Mesoscopic Modeling of Bio-Compatible PLGA Polymers with Coarse-Grained Molecular Dynamics Simulations.

Area of Science:

• Materials Engineering
• Computational Materials Science
• Polymer Science

Background:

• Developing accurate numerical models for predicting material properties at the atomistic level is crucial for materials engineering.
• Coarse-grained (CG) molecular dynamics (MD) simulations offer a pathway to bridge the gap between atomistic detail and experimental scales.
• Existing CG models for polymers, particularly for biocompatible materials like poly(lactic-co-glycolic acid) (PLGA), often lack quasi-atomistic accuracy for reliable material design.

Purpose of the Study:

• To develop and validate a generalizable coarse-grained (CG) molecular dynamics (MD) model for polymers.
• To achieve quasi-atomistic accuracy in predicting the physical properties of poly(lactic-co-glycolic acid) (PLGA).
• To enable larger-scale MD simulations for materials design and prototyping.

Main Methods:

• A novel CG model representing polymers as finite-size ellipsoids was developed.
• Short-range interactions were modeled using the generalized Gay-Berne potential.
• Electrostatic and long-range interactions were incorporated using point charges within ellipsoids.

Main Results:

• The CG model for PLGA demonstrated quantitative agreement with its atomistic counterpart.
• Key physical properties, including glass transition temperature, thermal conductivity, and elastic moduli, were accurately reproduced.
• The model successfully bridges the scale gap between atomistic simulations and experimental setups.

Conclusions:

• The proposed CG model offers a reliable method for simulating polymers with high accuracy.
• This approach facilitates the expansion of simulation domain sizes, making them comparable to experimental scales.
• The general parametrization strategy holds potential for broader applications in materials design and prototyping.