Public Data Resource

DFT Benchmarking

Contact: Francesca Tavazza.
Identifier: ark:/88434/mds00r072n
Version: 1.0
All the data in this project are generated running Density Functional (DFT) simulation either on NIST computer clusters of through our collaborators at University of Florida. The final data consist in relaxed atomic structures and corresponding energetic, mechanical, electronic and phonon properties. The metadata consist in the initial and relaxed structures, the description of the code, of the k points and of all the parameters used in running the simulations (energy or real space cutoff, type of minimization, occupation, etc.).
Research Areas
Keywords: Density Functional TheoryDFTUncertaintyUQexchange-correlation comparisonShow more...
These data are public.
Data and related material can be found at the following locations:
  Pade Extrapolates of Material Properties from DFT Calculations
Pade extrapolates of the materials properties of transition metals: Volume per atom (V0), Bulk Modulus (B) and Bulk Modulus Pressure Derivative (B') from DFT calculations performed with the PBE GGA exchange correlation functional in two codes: VASP and DMol3 and the LDA exchange correlation functionals of PW92 (DMol3) and PZ81 (VASP)
  Numerical Precision of Material Properties from DFT Calculations
This database provides the numerical precisions of DFT calculated material properties for transition elements: Equilibrium Volume per atom (V0), Bulk Modulus (B) and the Bulk Modulus Pressure Derivative (dB/dP) as a function of the kpoints density chosen for two codes VASP and DMol3. We use the GGA exchange correlation of PBE in VASP and DMol3 and the LDA exchange correlation of PZ81 in VASP and PWC in DMol3. We calculate the numerical precision using the Pade extrapolates of the material properties, which is hosted at https://researchdata.nist.gov/Materials-/Pade-Extrapolates-of-Material-Properties-from-DFT-/ak25-uy3p .
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Version: 1.0
Cite this dataset
Francesca Tavazza (2017), DFT Benchmarking, National Institute of Standards and Technology, https://data.nist.gov/od/id/5C37CA89A8E4E6C2E0531A5706818FF61872 (Accessed 2025-05-16)
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Machine-readable descriptions of this dataset are available in the following formats:
NERDm
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