Back to Search
Start Over
Dependence of predicted bulk properties of hexagonal hydroxyapatite on exchange–correlation functional.
- Source :
-
Computational Materials Science . May2023, Vol. 224, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- [Display omitted] Hydroxyapatite (HA) is the main component of human bones and teeth. HA has also been widely applied in various technological fields due to its unique properties. Reliable computational simulations for this critical material often require input parameters obtained from the first-principles density functional theory (DFT) calculations with appropriate exchange–correlation functionals. Previous DFT calculations are insufficient to verify the reliabilities of various functionals, particularly as they fail to assess predictions for multiple properties of the material. In this paper, we first select 18 different functionals to calculate geometric, elastic, electronic, and thermodynamic properties of hexagonal HA bulk crystal. We find that the results from optB86b-vdW and optB88-vdW functionals with dispersion corrections have the overall best agreement with available experimental data. Then, we choose optB88-vdW functional, as well as PBE functional without dispersion corrections as a comparison, to perform extensive first-principles DFT phonon calculations under the quasiharmonic approximation. Various thermodynamic properties (including phonon contributions to internal energy, entropy, and Helmholtz free energy) and thermal parameters (including thermal expansions of volume, thermal expansion coefficients, heat capacities, isothermal bulk moduli, etc.) versus temperature are consequently obtained. By comparing these quantities, we find that the results from optB88-vdW functional have significantly better agreement with available experimental data than those from PBE functional although the latter has been widely used in previous DFT calculations for HA-based material systems. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09270256
- Volume :
- 224
- Database :
- Academic Search Index
- Journal :
- Computational Materials Science
- Publication Type :
- Academic Journal
- Accession number :
- 163225727
- Full Text :
- https://doi.org/10.1016/j.commatsci.2023.112153