Temperature-Dependent Implicit-Solvent Model of Polyethylene Glycol in Aqueous Solution.

Area of Science:

• Computational chemistry
• Polymer science
• Physical chemistry

Background:

• Polyethylene glycol/oxide (PEG/PEO) is crucial in various applications.
• Accurate modeling of PEG/PEO in aqueous solutions is essential for predicting material properties.
• Existing models may lack temperature-dependent accuracy across a wide range.

Purpose of the Study:

• To develop a temperature-dependent coarse-grained (CG) Hamiltonian for PEG/PEO in aqueous solution.
• To create a model applicable to implicit-solvent material simulations over a broad temperature range.
• To ensure continuous transferability in temperature space for accurate predictions.

Main Methods:

• A combined "bottom-up" and "top-down" approach was used to derive T-dependent nonbonded CG interactions.
• Atomistic replica-exchange molecular dynamics simulations and iterative Boltzmann inversion were employed.
• Pair potentials were postrefined by benchmarking against experimental radius of gyration data.
• Truncated pair potentials were mapped to an analytic formula with T-dependent structural parameters.

Main Results:

• The developed model successfully reproduces experimentally known thermodynamic properties of semidilute PEG solutions.
• The model accurately predicts the temperature-dependent osmotic pressure (equation of state) for various PEG chain lengths.
• The model correctly predicts the cloud point (or collapse) temperature of PEG solutions.

Conclusions:

• The T-dependent CG Hamiltonian provides a robust and transferable model for PEG/PEO in aqueous solutions.
• This model enhances the predictive capability of implicit-solvent simulations for polymer solutions.
• The study offers a valuable tool for understanding and designing PEG-based materials.