Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
41
datasets available to search
ShareScore release 0.9.0
Dataset results
41 results for “atomistic simulation”
Atomistic trajectories from ab-initio molecular dynamics simulations of wetted TiO2 nanoparticle
<p>This repository contains atomistic trajectories from ab-initio molecular dynamics simulations of water and TiO2 nanoparticle described in the paper:</p> <p>E. G. Brandt, L. Agosta and A.P.Lyubartsev, " Reactive wetting properties of TiO2 nanoparticles predicted by ab initio molecular dynamics simulations", Nanoscale, 8, 13385-13398 (2016) DOI: 10.1039/c6nr02791a</p> <p>The trajectories are saved in the .xtc format, and initial structures with specification of atom types are given in the .pdb format.</p> <p>The name of each file contains brief information about the simulated system:</p> <p>TiO2 : composition of the nanoparticle<br> n24 : number of TiO2 units in the nanoparticle<br> anatase/brookite/rutile : type of crystall structure<br> - a number 0 - 30 : number of water molecules in the simulation<br> 2fs - the time step</p> <p>For more details, see the referred paper</p>
The Unfolding Journey of Superoxide Dismutase 1 Barrels Under Crowding: Atomistic Simulations Shed Light on Intermediate States and Their Interactions With Crowders
<p>This data accompanies the article entitled <em>The Unfolding Journey of Superoxide Dismutase 1 Barrels Under Crowding: Atomistic Simulations Shed Light on Intermediate States and Their Interactions With Crowders</em>, published in J. Phys. Chem. Lett. (<a href="https://doi.org/10.1021/acs.jpclett.0c00699">https://doi.org/10.1021/acs.jpclett.0c00699</a>).</p> <p><strong>01_SOD1bar_unfolding_REST2.zip: </strong>The zip archive includes REST2 trajectories for the three systems investigated in the paper: 1:1 packing, 2:1 packing, and the dilute case. The trajectories are saved in the GROMACS XTC file format, separately for each temperature (i=0,...,23). Given the large trajectory sizes, only protein coordinates (SOD1bar + crowders) are reported, and the output frequency is reduced to 100 ps. A starting geometry (in the Gromos87 GRO format) after equilibration of the initial packing is provided for each REST2 simulation (conf_prot.gro). Moreover, for each REST2 simulation, an xarray (http://xarray.pydata.org) dataset, saved in the netCDF file format, is included with computed fraction of native contacts, secondary structure content, and the Calpha RMSD of the barrel core (beta sheets beta1 - beta8) with respect to the crystal structure.</p> <p><strong>02_SOD1bar_geometries_representative_unfolding.zip:</strong> Representative SOD1bar geometries along the unfolding pathway (presented in Figure 3 of the paper).</p> <p><strong>03_SOD1bar_geometries_loopVII.zip: </strong>SOD1bar geometries with varying loop VII conformation which were isolated from dilute REST2 and which are presented in Figure S9 of the paper.</p>
Fracture Toughness of Off-Stoichiometric B2 NiAl as determined by micromechanical tests and atomistic simulations
<p>KQJ-Alconcentration-NiAl_experiment.csv : semicolon-separated ASCII file containing the fracture toughness (2nd column) and the contribution of the plastic deformation to the fracture toughness (3rd column) as function of Al concentration (1st column) for off-stoichiometric B2 NiAl as determined by micro mechanical tests on notched cantilever beams.</p> <p>KIc-Alconcentration-NiAl_static-simulations.dat : space-separated ASCII file containing the fracture toughness (K_Ic) of B2 NiAl (2nd column) for different Al concentrations (first column) as as determined by static atomistic calculations with the<br> # Potential by G. P. P. Pun, Y. Mishin, (Phil. Mag. 89 (34-36) (2009) 3245– 3267).