Towards a predictive model for polymer solubility using the noncovalent interaction index: polyethylene as a case...

Area of Science:

• Polymer Science
• Computational Chemistry
• Materials Science

Background:

• Assessing polymer solubility is crucial for material design and processing.
• Existing methods like Hansen's solubility parameters and COSMO models have limitations in predicting complex solute-solvent interactions.
• Understanding polymer solvation behavior is key to controlling material properties.

Purpose of the Study:

• To develop a novel, quantitative descriptor for polymer solubility based on the non-covalent interaction (NCI) index.
• To provide a more insightful alternative to Hansen's solubility parameters and the COSMO model.
• To quantitatively assess and predict polymer solubility in different solvents.

Main Methods:

• Molecular dynamics simulations were employed to study polyethylene chain behavior in anisole and methanol.
• Solvation free energy and solvent accessible surface area were used as established descriptors.
• The non-covalent interaction (NCI) index was utilized to analyze solute-solvent and intramolecular interactions.

Main Results:

• Polyethylene exhibited distinct solvation behaviors: maximizing interface in anisole and forming rod-like structures in methanol above a chain length threshold.
• The NCI index provided qualitative and quantitative insights into solute-solvent interactions, solute conformation, and intramolecular interactions.
• Two new NCI-based descriptors, relative integrated NCI density and integrated NCI difference, were proposed for quantifying solubility.

Conclusions:

• The novel NCI-based descriptors offer a versatile and insightful approach to assessing polymer solubility.
• These descriptors enable fast, reliable, and high-throughput screening of solvent-solute combinations.
• The proposed method enhances the understanding of polymer solvation and conformation in different solvent environments.