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Boron data set for machine learning applications

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DataCite Commons2025-05-15 更新2025-05-18 收录
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https://rodare.hzdr.de/record/3745
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<strong>Boron data set for machine learning applications</strong> This dataset contains DFT inputs, outputs, LDOS data and bispectrum descriptor vectors for an α-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. This dataset contains one .zip file for each of its five type of data (bispectrum descriptors, LDOS, DFT inputs, DFT outputs and trained models). <em>Authors:</em> - Fiedler, Lenz (HZDR / CASUS)<br> - Cangi, Attila (HZDR / CASUS) Affiliations<em>:</em> HZDR - Helmholtz-Zentrum Dresden-Rossendorf<br> CASUS - Center for Advanced Systems Understanding <em>Dataset description</em> - Total size: 26 GB<br> - System: B144<br> - Temperature(s): 298K<br> - Mass density(ies): 2.483 gcc<br> - Crystal Structure: amorphous (material mp-160 in the materials project)<br> - Number of atomic snapshots: 15<br> - Contents:<br>     - ideal crystal structure: no<br>     - MD trajectory: no<br>     - Atomic positions: no<br>     - DFT inputs: yes<br>     - DFT outputs (energies): yes<br>     - SNAP vectors: yes<br>         - dimensions: 108x108x35x94 (last dimension: first three entries are x,y,z coordinates, data size is 91)<br>         - units: a.u.<br>     - LDOS vectors: yes<br>         - dimensions: 108x108x35x241<br>         - units: 1/(eV*Angstrom^3)<br>     - trained networks: yes <br> <em>Dataset structure</em> A .zip file is included for each for each of its five type of data: - ldos.zip: holds the LDOS vectors (one HDF5 file per snapshot)<br> - bispectrum.zip: holds the bispectrum fingerprint vectors  (one HDF5 file per snapshot)<br> - dft_outputs: holds the outputs from the DFT calculations, i.e. energies and simulation parameters in a .json format (one per snapshot)<br> - dft_inputs: holds the inputs for the DFT calculations, in the form of a QE input file (one per snapshot)<br> - models: holds five trained NN models for the data set
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Rodare
创建时间:
2025-05-14
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