</p> <p>NiAl_Pun_conc_0.40-0.65Ni_Esurf110_Cij.dat : space-separated ASCII file containing the energy of {110} surfaces (2nd column) and elastic constants (columns 3-5) of B2 NiAl for different Ni concentrations (f1st column) as determined by atomistic simulations using the the potential by G. P. P. Pun, Y. Mishin, (Phil. Mag. 89 (34-36) (2009) 3245– 3267)</p> <p>KIc-Alconcentration-NiAl_theory.dat : space-separated ASCII file containing the fracture toughness (K_Ic) of B2 NiAl (2nd column) for different Al concentrations (1st column) as calculated by the Griffith equation.</p> <p> </p>
Dataset for article - Dislocation dynamics in Ni: Parameterising dislocation trajectories from atomistic simulations
<p>Data supporting findings in "Dislocation dynamics in Ni: Parameterising dislocation trajectories from atomistic simulations". In this work, 8 identical Molecular Dynamics (MD) simulations of edge dislocations in pure Nickel were run and analysed, where dislocation positions were extracted and each dislocation is tracked for further analysis. Each simulation only differs in the random seed used for setting the initial atom velocities. Files needed to reproduce a specific simulation can be found in the directories provided in <em>data.zip</em>:</p> <ul> <li>fr_18430</li> <li>fr_27743</li> <li>fr_44345</li> <li>fr_46165</li> <li>fr_54382</li> <li>fr_54992</li> <li>fr_97181</li> <li>fr_98232</li> </ul> <p>The random seed needed to set the initial velocities of the atoms are set in the LAMMPS script. The log files generated by LAMMPS are provided for the different stages of a given simulation in the <em>LAMMPS_logs</em> sub-directories. The corresponding output files from the OVITO DXA are also included in the sub-directory <em>Ni_disloc_const</em>. The files <em>disloc_data_*.ca</em> contain the raw output from the OVITO DXA and can be opened directly in OVITO. The <em>disloc_data_*.txt </em>files contain information extracted from the OVITO DXA in a format that can be read in and processed by the dislocation tracking code (<a href="https://github.com/geraldineanis/DislocCode/tree/v1.0.0">https://github.com/geraldineanis/DislocCode/tree/v1.0.0</a>). The wildcard character "*" is replaced with the simulation timestep. In each directory, the dislocation position vs. time data is included as a text file<em> </em>named<em> </em><em>perfect_pos_<seed>.txt</em>. The Mishin 2004 EAM interatomic potential file <em>NiAl_Mishin_2004.eam.alloy</em> used to generate the data is also provided.</p> <p>Additional simulations were carried out at a range of applied shear stresses (20 MPa - 50 MPa). Files needed to reproduce theses simulations are provided in <em>data_stress.zip </em>and follow the same format described above.</p> <p>The data provided here was generated with the <code>LAMMPS/29Sep2021-kokkos</code><em> </em>module on the SULIS Tier 2 HPC platform, which has been built with the OpenMP backend of the <code>kokkos</code> package and uses the <code>foss-2021b</code> toolchain (<a href="https://docs.easybuild.io/common-toolchains/">https://docs.easybuild.io/common-toolchains/</a>). For further information, please refer to <a href="https://sulis-hpc.github.io/appnotes/lammps.html">https://sulis-hpc.github.io/appnotes/lammps.html</a>.</p> <p>For more details on the calculations, please refer to the publication (in preparation). Please refer to the GitHub repository at <a href="https://github.com/geraldineanis/DislocCode/tree/v1.0.0">https://github.com/geraldineanis/DislocCode/tree/v1.0.0</a> for the analysis tools developed and for detailed instructuctions for their use.</p>
Assessment of mutation probabilities of KRAS G12 missense mutants and their long-time scale dynamics by atomistic molecular simulations and Markov state modeling: Datasets.
