Evaluating models for polycaprolactone crystallization via simultaneous rheology and Raman spectroscopy

Area of Science:

• Polymer Science
• Materials Science
• Rheology

Background:

• Polymer melt crystallization significantly alters material properties, impacting industrial product manufacturing.
• Correlating rheology and crystallinity is crucial for process simulation but challenging due to experimental limitations.
• Simultaneous measurements are needed to overcome differences in sample history, geometry, and temperature.

Purpose of the Study:

• To investigate the relationship between structure, crystallinity, and rheology during isothermal polycaprolactone crystallization.
• To apply a novel rheo-Raman microscope for simultaneous, quantitative measurements.
• To develop and validate a model describing the complex modulus as a function of crystallinity.

Main Methods:

• Utilized a rheo-Raman microscope for simultaneous rheology, Raman spectroscopy, and polarized optical measurements.
• Monitored isothermal crystallization of polycaprolactone.
• Quantified crystallinity using Raman spectral features.
• Measured rheological parameters including shear modulus and birefringence.
• Developed a new suspension-based model to correlate rheological data with crystallinity.

Main Results:

• Crystallinity and shear modulus evolved over similar timescales; birefringence increased earlier.
• Existing models failed to describe the crystallinity-modulus relationship throughout the process.
• A novel suspension-based model successfully fitted the complex modulus across the crystallization range.
• The crystallization process exhibited a critical percolation fraction and a single scaling exponent.

Conclusions:

• The developed rheo-Raman technique enables direct correlation of rheological and structural changes during polymer crystallization.
• A new suspension-based model provides accurate description of the modulus-crystallinity relationship.
• Understanding these relationships is key for optimizing polymer processing and predicting final product properties.