Open Access

Development of Sustainable Okra Fiber-Nano-SiO₂-reinforced Epoxy Composites: Mechanical Characterization and Machine Learning-based Prediction

N. A. Prashanth, prashanthna@bmsit.in
Department of Electrical and Electronics Engineering, BMS Institute of Technology and Management, Avalahalli, Bengaluru, KA, India
Keerthi Kumar N kannan.maya1986@gmail.com
Department of Electrical and Electronics Engineering, BMS Institute of Technology and Management, Avalahalli, Bengaluru, KA, India



J. Environ. Nanotechnol., Volume 14, No 2 (June 2025) pp. 146-161

https://doi.org/10.13074/jent.2025.06.2511437

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Abstract

The transformation to environmentally friendly components in composite production is essential to minimize the environmental impact and expenditures. Substituting natural fibers, especially those from plants like okra, for conventional reinforcing elements in polymer composites makes them eco-friendlier and more cost-effective. This study aims to characterize and produce polymer composites reinforced with nano-SiO2 filler and chemically-treated okra fibers. Okra fibers, derived from the okra plant, stand out due to their accessibility, mechanical qualities, and positive impact on the environment. Physical and mechanical properties of composites, such as water absorption, tensile strength, and flexural strength, are studied concerning weight percentage, length, thickness, and nano-SiO2 content. Composites with fibers of 12 mm length, 2 mm thickness, and 8 wt.% nano-SiO2 arrangement have shown excellent performance. These composites have a flexural strength of 55.65 MPa and an ultimate tensile strength of 35.92 MPa, which enhances the structural integrity and longevity of the composites. Increasing the fiber weight percentage results in higher water absorption rates, reaching a peak of 3.26%, which highlights the significant impact of fiber dimensions. In addition, when comparing the performance of Response Surface Methodology (RSM) and Feed-Forward Artificial Neural Network (FFANN), predictive modeling using RSM yielded an average accuracy of 85–90%, whereas FFANN achieved 95–98%. Finally, the experimental results were validated through microstructural studies, which underscored the potential of okra fibers to enhance the performance of natural fiber-reinforced composites in various industrial applications.

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