Transferable density functional tight binding for carbon, hydrogen, nitrogen, and oxygen: Application to shock compression.
Marc J CawkwellR PerriotPublished in: The Journal of chemical physics (2019)
A new parameterization for density functional tight binding (DFTB) theory, lanl31, has been developed for molecules containing carbon, hydrogen, nitrogen, and oxygen. Optimal values for the Hubbard Us, on-site energies, and the radial dependences of the bond integrals and repulsive potentials were determined by numerical optimization using simulated annealing to a modest database of ab initio-calculated atomization energies and interatomic forces. The transferability of the optimized DFTB parameterization has been assessed using the CHNO subset of the QM-9 database [R. Ramakrishnan et al., Sci. Data 1, 140022 (2014)]. These analyses showed that the errors in the atomization energies and interatomic forces predicted by our model are small and in the vicinity of the differences between density functional theory calculations with different basis sets and exchange-correlation functionals. Good correlations between the molecular dipole moments and HOMO-LUMO gaps predicted by lanl31 and the QM-9 data set are also found. Furthermore, the errors in the atomization energies and forces derived from lanl31 are significantly smaller than those obtained from the ReaxFF-lg reactive force field for organic materials [L. Liu et al., J. Phys. Chem. A 115, 11016 (2011)]. The lanl31 DFTB parameterization for C, H, N, and O has been applied to the molecular dynamics simulation of the principal Hugoniot of liquid nitromethane, liquid benzene, liquid nitrogen, pentaerythritol tetranitrate, trinitrotoluene, and cyclotetramethylene tetranitramine. The computed and measured Hugoniot loci are in excellent agreement with experiment, and we discuss the sensitivity of the loci to the underestimated shock heating that is a characteristic of classical molecular dynamics simulations.
Keyphrases
- molecular dynamics simulations
- density functional theory
- adverse drug
- molecular dynamics
- electronic health record
- molecular docking
- ionic liquid
- blood brain barrier
- genome wide
- big data
- patient safety
- genome wide association study
- single molecule
- spinal cord injury
- genome wide association
- machine learning
- magnetic resonance imaging
- binding protein
- dna methylation
- dna binding
- computed tomography
- artificial intelligence
- water soluble