Computational discovery of chemically patterned surfaces that effect unique hydration water dynamics

Area of Science:

• Surface science
• Physical chemistry
• Computational chemistry

Background:

• Water-surface interactions dictate hydrophobicity/hydrophilicity, influenced by surface chemistry.
• Precise chemical patterning, not just average coverage, significantly impacts hydration water structure, thermodynamics, and interfacial properties.

Purpose of the Study:

• To investigate how surface heterogeneities and chemical group patterning control hydration water dynamics.
• To design surface functional group patterns that minimize or maximize water diffusivity using computational methods.

Main Methods:

• Coupling a genetic algorithm with iterative molecular dynamics simulations.
• Designing surface functional group patterns at fixed coverage to modulate water diffusivity.
• Analyzing hydration water mobility, orientational entropy, and hydrophobe insertion thermodynamics.

Main Results:

• Clustering hydrophilic groups increases hydration water mobility; dispersing them decreases it, contingent on hydrogen-bonding interactions.
• Hydration water orientational entropy and hydrophobe insertion chemical potential predict water diffusivity across various surfaces, coverages, and patterns.
• Subnanometer chemical surface patterning is a key design parameter for controlling water dynamics.

Conclusions:

• Surface patterning offers a powerful strategy for engineering solid-water interfaces.
• Thermodynamic quantities like orientational entropy effectively predict water dynamics at interfaces.
• Findings have broad implications for designing materials for separations, catalysis, and biomolecular applications.