<p>Datasets related to the publication [1].<br> Including:</p> <ul> <li>KRAS G12X mutations derived from COSMIC v.79 [http://cancer.sanger.ac.uk/cosmic/] (KRAS_G12X_mut_COSMICv79..xlsx)</li> <li>RMSFs (300-2000ns) of GDP-systems (300_2000rmsf_GDP_systems_RAW_AVG_SE.xlsx)</li> <li>RMSFs (300-2000ns) of GTP-systems (300_2000RMSF_GTP_systems_RAW_AVG_SE.xlsx)</li> <li>PyInteraph analysis data for salt-bridges and hydrophobic clusters (.dat files for each system in the PyInteraph_data.zip-file)</li> <li>Backbone trajectories for each system (residues 4-164; frames for every 1ns). Last number (e.g. _1) refers to the replica of the simulated system.</li> <li>backbone_4-164.gro/.pdb/.tpr -files (resid 4-164) </li> </ul> <p><br> [1] Pantsar T et al. Assessment of mutation probabilities of KRAS G12 missense mutants and their long-time scale dynamics by atomistic molecular simulations and Markov state modeling. <em>PLoS Comput Biol Submitted</em> (2018)</p>
Data for 'Grain boundary segregation and phase separation in ceria-zirconia from atomistic simulation'
<p>Data for the article 'Grain boundary segregation and phase separation in ceria-zirconia from atomistic simulation', including input and output files for simulations, and scripts to perform data analysis and generate figures.</p>
Topology and structure of Au144(SRNH3+)60 from "Atomistic Simulations of Functional Au144(SR)60 Gold Nanoparticles in Aqueous Environment"
<p>Positively charged monolayer-protected gold nanoparticles (AuNPs) structure and topology files for GROMACS used in DOI: 10.1021/jp301094m. The final structure of the simulation reported in DOI: 10.1021/jp301094m for the neutral case is provided.</p> <p>The gold nanoparticle contain a core of 144 Au atoms and 60 functionalized alkanethiol side groups (undecanyl chain, R = C11H22), each possessing a positively charged amonium terminal group.</p> <p>When using this structure do not forget to cite DOI: 10.1021/jp301094m. </p> <p>NOTE1: Different versions for the topology files are provided of both AuNPs. All versions were used for the publication. The changes only affect the core surface and therefore had no influence in the reported properties. Still we recommentd using the latest version: AU144SRNH360_v3.itp.</p> <p>NOTE2: The original simulations used GROMACS 4.0.5. The files should work, however, as well up to GROMACS 4.6.7.</p>
Topology and structure of Au144(SRCOO-)60 from "Atomistic Simulations of Functional Au144(SR)60 Gold Nanoparticles in Aqueous Environment"
<p>Negatively charged monolayer-protected gold nanoparticles (AuNPs) structure and topology files for GROMACS used in DOI: 10.1021/jp301094m. The final structure of the simulation reported in DOI: 10.1021/jp301094m for the neutral case is provided.</p> <p>The gold nanoparticle contain a core of 144 Au atoms and 60 functionalized alkanethiol side groups (undecanyl chain, R = C11H22), each possessing a negatively charged carboxylic terminal group.</p> <p>When using this structure do not forget to cite DOI: 10.1021/jp301094m. </p> <p>NOTE1: Different versions for the topology files are provided of both AuNPs. All versions were used for the publication. The changes only affect the core surface and therefore had no influence in the reported properties. Still we recommentd using the latest version: AU144SRCOO60_v2.itp.</p> <p>NOTE2: The original simulations used GROMACS 4.0.5. The files should work, however, as well up to GROMACS 4.6.7.</p>
Atomistic spin dynamics simulations of iron and cobalt
<p>Atomistic spin dynamics (ASD) simulations of ultrafast demagnetization in ferromagnetic iron and cobalt. The ASD simulations here are energy-conserving, which means that energy flow into and out of the spin system is considered.</p> <p>The dataset contains simulations at four different pump laser fluences for iron and six different fluences for cobalt. The excitation was assumed to be homogeneous throughout the simulated volume.</p> <p>The heat capacities and electron-phonon coupling parameters which were used in the ASD simulations are provided in the folder "heat capacities and G_ep".</p> <p>More information is available here:<br> - https://arxiv.org/abs/2110.00525<br> - Zahn et al. Phys. Rev. Research 3, 023032 (2021)<br> https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.3.023032</p> <p> </p>
Raw data to: Molecular Interplay of ADAMTS13-MDTCS and von Willebrand Factor-A2: Deepened Insights from Extensive Atomistic Simulations
<p>Structural ensembles of ADAMTS13-MDTCS in isolation and in interaction with the von Willebrand factor A2 domain, as obtained from extensive TIGER2h replica exchange simulations. Scripts to filter for certain binding states by given contacts, extract conformational clusters, a movie illustrating the binding transition between recruitment (Model2) and proteolytic (Model1) states, PDB files of both models for further investigation along with upcoming experimental verification.</p>
Data Supplement for "Impact of Charged Surfaces on the Structure and Dynamics of Polymer Electrolytes: Insights from Atomistic Simulations"
<p>Data set containing the molecular dynamics simulation data used for the journal article "Impact of Charged Surfaces on the Structure and Dynamics of Polymer Electrolytes: Insights from Atomistic Simulations" (<span>Andreas Thum, </span><span>Diddo Diddens, </span><span>Andreas Heuer, </span><em>J. Phys. Chem. C</em> <strong>2021</strong>, <em>125</em>, 25392−25403, <a href="https://doi.org/10.1021/acs.jpcc.1c07751">https://doi.org/10.1021/acs.jpcc.1c07751</a>).</p>
Data from: Free energy analysis of peptide-induced pore formation in lipid membranes by bridging atomistic and coarse-grained simulations
Open the record for dataset details and reuse information.
