Fiscal Year:
2007
Title:
Efficient Implementation of A New and Accurate DFT Method
Agency:
HHS
Contract:
1R43GM081928-01
Award Amount:
$104,313.00
Abstract:
DESCRIPTION (provided by applicant): Density functional theory (DFT) is perhaps the most widely applied quantum chemistry method in molecular simulations due to its ability to accurately and efficiently model a wide range of molecular systems. Still, it ha
s some deficiencies in two major aspects of biological modeling: the barriers of chemical reactions (including charge transfer and hydrogen bonding) and the dispersion interaction prominent in hydrophobicinteractions. Recently, Axel Becke, one of the pione
ers of DFT, and his co-workers, have proposed two conceptually novel functional models to overcome the deficiencies and their results have shown a great deal of potential. The model for the reaction barrier, namely real-space correlation (RSC), imposes a s
erious challenge to the current DFT numerical algorithms. The solution to the challenge is also a prerequisite to the efficient exploitation of the dispersion model. The RSC model requires the evaluation of Hartree-Fock (HF) exchange energy density at each
grid point, which incurs prohibitively high computational cost. Further more, it contains a non-smooth correlation factor and an iterative solution to an auxiliary functional, preventing a self-consistent-field (SCF) solution. For this Phase I project, we
propose to apply the resolution-of-identity technique to reduce the cost of the calculation of the HF-exchange energy density in the RSC model. We will show that the computational cost of the new algorithm will be reduced to the same level as the conventi
onal DFT algorithms. We will also develop an analytical interpolation to the auxiliary functional and smoothen the correlation factor. All those developments will lead to a SCF solution of the RSC model, which is needed in just about every application of D
FT. The new development will afford the general application of the new and accurate DFT method and enable its further development.
Business Contact:
Jing Kong
Small Business Information at Submission:
Q-CHEM, INC.
Q-CHEM, INC. 5001 BAUM BLVD, STE 690 PITTSBURGH, PA 15213
EIN/Tax ID:
251771588
DUNS:
N/A
Number of Employees:
N/A
Woman-Owned:
No
Minority-Owned:
No
HUBZone-Owned:
No