Force-resolved and recurrence-based identification of dynamical heterogeneity in liquid water

Area of Science:

• Physical Chemistry
• Computational Chemistry
• Materials Science

Background:

• Macroscopic properties of liquid water are governed by microscopic molecular fluctuations.
• Identifying dynamically active molecular environments is crucial for understanding water's behavior.
• Conventional structural descriptors often fail to capture transient and persistent molecular dynamics.

Purpose of the Study:

• To introduce a novel framework for identifying dynamically active molecular environments in liquid water.
• To distinguish between transient extreme fluctuations and persistent molecular activity.
• To link microscopic molecular dynamics to macroscopic properties like transport and reactivity.

Main Methods:

• Development of a force-resolved, recurrence-based framework.
• Utilizing a charge-aware neuroevolution potential (q-NEP) for molecular simulations.
• Combining force-derived instability metrics with recurrence statistics to analyze molecular behavior.

Main Results:

• Identified a small fraction (approx. 5-10%) of molecules repeatedly participating in high-instability events.
• Revealed spatially localized 'hotspots' of persistent molecular activity driving hydrogen-bond rearrangement.
• Demonstrated that recurrence-weighted force fluctuations are a more sensitive measure of molecular activity than conventional descriptors.

Conclusions:

• A clear separation exists between extreme and persistent molecular dynamics in water.
• The developed framework accurately identifies molecular environments governing water's transport and reactivity.
• This approach provides a generalizable method for connecting microscopic dynamics to macroscopic behavior in aqueous systems.