Automated Search for Minimum Energy Conical Intersection Geometries between the Lowest Two Singlet States S0/S1-MECIs...

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry

Background:

• Minimum energy conical intersections (MECIs) are crucial for understanding photochemical reactions and non-adiabatic processes.
• Previous automated searches for MECIs often relied on computationally expensive multireference methods.
• Efficient methods are needed to locate S0/S1-MECIs (minimum energy conical intersections between the lowest two singlet states) for larger molecular systems.

Purpose of the Study:

• To develop and evaluate an automated computational approach for locating S0/S1-MECIs.
• To combine the seam model function (SMF) and anharmonic downward distortion following (ADDF) methods with spin-flip time-dependent density functional theory (SF-TDDFT).

Main Methods:

• Employed a hybrid approach combining SMF/ADDF with SF-TDDFT for automated MECI searches.
• Utilized SF-TDDFT for efficient optimization of S0/S1-MECIs within the TDDFT framework.
• Tested the method's performance on ethylene and 1,3-butadiene systems.

Main Results:

• The hybrid SMF/ADDF and SF-TDDFT method successfully and automatically identified both previously known and novel S0/S1-MECIs.
• The approach demonstrated efficiency in locating MECIs on potential energy surfaces.
• The method proved capable of handling systems like ethylene and 1,3-butadiene.

Conclusions:

• The developed hybrid method is a promising and efficient approach for the automated localization of S0/S1-MECIs.
• This technique offers a computationally modest solution for exploring MECIs in large and complex molecular systems.
• The study validates the utility of combining SMF/ADDF with SF-TDDFT for advancing automated reaction pathway searches.