Optimizing conical intersections of solvated molecules: the combined spin-flip density functional theory/effective...

Area of Science:

• Computational Chemistry
• Theoretical Chemistry
• Physical Chemistry

Background:

• Potential energy surface crossings are crucial for nonadiabatic processes in chemistry.
• Understanding solvent effects on these crossings is essential for accurate molecular simulations.
• Previous methods often struggle to efficiently model these complex interactions in solution.

Purpose of the Study:

• To investigate the impact of solvent environments on potential energy surface crossings.
• To develop and apply a novel computational method for studying conical intersections in solution.
• To analyze the geometric and energetic changes of conical intersections due to solvent interactions.

Main Methods:

• Derivation and implementation of an analytic energy gradient for collinear spin-flip density functional theory (SFDFT).
• Integration of SFDFT with the effective fragment potential (EFP) solvent model for aqueous solutions.
• Application to model systems: azomethane-water cluster and green fluorescent protein chromophore.

Main Results:

• The SFDFT/EFP method successfully optimized conical intersections in aqueous solution.
• Significant alterations in conical intersection geometries were observed due to solvent effects.
• Polar solvents were found to strongly stabilize the conical intersections.
• Results from the hybrid SFDFT/EFP scheme closely matched those from full SFDFT calculations.

Conclusions:

• The developed SFDFT/EFP method is an efficient and promising approach for studying nonadiabatic processes in solution.
• Solvent polarization plays a critical role in modifying the energetics and geometries of conical intersections.
• This methodology provides valuable insights into the behavior of molecules undergoing electronic transitions in condensed phases.