Density functional theory-based electric field gradient database

Abstract

The deviation of the electron density around the nuclei from spherical symmetry determines the electric field gradient (EFG), which can be measured by various types of spectroscopy. Nuclear Quadrupole Resonance (NQR) is particularly sensitive to the EFG. The EFGs, and by implication NQR frequencies, vary dramatically across materials. Consequently, searching for NQR spectral lines in previously uninvestigated materials represents a major challenge. Calculated EFGs can significantly aid at the search’s inception. To facilitate this task, we have applied high-throughput density functional theory calculations to predict EFGs for 15187 materials in the JARVIS-DFT database. This database, which will include EFG as a standard entry, is continuously increasing. Given the large scope of the database, it is impractical to verify each calculation. However, we assess accuracy by singling out cases for which reliable experimental information is readily available and compare them to the calculations. We further present a statistical analysis of the results. The database and tools associated with our work are made publicly available by JARVIS-DFT (https://www.ctcms.nist.gov/~knc6/JVASP.html) and NIST-JARVIS API (http://jarvis.nist.gov/).

Large scale dataset of real space electronic charge density of cubic inorganic materials from density functional theory (DFT) calculations

“…These calculations are performed until the maximal Hellmann-Feynman force component smaller than 10 −3 eVÅ −1 , and the total energy convergence tolerance is set to be 10 −6 eV. To obtain accurate lattice parameters 34 – 36 , the Opt-B88vdW functional 37 is taken into account to deal with the long term interactions in the exchange-correlation interaction. The k-point grids (KPOINTS) for each material used to calculate their CHGs are the same KPOINTS files as used in static calculations in Materials Project database (downloaded in around June 2020), which have been proved to achieve good convergence in previous works.…”

“…Besides, we extract initial structures of each material from the Material Project database and re-optimize them using the opt-B88vdW functional instead of the GGA/PBE functional used in the Material Project database. This would be more accurate because the opt-B88vdW functional has been proved to give much improved lattice parameters for both van der Waals (vdW) and non-vdW solids 34 , which are essential to the calculations of accurate electronic charge density. In addition, such functional is usually adopted in the construction of many other properties related database 8 , 34 , 36 , 41 , hence our datasets would be useful for further analysis and comparisons since consistent computational procedures are adopted.…”

“…The calculated electronic charge density ρ ( r ) is a widely accepted quantity for predicting physical properties 34 benefitting from the significant predictive power of the state-of-the-art DFT calculations. Here we elaborate several patterns of the calculated ρ ( r ) and compare them with those reported in previous theoretical or experimental studies, to further verify the correctness of our simulations.…”

Database of Wannier tight-binding Hamiltonians using high-throughput density functional theory

“…We use our Wannierization workflow on the JARVIS-DFT ( https://jarvis.nist.gov/jarvisdft ) database which is a part of the MGI at NIST. The NIST-JARVIS 40 ( https://jarvis.nist.gov ) has several components such as JARVIS-FF 47 , 48 , JARVIS-DFT 48 – 57 , JARVIS-ML 49 , 51 , 57 – 59 , JARVIS-STM 51 , JARVIS-Heterostructure 53 and hosts material-properties such as lattice parameters 50 , formation energies 60 , 2D exfoliation energies 55 , bandgaps, elastic constants 50 , dielectric constants 59 , infrared intensities 59 , piezoelectric constants 59 , thermoelectric properties 57 , optoelectronic properties, solar-cell efficiencies 47 , 49 , topological materials 17 , 21 , electric field gradient 61 , and computational STM images 51 . The JARVIS-DFT database consists of ≈ 40000 3D and ≈1000 2D materials.…”

Entanglement between a muon spin and $I>\frac{1}{2}$ nuclear spins

“…Note that site assignments come with some small uncertainty, and previous investigations that can be compared with experiment [17,18,[34][35][36] reveal that a discrepancy of the order of a tenth of Angstrom is to be expected. On the other hand, plane wave based estimations of EFGs are subject to a much larger uncertainty of the order of 30% and 1.17 × 10 21 V/m 2 in relative and absolute terms [37].…”