Predicting Polymer Brush Behavior in Solvents Using the Steepest-Entropy-Ascent Quantum Thermodynamic Framework.

Area of Science:

• Physical Chemistry
• Polymer Science
• Thermodynamics

Background:

• Understanding temperature effects on polymer brushes is crucial for materials science.
• Existing models may not fully capture the dynamic evolution of polymer brushes under varying thermal conditions.

Purpose of the Study:

• To investigate the influence of temperature on polymer brushes using the steepest-entropy-ascent quantum thermodynamic (SEAQT) framework.
• To establish a kinetic path for polymer brush evolution from initial states to equilibrium.
• To predict thermodynamic and structural properties of polymer brushes under different nonequilibrium conditions.

Main Methods:

• Utilized the steepest-entropy-ascent quantum thermodynamic (SEAQT) framework.
• Employed the replica-exchange Wang-Landau algorithm to obtain energy degeneracies for polymer brushes with discrete energy spectra.
• Applied the SEAQT equation of motion to the density of states to define kinetic paths and predict properties.

Main Results:

• Predicted polymer density profiles for a polystyrene brush in cyclohexane qualitatively matched experimental data.
• The Flory-Huggins parameter influenced solvent distribution but minimally affected the polymer density profile.
• Calculated various properties (tortuosity, radius of gyration, densities, conformations) for heating, cooling, and heating-cooling nonequilibrium paths.

Conclusions:

• The SEAQT framework provides a viable method for studying temperature effects and nonequilibrium dynamics in polymer brushes.
• The model successfully predicts key thermodynamic and structural properties, validating its applicability.
• Different nonequilibrium paths exhibit distinct impacts on brush properties, highlighting the importance of path selection.