represents the distance (in atomic units) from the center of mass of MgH molecule to the H atom, and θ is the rotation angle (in degrees) of the H atom around the MgH. All the PESs are obtained using the MOLPRO package (e.g. Werner et al. 2010).</p> <p><br> The files "MgHH_Sigma_0toL_Singlet.csv" and "MgHH_Sigma_0toL_Triplet.csv" respectively contain results of the infinite-order sudden (IOS) approximation calculation of cross sections, σ(0->L) in units of Angstrom^2, as functions of energy in units of cm^-1 for the 1A' and 3A' states of the MgH-H system. The IOS cross sections are calculated using MOLSCAT code (Hutson & Green 1994). The depolarization and transfer of polarization cross sections can be calculated from the IOS cross sections via Eqs. (1) & (2) of Qutub et al. 2020.</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.