Leucaena-Silicone Biocomposite: Experimentation, Quantification and Prediction of Mechanical Properties for Potential Applications in Medicine and Healthcar

Muhammad Hamizan Hidzer; Nurul Haiza  Sapiee; Wan Mohd Nazri  Wan Abdul Rahman; Chi Hieu  Le; Quang Nguyen  Ho; Jamaluddin Mahmud

doi:10.15282/ijame.22.2.2025.7.0944

Authors

Muhammad Hamizan Hidzer College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
Nurul Haiza Sapiee College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
Wan Mohd Nazri Wan Abdul Rahman Universiti Teknologi MARA Cawangan Pahang, Kampus Jengka, 26400 Bandar Tun Abdul Razak Jengka, Pahang, Malaysia
Chi Hieu Le Faculty of Science and Engineering, University of Greenwich, Kent ME4 4TB, United Kingdom
Quang Nguyen Ho Institute of Engineering and Technology, Thu Dau Mot University, 820000 Binh Duong, Vietnam
Jamaluddin Mahmud College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia

DOI:

https://doi.org/10.15282/ijame.22.2.2025.7.0944

Keywords:

Leucaena, Silicone, Biocomposite, Hyperelastic, Ogden, Artificial neural network

Abstract

Silicone rubber, in general, possesses super soft physical behavior, which is not suitable for structural applications. Therefore, this study aims to introduce an innovative biocomposite material combining Leucaena and Silicone, named LeuSiC, to establish its physical and mechanical properties for possible medical applications. Various Leucaena fiber compositions ranging from 0 wt% to 16 wt% were mixed with pure silicone rubber, where density, compression set, and uniaxial tensile behavior were experimentally investigated following ASTM standards. The Ogden hyperelastic constitutive was employed to quantify the tensile behavior of LeuSiC via material constants, µ and material exponent, α. Additionally, the tensile properties of LeuSiC were also predicted using Artificial Neural Network (ANN). The results revealed that the material constants, µ value, increased with higher Leucaena fiber composition, indicating stiffness increment. In contrast, increasing fiber composition reduced the tensile strength and flexibility of LeuSiC. In terms of prediction using ANN, the results proved the capability of the constructed neural network model, where the error was less than 0.4%. The quantified and predicted properties of µ and α range from 5.4 to 55.9 kPa and 2.16 to 3.0 respectively, suggest that LeuSiC has the potential to mimic and be made into synthetic connective tissues.

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