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Chlorine-driven phase dispersion, crystal growth, and morphological variation in thin films of biodegradable poly (ε-caprolactone) and chlorinated polyethylene binary blends

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Published/Copyright: September 19, 2025
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Abstract

Polycaprolactone (PCL) and chlorinated polyethylene (CPE) binary blends were investigated to understand the effects of chlorine content and blend composition on crystal growth, morphology, and phase behavior in thin films. The crystal growth rate of PCL decreased with increasing CPE content, with higher chlorine content in CPE leading to more significant reductions due to disruption of PCL chain mobility and increased phase segregation. Morphological changes were observed as CPE content increased, transitioning from truncated lozenge shapes in neat PCL to S- or C-shaped crystals in the blends. The bending angle of these crystals increased with distance from the center and higher CPE concentrations, attributed to chain tilting caused by compressive or dilation stresses during rapid crystallization. Significant morphological differences were found between bulk, thin, and ultrathin films of the PCL/CPE blends. Bulk samples exhibited pronounced spherulitic structures, while thin films showed more irregular, constrained crystallization patterns, and ultrathin films displayed smooth, continuous morphologies. The chlorine content in CPE influenced the blend morphology, with higher chlorine content promoting more organized crystalline structures. These findings contribute to understanding how blend composition, film thickness, and processing conditions affect the morphology and crystallization behavior of PCL/CPE blends.


Corresponding author: Al Mamun, Department of Physics, College of Science, University of Hafr Al Batin, Al Jamiah, Hafr Al Batin, 39524, Saudi Arabia, E-mail:

Acknowledgments

The authors thank the Deanship of Scientific Research, University of Hafr Al Batin, for the experimental facilities.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/polyeng-2025-0009).


Received: 2025-01-13
Accepted: 2025-08-31
Published Online: 2025-09-19
Published in Print: 2025-11-25

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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