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Updated: May 9, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
Published on: December 4, 2017
On asymptotic behavior of density functional theory
Wojciech Cencek1, Krzysztof Szalewicz
1Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, USA. cencek@udel.edu
Asymptotic corrections significantly improve density functional theory (DFT) predictions for molecular properties. The best corrected methods achieve near-benchmark accuracy, outperforming standard DFT for electron densities.
Area of Science:
- Computational chemistry
- Quantum chemistry
- Theoretical physics
Background:
- Density functional theory (DFT) is a powerful computational tool.
- Accurate electron density behavior is crucial for predicting molecular properties.
- Standard DFT methods often struggle with the asymptotic behavior of electron densities.
Purpose of the Study:
- Evaluate methods for correcting asymptotic electron densities in DFT.
- Compare performance against benchmark values for sensitive molecular properties.
- Investigate the efficacy of range-separated hybrid (RSH) functionals.
Main Methods:
- Assessed novel and existing asymptotic correction approaches for DFT.
- Calculated molecular properties: polarizabilities, Rydberg excitation energies, and interaction energies.
- Employed symmetry-adapted perturbation theory for interaction energy calculations.
Main Results:
- Asymptotically corrected DFT significantly reduces errors (from ~12% to <2%) compared to uncorrected methods.
- Best corrected functionals achieve near-benchmark accuracy, comparable to high-level coupled-cluster methods.
- Range-separated hybrid (RSH) functionals perform well for excitation energies but fail for interaction energies.
Conclusions:
- Asymptotic corrections are vital for accurate DFT predictions of sensitive molecular properties.
- RSH functionals require modification for reliable interaction energy calculations.
- Correcting the asymptotic behavior of electron densities is key to advancing DFT accuracy.
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