Origin of cloudiness in PET bottles modified with chain extenders for mechanical recycling
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Toshihiko Kanda
Abstract
Melt viscosity improvers (MVs) are known as chain extenders that increase the intrinsic viscosity of recycled polyethylene terephthalate (PET) by forming covalent bonds with PET molecules. Experimental results showed that MVs accelerate epitaxial crystallization in a direction perpendicular to the orientation of MV agglomerates. Acting as nucleating agents, MVs promote crystallization under tension and the formation of light-scattering structures, resulting in cloudiness. Transmission electron microscopy confirmed the presence of MV agglomerates within PET bottles. Wide-angle X-ray diffraction further revealed that MVs altered the crystal orientation of PET by 90° compared to neat PET. Small-angle X-ray scattering during tensile tests indicated that MV-induced crystals within PET bottles were highly oriented perpendicular to the MV orientation direction, potentially contributing to enhanced mechanical drawability and toughness.
Acknowledgments
We would like to thank Frontier, Inc. (Nagano, Japan) for injection molding and blowing the various formulations of the PET bottles under different conditions, and Kaneka Techno Research Corporation (Osaka, Japan) for obtaining the WAXS patterns and TEM images of the PET bottles. We would like to thank Mr. Kimihide Nishimura and Mr. Tetsunori Mori of Kaneka Corporation (Osaka, Japan) for synthesizing MV polymers and production of PET compounds for injection blow molding. We thank Prof. Masayuki Yamaguchi of JAIST (Ishikawa, Japan) for supportive discussion to elucidate the mechanism of cloudiness effect. We also thank Dr. Noboru Ohta for the X-ray measurements at the beam line of BL40B2 in SPring-8 (Hyogo, Japan).
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Research ethics: Not applicable.
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Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: All other authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/ipp-2025-0043).
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