Effective Cross-Link Density as a Metric for Structure-Property Relationships in Complex Polymer Networks: Insights...

Area of Science:

• Polymer Science
• Materials Science
• Computational Chemistry

Background:

• Traditional metrics like cross-link density (XLD) struggle to capture polymer network complexities.
• Structural factors like functional groups, connection sites, and defects hinder accurate microstructural description.

Purpose of the Study:

• To develop a more accurate metric for describing polymer network microstructure.
• To establish correlations between polymer microstructure and thermomechanical properties.
• To introduce effective cross-link density (XLD extsuperscript{eff}) as a predictive tool.

Main Methods:

• Multiscale molecular dynamics simulations were employed.
• Complex polymer network structures, including acrylic-melamine systems, were constructed.
• A modified XLD metric, XLD extsuperscript{eff}, was developed by considering the elastic contribution of each cross-link.

Main Results:

• Strong linear correlations were found between XLD extsuperscript{eff} and elastic modulus.
• Strong linear correlations were observed between XLD extsuperscript{eff} and glass transition temperature (T extsubscript{g}).
• Conventional XLD failed to establish these robust correlations.

Conclusions:

• XLD extsuperscript{eff} is a robust and predictive metric for thermomechanical properties.
• This metric is effective across various cross-linking conversions and prepolymer systems.
• XLD extsuperscript{eff} facilitates in silico design and optimization of thermoset polymers.