May 14, 2025 Dataset Open Access

Fiedler, Lenz; Cangi, Attila

DCAT Export

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    <dct:title>Boron data set for machine learning applications</dct:title>
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    <dct:description>&lt;p&gt;&lt;strong&gt;Boron data set for machine learning applications&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;This dataset contains DFT inputs, outputs, LDOS data and bispectrum descriptor vectors for an &amp;alpha;-rhombohedral boron cell of 144 atoms at room temperature and ambient mass density. All simulations have been performed at an LDOS converged k-grid of 4x4x4 k-points.&lt;/p&gt; &lt;p&gt;This dataset contains one .zip file for each of its five type of data (bispectrum descriptors, LDOS, DFT inputs, DFT outputs and trained models).&lt;/p&gt; &lt;p&gt;&lt;em&gt;Authors:&lt;/em&gt;&lt;/p&gt; &lt;p&gt;- Fiedler, Lenz (HZDR / CASUS)&lt;br&gt; - Cangi, Attila (HZDR / CASUS)&lt;/p&gt; &lt;p&gt;Affiliations&lt;em&gt;:&lt;/em&gt;&lt;/p&gt; &lt;p&gt;HZDR - Helmholtz-Zentrum Dresden-Rossendorf&lt;br&gt; CASUS - Center for Advanced Systems Understanding&lt;/p&gt; &lt;p&gt;&lt;em&gt;Dataset description&lt;/em&gt;&lt;/p&gt; &lt;p&gt;- Total size: 26 GB&lt;br&gt; - System: B144&lt;br&gt; - Temperature(s): 298K&lt;br&gt; - Mass density(ies): 2.483 gcc&lt;br&gt; - Crystal Structure: amorphous (material mp-160 in the materials project)&lt;br&gt; - Number of atomic snapshots: 15&lt;br&gt; - Contents:&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; - ideal crystal structure: no&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; - MD trajectory: no&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; - Atomic positions: no&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; - DFT inputs: yes&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; - DFT outputs (energies): yes&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; - SNAP vectors: yes&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; - dimensions: 108x108x35x94 (last dimension: first three entries are x,y,z coordinates, data size is 91)&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; - units: a.u.&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; - LDOS vectors: yes&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; - dimensions: 108x108x35x241&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; - units: 1/(eV*Angstrom^3)&lt;br&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; - trained networks: yes&lt;/p&gt; &lt;p&gt;&lt;br&gt; &lt;em&gt;Dataset structure&lt;/em&gt;&lt;/p&gt; &lt;p&gt;A .zip file is included for each for each of its five type of data:&lt;/p&gt; &lt;p&gt;- ldos.zip: holds the LDOS vectors (one HDF5 file per snapshot)&lt;br&gt; - bispectrum.zip: holds the bispectrum fingerprint vectors&amp;nbsp; (one HDF5 file per snapshot)&lt;br&gt; - dft_outputs: holds the outputs from the DFT calculations, i.e. energies and simulation parameters in a .json format (one per snapshot)&lt;br&gt; - dft_inputs: holds the inputs for the DFT calculations, in the form of a QE input file (one per snapshot)&lt;br&gt; - models: holds five trained NN models for the data set&lt;/p&gt;</dct:description>
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