Startseite Mechanical and thermal characterization of cuscuta stem fiber-reinforced biodegradable polymer composites
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Mechanical and thermal characterization of cuscuta stem fiber-reinforced biodegradable polymer composites

  • Sakthi Vadivel Kulandaisamy , Selvakumar Mani ORCID logo EMAIL logo , Govindasamy Ponnusamy und Dinesh Kumar Jeganathan
Veröffentlicht/Copyright: 27. Oktober 2025
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Abstract

Thoroughly investigating the potential applications of Cuscuta stem (CS) fibers in natural composites is essential for advancing the production of eco-friendly, lightweight biomass materials and functional products. Natural plant fibers are being investigated as potential replacements for artificial fibers in composite materials. In this work, Cuscuta stem fiber was tested to determine its physicochemical parameters, thermal behaviour, and other associated aspects. Examining the chemical composition of CS fiber revealed a high proportion of cellulose (66.8 %), lignin (9.25 %), and hemicellulose (12.8 %), with minor quantities of wax (0.26 %) and ash (4.11 %). Furthermore, the X-ray diffraction analysis indicates a crystallinity index of 82.7 % and a crystalline size of 7.29 nm in CS the fiber. The thermal characteristics of CS fiber were assessed using thermogravimetric analysis and differential scanning calorimetry. The outcomes confirmed thermal permanency up to 220 °C and deterioration at 350 °C, indicating potential for polymer composite production. Scanning electron microscopy revealed that the average diameter of the CS fiber was 460 µm.


Corresponding author: Selvakumar Mani, Department of Mechanical Engineering, Adithya Institute of Technology, Coimbatore, India, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. K. Sakthi vadivel - Conceptualization & Writing M. Selvakumar - supervision P. Govindasamy - Validation J. Dinesh Kumar - Methodology.

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

  5. Conflict of interest: All other authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2025-02-06
Accepted: 2025-04-25
Published Online: 2025-10-27

© 2025 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 25.10.2025 von https://www.degruyterbrill.com/document/doi/10.1515/ijmr-2025-0038/pdf
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