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Published on: May 27, 2020
Ionization potential optimized double-hybrid density functional approximations
Johannes T Margraf1, Prakash Verma1, Rodney J Bartlett1
1Quantum Theory Project, University of Florida, Gainesville, Florida 32611, USA.
Double-hybrid density functional approximations (DH-DFAs) can be improved by optimizing their potential for accurate orbital energies. A new functional, B2IP-PLYP, demonstrates superior performance, especially for challenging electronic cases.
Area of Science:
- Quantum Chemistry
- Computational Chemistry
- Electronic Structure Theory
Background:
- Double-hybrid density functional approximations (DH-DFAs) combine density functional theory and wavefunction theory for accurate molecular electronic structure.
- The Kohn-Sham (KS) potential is crucial for DH-DFA performance, but its accurate generation remains an area of research.
Purpose of the Study:
- To investigate the properties of the potential used in DH-DFAs.
- To develop a method for generating a consistent KS potential for DH-DFAs, including second-order perturbational contributions.
- To propose a strategy for constructing DH-DFAs that yield accurate orbital energies.
Main Methods:
- Utilized the optimized effective potential (OEP) approach to derive the consistent KS potential for DH-DFAs.
- Reparameterized the B2-PLYP functional to create the IP-optimized B2IP-PLYP functional.
- Validated the new functional using a dataset of vertical ionization potentials (IPs) and atomization energies.
Main Results:
- The OEP-derived potential provides improved orbital energies (as vertical IPs) compared to the standard perturbation-free KS potential.
- The reparameterized B2IP-PLYP functional outperforms the original B2-PLYP across various benchmarks.
- B2IP-PLYP demonstrates performance comparable to B2GP-PLYP and excels in difficult electronic and multireference systems.
Conclusions:
- Optimizing the DH-DFA potential for accurate orbital energies is a viable strategy for improving functional performance.
- The B2IP-PLYP functional represents a significant advancement, offering reliability for complex chemical problems.
- This work provides a pathway for developing more accurate and robust DH-DFAs.
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