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Modeling of phase separation mechanism in polycaprolactone/dioxane binary systems.

Domenico Larobina¹, Vincenzo Guarino, Luigi Ambrosio

¹Institute of Composite and Biomedical Materials, National Research Council of Italy, Naples, Italy. larobina@unina.it

Journal of Applied Biomaterials & Functional Materials

|December 18, 2012

Summary

This study investigates polycaprolactone microcellular material production using freeze-drying. Process parameters like polymer concentration and temperature influence pore structure, with a model accurately predicting morphology variations.

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Fabricating Superhydrophobic Polymeric Materials for Biomedical Applications

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Area of Science:

Materials Science
Biomedical Engineering
Polymer Science

Background:

Unidirectional freezing followed by freeze-drying creates microcellular materials from polymer solutions for biomedical applications.
This technique results in characteristic channel bundles with diameters in the hundreds of microns.
Variations in porosity, density, and pore organization are observed with changes in polymer concentration and quenching temperature.

Purpose of the Study:

To investigate the thermally induced phase separation of polycaprolactone/dioxane solutions.
To understand how polymer concentration and quenching temperature affect the morphology of microcellular materials.
To correlate process parameters with the resulting porous structure.

Main Methods:

Preparation of polycaprolactone microcellular samples using a freeze/freeze-drying technique.
Microstructural analysis via scanning electron microscopy.
Development of a mathematical model to predict temperature profiles and material morphology.

Main Results:

Observed microstructural disorder regions within samples, linked to specific process parameters.
The developed model successfully predicted the formation of these disorder regions.
Model predictions regarding freezing rate and concentration effects showed excellent agreement with experimental findings.

Conclusions:

The study successfully correlated process parameters with microcellular material morphology.
The mathematical model provides a valuable tool for predicting and controlling microcellular material structure.
Understanding these relationships is crucial for optimizing microcellular materials in biomedical applications.