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Predictive Models for the Tensile Strength of Polymer Composites Comprising Spherical Nano-Starch Using Interphase Properties Publisher



Montazeri M1 ; Mohammadi M1 ; Zare Y2 ; Rhee KY3
Authors
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Authors Affiliations
  1. 1. Department of Polymer Engineering, Faculty of Engineering, Qom University of Technology, P.O. Box: 37195-1519, Qom, Iran
  2. 2. Biomaterials and Tissue Engineering Research Group, Department of Interdisciplinary Technologies, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran
  3. 3. Department of Mechanical Engineering (BK21 four), College of Engineering, Kyung Hee University, Yongin, South Korea

Source: Industrial Crops and Products Published:2025


Abstract

This study presents two novel predictive equations based on the Pukanszky and Leidner–Woodhams models, tailored to forecast the tensile strength of polymer composites containing spherical nano-starch. The developed models integrate factors such as the starch volume fraction (ϕf), interphase strength (σi), interphase Thickness (ti), and starch radius (r) to provide a comprehensive understanding of nanocomposite strength. Accurate evaluation against experimental data highlights the models’ efficacy in precisely predicting the tensile strength for various starch-based nanocomposites. Neglecting these properties lead to erroneous predictions, emphasizing the importance of the developed models for optimizing nanocomposite performances. The proposed models assume the filler volume fraction powers as 1/3 and 2/3. The findings indicate that when the filler volume fraction power is set to 1/3, the developed models exhibit the most accurate fit to the experimental data. Additionally, the impacts of several variables, such as the interfacial parameter (B), σi, ti, and ϕf, on the strength of the nanocomposites are graphed using the developed models. In the Pukanszky model, ϕf only achieves high strength when the starch radius is low, indicating the significant roles of ϕf and r data. The developed models reveal that B, ti, and σi have direct relations with the strength of the nanocomposites, whereas r plays an inverse role. © 2025
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