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Simple Models for Tensile Modulus of Shape Memory Polymer Nanocomposites at Ambient Temperature Publisher



Molaabasi F1 ; Zare Y1 ; Rhee KY2
Authors
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Authors Affiliations
  1. 1. Department of Interdisciplinary Technologies, Breast Cancer Research Center, Biomaterials and Tissue Engineering Research Group, Motamed Cancer Institute, ACECR, Tehran, Iran
  2. 2. Department of Mechanical Engineering (BK21 Four), College of Engineering, Kyung Hee University, Yongin, South Korea

Source: Nanotechnology Reviews Published:2022


Abstract

This article analyzes the tensile modulus of shape memory polymer nanocomposites (SMPNs) at ambient temperature. Several conventional models, such as rule of mixtures, Halpin-Tsai and Kerner-Nielsen, cannot practically estimate the modulus due to the absence of some main parameters for nanocomposites. Additionally, some parameters in Kerner-Nielsen and Sato-Furukawa models are useless and ineffective, due to the small concentration and high modulus of nanofillers in SMPNs. Therefore, Kerner-Nielsen and Sato-Furukawa models are simplified and modified to deliver the simple models for calculation of modulus in SMPNs. Various nanocomposite samples are provided to prove the validity of the suggested models. The results demonstrate that the predictions of the suggested models have a good match with the experimental results. The models also demonstrate high simplicity and good accuracy for the calculation of modulus in SMPNs at ambient temperature. Generally, the calculated results disclose that the modified Kerner-Nielsen model is preferable for approximation of modulus in SMPNs. © 2022 Fatemeh Molaabasi et al., published by De Gruyter.
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