Extending the Applicability of the Multiple-Spawning Framework for Nonadiabatic Molecular Dynamics.

Area of Science:

• Computational chemistry
• Theoretical chemistry
• Molecular dynamics

Background:

• Ab initio multiple-spawning (AIMS) models molecular nonadiabatic dynamics using trajectory basis functions (TBFs).
• AIMS accuracy stems from adaptive TBF basis size, but uncontrolled growth hinders computational efficiency.

Purpose of the Study:

• To evaluate the performance of AIMS with informed stochastic selections (AIMSWISS).
• To demonstrate AIMSWISS's robustness in simulating challenging nonadiabatic processes.

Main Methods:

• AIMS with informed stochastic selections (AIMSWISS) was employed.
• Simulations covered photodynamics of 2D model systems, 1,2-dithiane, and chromium (0) hexacarbonyl.

Main Results:

• AIMSWISS significantly reduces the number of TBFs compared to standard AIMS.
• The method proved robust across diverse nonadiabatic processes.

Conclusions:

• AIMSWISS offers a computationally efficient alternative for simulating nonadiabatic molecular dynamics.
• This approach expands the applicability of multiple-spawning methods to a wider range of molecular systems.