February 18, 2022 Dataset Open Access

Fiedler, Lenz; Cangi, Attila

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  "datePublished": "2022-02-18", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "@type": "Dataset", 
  "version": "1.1.0", 
  "creator": [
    {
      "name": "Fiedler, Lenz", 
      "affiliation": "HZDR / CASUS", 
      "@id": "https://orcid.org/0000-0002-8311-0613", 
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    {
      "name": "Cangi, Attila", 
      "affiliation": "HZDR / CASUS", 
      "@id": "https://orcid.org/0000-0001-9162-262X", 
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  "name": "LDOS/SNAP data for MALA: Beryllium at 298K", 
  "@id": "https://doi.org/10.14278/rodare.1834", 
  "description": "<pre><em><strong>Beryllium data set for Machine Learning applications</strong></em>\n</pre>\n\n<p> </p>\n\n<p>This dataset contains DFT inputs, outputs, LDOS data and fingerprint vectors for a beryllium cell at ambient conditions and varying sizes. Different levels of k-grid convergence were employed:<br>\n -&nbsp; Gamma point (gamma_point)<br>\n -&nbsp; total energy convergence (k-grid converged to 1meV/atom to total energy difference, total_energy_convergence)<br>\n -&nbsp; LDOS convergence (k-grid converged to LDOS without unphyiscal oscillations, ldos_convergence)</p>\n\n<p> </p>\n\n<p>The data set contains a .zip file for each system size (see below), as well as one .zip file containing sample scripts for recalculation and preprocessing of data.<br>\n The cutoff energy was converged with respect to the energy convergence and held fixed 40Ry for all three levels of k-grids. Note that not for all sizes of unit cells data for all types of k-grid were generated.</p>\n\n<p> </p>\n\n<pre><strong>Authors:</strong>\n\n<em>- </em>Fiedler, Lenz (HZDR / CASUS)\n<em>- </em>Cangi, Attila (HZDR / CASUS)\n\n<em>Affiliations</em><strong>:</strong>\n\nHZDR - Helmholtz-Zentrum Dresden-Rossendorf\n\nCASUS - Center for Advanced Systems Understanding\n\n<strong>Dataset description</strong>\n\n<em>- </em>Total size: 143G GB \n<em>- </em>System: Be128, Be256, Be512, Be1024, Be2048\n<em>- </em>Temperature(s): 298K\n<em>- </em>Mass density(ies): 1.896 gcc\n<em>- </em>Crystal Structure: hpc (material mp-87 in the materials project)\n<em>- </em>Number of atomic snapshots: 145\n  <em>  - </em>40 (Be128)\n  <em>  - </em>35 (Be256)\n   <em>- </em>30 (Be512)\n   <em>- </em>20 (Be1024)\n   <em>- </em>10 (Be2048)\n<em>- </em>Contents:\n   <em>- </em>ideal crystal structure: yes\n  <em>  - </em>MD trajectory: yes\n  <em>  - </em>Atomic positions: yes\n   <em>- </em>DFT inputs: yes\n  <em>  - </em>DFT outputs (energies): yes\n  <em>  - </em>SNAP vectors: yes (partially, see below)\n      <em>  - </em>dimensions: XxYxZx94 (last dimension: first three entries are x,y,z coordinates, data size is 91), where X, Y, Z are:\n         <em>- </em>Be128: 72x72x120 (size per file: 447MB)\n         <em>- </em>Be256: 144x72x120  (size per file: 893MB)\n         <em>- </em>Be512: 144x144x120 (size per file: 1.8GB)\n      <em>  - </em>units: a.u./Bohr\n  <em>  - </em>LDOS vectors: yes (partially, see below)\n      <em>  - </em>dimensions: XxYxZx250, where X, Y, Z are:\n         <em>- </em>Be128: 72x72x120 (size per file: 1.2GB)\n         <em>- </em>Be256: 144x72x120  (size per file: 2.4GB)\n         <em>- </em>Be512: 144x144x120 (size per file: 4.7GB)\n      <em>  - </em>units: 1/eV\n      <em>- </em>note: LDOS parameters are the same for all sizes of the unit cell\n  <em>  - </em>trained networks: no\n\n<strong>Data generation</strong>\n\nIdeal crystal structures were obtained using the Materials Project. (https://materialsproject.org/materials/mp-87/)\nDFT-MD calculations were performed using either QuantumESPRESSO (https://www.quantum-espresso.org/, QE, for Be128, Be256 and Be512) or the Vienna Ab initio Simulation Package (https://www.vasp.at/, VASP, for Be1024, Be2048). DFT calculations were performed using QuantumESPRESSO. \nFor the VASP calculations, the standard VASP pseudopotentials were used. For Quantum Espresso, pslibrary was used (https://dalcorso.github.io/pslibrary/).\nSNAP vectors were calculated using MALA (https://github.com/mala-project/mala) and its LAMMPS (https://github.com/mala-project/mala) interface. The LDOS was preprocessed using MALA as well.\n\n<strong>Dataset structure</strong>\n\nThe folder called &quot;sample_inputs&quot; is provided to show how MALA preprocessing and LDOS calculation have been performed. \nFor each temperature/mass density/number of atoms, the following subfolders exist:\n\n<em>- </em>md_inputs: Input files for the MD simulations, either as QE or VASP file(s)\n<em>- </em>md_outputs: The MD trajectory plus a numpy array containing the temperatures at the individual time steps\n<em>- </em>gamma_point\n<em>- </em>total_energy_convergence\n<em>- </em>ldos_convergence\n\nEach gamma_point/total_energy_convergence/ldos_convergence contains the following folders:\n\n<em>- </em>ldos: holds the LDOS vectors\n<em>- </em>fingerprints: holds the SNAP fingerprint vectors\n<em>- </em>snapshots: holds the atomic positions of the atomic snapshots for which DFT and LDOS calculations were performed (as .xyz files)\n<em>- </em>dft_outputs: holds the outputs from the DFT calculations, i.e. energies in the form of a QE output file\n<em>- </em>dft_inputs: holds the inputs for the DFT calculations, in the form of a QE input file\n\nPlease note that the numbering of the snapshots is contiguous per temperature/mass density/number of atoms, NOT within the k-grids themselves. \nAlso, LDOS and fingerprint files have only been calculated for snapshots in the ldos_convergence \nfolders. Therefore, no LDOS and fingerprint files have been calculated for the 1024 anf 2048 atom systems.\n</pre>", 
  "identifier": "https://doi.org/10.14278/rodare.1834"
}