A multiscale scheme for simulating polymer Tg.

Area of Science:

• Polymer Science
• Computational Chemistry
• Materials Science

Background:

• All-atomistic molecular dynamics (MD) is valuable for polymer glass transition temperature (Tg) studies but computationally intensive and lacks consistent accuracy.
• Simulated Tg values often deviate from experimental data, necessitating improved computational methods.

Purpose of the Study:

• To develop and validate a multiscale modeling scheme for accurate prediction of polymer Tg.
• To establish a reliable computational framework for investigating factors influencing polymer Tg.

Main Methods:

• A multiscale scheme was developed, parameterizing coarse-grained (CG) potentials using all-atomistic (AA) simulations of oligomeric melts.
• MD simulations were performed using CG potentials on oligomer bulks and polymer systems to determine dynamical Tg.
• A linear relationship between simulated dynamical Tg of oligomeric bulks and empirical Tg was established to predict the actual Tg of polymer bulks.

Main Results:

• The multiscale approach successfully predicted dynamical Tg values for poly(ethylene oxide) and poly(methyl methacrylate).
• A linear correlation was observed between simulated dynamical Tg of oligomeric bulks and experimental Tg values.
• The rescaled Tg values from the multiscale model showed excellent agreement with experimental data.

Conclusions:

• The proposed multiscale modeling framework offers a computationally efficient and accurate method for predicting polymer Tg.
• This approach provides a promising tool for exploring the impact of various factors on polymer Tg.
• The rescaled dynamical Tg from simulations reliably predicts the actual polymer Tg.