Conical intersections in solution: formulation, algorithm, and implementation with combined quantum...

Area of Science:

• Computational Chemistry
• Theoretical Chemistry
• Molecular Modeling

Background:

• Conical intersections are crucial in molecular photophysics and photochemistry.
• Optimizing conical intersections for gas-phase molecules is routine.
• Current methods for solution/macromolecular systems are inefficient and computationally expensive.

Purpose of the Study:

• To develop efficient methods for optimizing conical intersections in solution or macromolecules.
• To address the challenges posed by high dimensionality and costly calculations in condensed phases.

Main Methods:

• Sequential quantum mechanics/molecular mechanics (QM/MM) approaches.
• QM/MM-minimum free energy path methods.
• Two specific methods: sequential QM optimization with MM minimization (potential energy surfaces) and sequential QM optimization with MM sampling (free energy surfaces).

Main Results:

• Reduced dimensionality of gradient difference and nonadiabatic coupling vectors by confining electronic changes to the QM subsystem.
• Significant decrease in the number of costly gradient difference and nonadiabatic coupling vector evaluations compared to concurrent schemes.
• Successful test optimizations of conical intersections for cyclopropanone and acetaldehyde in aqueous solution.

Conclusions:

• The developed sequential QM/MM methods offer a computationally efficient way to optimize conical intersections for molecules in solution and macromolecules.
• These methods overcome the limitations of existing approaches for condensed-phase systems.
• The findings pave the way for more accurate theoretical studies of photochemical processes in complex environments.