Dislocation Mobilities in BCC and B2 Metals as Determined from Atomistic Simulations
<p>Data regarding the velocity of dislocations subjected to different stresses at temperatures determined by molecular dynamics simulations in a tar file.</p> <p>The simulation setup and main results are presented in<br> Setup_and_resulting_plots.pdf</p> <p>The folder RESULTS contains the results for edge dislocations in the folder EDGE-DISLOCATION and the results of screw dislocations in the folder SCREW-DISLOCATION</p> <p>Two types of resulting data are provided in RESULTS:<br> - Steady state velocities (6th column, unit Angstrom/ps) as function of shear stress (2nd column, unit MPa) and temperature (1st column, unit Kelvin),<br> these are named: v_tau_T*.dat<br> - Dislocation position (2nd column, unit Angstrom) as function of time (1st column, unit ps) for different dislocations, stress and temperature,<br> these are named: x_t_T*K_tau*MPa_*.dat</p> <p># Studied Materials/crystal structures<br> Fe/bcc<br> W/bcc<br> NiAl/B2</p> <p># Studied potentials:<br> Fe_Chiesa : https://www.ctcms.nist.gov/potentials/entry/2011--Chiesa-S-Derlet-P-M-Dudarev-S-L-Swygenhoven-H-V--Fe-33/<br> Fe_Mendelev_II: https://www.ctcms.nist.gov/potentials/entry/2003--Mendelev-M-I-Han-S-Srolovitz-D-J-et-al--Fe-2/<br> W_Wang : https://www.ctcms.nist.gov/potentials/entry/2013--Wang-J-Zhou-Y-L-Li-M-Hou-Q--W/<br> NiAl_Pun : https://www.ctcms.nist.gov/potentials/entry/2009--Purja-Pun-G-P-Mishin-Y--Ni-Al/</p> <p># Studied dislocations / Potential / Temparature<br> perfect edge dislocation / Fe_Chiesa / 30K<br> perfect edge dislocation / Fe_Chiesa / 300K<br> perfect edge dislocation / Fe_Mendelev_II / 30K<br> perfect edge dislocation / Fe_Mendelev_II / 300K<br> perfect edge dislocation / W_Wang / 30K<br> perfect edge dislocation / W_Wang / 300K<br> perfect edge dislocation / NiAl_Pun / 30K<br> perfect edge dislocation / NiAl_Pun / 300K<br> perfect screw dislocation / NiAl_Pun / 30K</p> <p>The files necessary to reproduce the results in the folder SIMULATION-FILES and described there.</p>
Spidroin Martini Coarse grain and atomistic simulation results
<p>The pdb files contained in this zip archive are the outputs of our simulations of the pre-spun silk proteins (MaSp1 and MaSp2) found in Black Widow silk dope. We used a combination of Martini V2.6 Martini 3.0 coarse grain, Alphafold, and Charmm36 atomistic simulations. </p>
Dataset for "Mo-Si alloys studied by atomistic computer simulations using a novel machine-learning interatomic potential: Thermodynamics and interface phenomena"
<p>This dataset was used to fit a general purpose machine-learning interatomic potential for Mo-Si alloys based on the Atomic Cluster Expansion (ACE) formalism. It supports the paper "Mo-Si alloys studied by atomistic computer simulations using a novel machine-learning interatomic potential: Thermodynamics and interface phenomena".</p>
LAMMPS atomistic simulation data of a binary LJ glass
<p>Simulation data associated with the published papers:</p> <ul> <li>Correlated disorder in a model binary glass through a local SU (2) bonding topology, P. M. Derlet, Phys. Rev. Mater. 4, 125601 (2020).</li> <li>Micro-plasticity in a model binary glass, PM Derlet and R. Maass, Acta. Mater. 209, 116771 (2021).</li> <li>Viscosity and transport in a model fragile metallic glass, P. M. Derlet, H. Bocquet, and R. Maass, Phys. Rev Mater 5, 125601 (2021).</li> </ul>
