Singlet-triplet energy gaps for diradicals from particle-particle random phase approximation

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry

Background:

• Diradicals are challenging chemical systems due to their unique electronic structures.
• Accurate calculation of excitation energies, particularly singlet-triplet gaps, is crucial for understanding diradical behavior.
• Existing methods often struggle with static correlation and asymptotic behavior in diradical systems.

Purpose of the Study:

• To evaluate the performance of the particle-particle random phase approximation (pp-RPA) method for calculating excitation energies in various diradical systems.
• To compare pp-RPA with other established computational methods like DFT, SF-CIS, and NC-SF-TDDFT.
• To assess the suitability of pp-RPA for handling challenging diradical cases, including disjoint diradicals.

Main Methods:

• Application of the particle-particle random phase approximation (pp-RPA) method.
• Treating nonbonding electrons in a subspace configuration interaction manner within pp-RPA.
• Utilizing density functional theory (DFT) for the remaining electronic system.
• Calculating vertical and adiabatic singlet-triplet energy gaps for diverse diradical categories.

Main Results:

• pp-RPA generally predicts singlet-triplet gaps well, with exceptions for some four-π-electron diradicals.
• The method exhibits favorable O(r(4)) scaling, outperforming spin-flip configuration interaction singles.
• pp-RPA shows comparable or superior performance to fractional-spin methods and excels for disjoint diradicals and benzynes.
• It accurately describes challenging ground state and charge transfer excitations in disjoint diradicals where other DFT methods fail.

Conclusions:

• The pp-RPA method is a promising theoretical tool for calculating excitation energies in diradical systems.
• Its ability to handle static correlation and provide correct asymptotic behavior makes it particularly suitable for disjoint diradicals.
• pp-RPA offers a computationally efficient and accurate alternative for studying a wide range of diradical problems.