A Unified Hyperdynamics Framework for Rare-Event Simulations Across Complex Energy Landscapes.

Area of Science:

• Computational Chemistry
• Materials Science
• Chemical Physics

Background:

• Collective Variable-driven Hyperdynamics (CVHD) extends molecular simulation timescales.
• CVHD can be inefficient for high-energy barriers, limiting rare event simulation.
• Complex systems often feature widely separated energy barriers.

Purpose of the Study:

• To develop a hybrid method combining On-the-fly Probability-Enhanced Sampling (OPES) with CVHD.
• To efficiently accelerate rare event simulations and extract kinetic rates in complex systems.
• To address challenges posed by widely separated energy barriers.

Main Methods:

• Integration of OPES with CVHD, creating the OPES_CVHD approach.
• Periodic updating of the OPES barrier parameter to manage diverse energy landscapes.
• Combining adaptive biasing for complex systems with static biasing for well-characterized systems.

Main Results:

• Demonstrated the performance and applicability of OPES_CVHD across representative systems.
• Showcased the method's effectiveness in accelerating rare events.
• Validated the extraction of physically meaningful kinetic rates.

Conclusions:

• OPES_CVHD is a powerful and general tool for rare-event simulations.
• The hybrid approach enhances efficiency for complex chemical and materials systems.
• Periodic barrier parameter updates effectively manage complex energy landscapes.