Thermodynamics of alkali feldspar solid solutions with varying Al–Si order: atomistic simulations using a neural network potential - Accompanying Data
<p>This dataset accompanies the manuscript: "Thermodynamics of alkali feldspar solid solutions with varying Al–Si order: atomistic simulations using a neural network potential". It contains:</p> <ul> <li>LAMMPS-data files of the relaxed 8x6x8 systems for the three ordering types across Na-K composition, </li> <li>template input files for the minimization and for the semi grand canonical Monte Carlo + molecular dynamics simulation,</li> <li>the training and testing data with and without the point charge correction,</li> <li>the neural network potential committee and a modified n2p2 source that is necessary for running the special weighted atom centered symmetry functions. </li> </ul> <p>The algorithm to create the Al-Si and Na-K disorder is hosted on <a href="https://github.com/alexgorfer/Alkali-feldspar-disorder-generator">https://github.com/alexgorfer/Alkali-feldspar-disorder-generator</a> instead.</p>
Atomistic Fingerprint of Hyaluronan-CD44 Binding: Weak E-field Simulations, Upright Mode
<p>Simulation files (Gromacs 4.6.7 format) for the "E-field weak, upright mode" simulations in Ref. [1]. There are 20 replicas marked with "_1" , "_2", etc.</p> <p>Files include:</p> <p>-trajectories (.xtc) that are saved every 100ps <br> -initial structures (.gro), <br> -run input files (.tpr)<br> -checkpoint files (.cpt)<br> -simulation parameter files (.mdp)<br> -system topology file (.top)<br> -topology files included in the system topology file (.itp)</p> <p>[1] Vuorio J. et al., Atomistic Fingerprint of Hyaluronan-CD44 Binding, PLOS Comp. Biol., 2017. (Submitted)</p>
Atomistic Fingerprint of Hyaluronan-CD44 Binding: Weak E-field Simulations, Parallel Mode
<p>Simulation files (Gromacs 4.6.7 format) for the "E-field weak, parallel mode" simulations in Ref. [1]. There are 20 replicas marked with "_1" , "_2", etc.</p> <p>Files include:</p> <p>-trajectories (.xtc) that are saved every 100ps <br> -initial structures (.gro), <br> -run input files (.tpr)<br> -checkpoint files (.cpt)<br> -simulation parameter files (.mdp)<br> -system topology file (.top)<br> -topology files included in the system topology file (.itp)</p> <p>[1] Vuorio J. et al., Atomistic Fingerprint of Hyaluronan-CD44 Binding, PLOS Comp. Biol., 2017. (Submitted)</p>
Atomistic Fingerprint of Hyaluronan-CD44 Binding: Weak E-field Simulations, Crystallographic Mode
<p>Simulation files (Gromacs 4.6.7 format) for the "E-field weak, crystallographic mode" simulations in Ref. [1]. There are 20 replicas marked with "_1" , "_2", etc.</p> <p>Files include:</p> <p>-trajectories (.xtc) that are saved every 100ps <br> -initial structures (.gro), <br> -run input files (.tpr)<br> -checkpoint files (.cpt)<br> -simulation parameter files (.mdp)<br> -system topology file (.top)<br> -topology files included in the system topology file (.itp)</p> <p>[1] Vuorio J. et al., Atomistic Fingerprint of Hyaluronan-CD44 Binding, PLOS Comp. Biol., 2017. (Submitted)</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.