Abstract

The transition to sustainable materials in composite manufacturing is crucial for reducing environmental impact and costs. Natural fibers, particularly from plants like Hibiscus Rosa-Sinensis, offer an eco-friendly and cost-effective alternative to traditional reinforcement materials in polymer composites. This study explores the development and characterization of polymer composites reinforced with chemically treated Hibiscus Rosa-Sinensis (HRS) fibers. HRS fibers, derived from the plant Hibiscus Rosa-Sinensis, are notable for their availability, mechanical properties, and environmental benefits. The research investigates how fiber weight percentage, fiber length, and fiber thickness affect the physical and mechanical properties of the composites, including void content, microhardness, water absorption, tensile strength, flexural strength, and Impact Strength. Composites with a fiber configuration of 15 Wt%, 10 mm length, and 2 mm thickness have exhibited optimal performance, achieving an ultimate tensile strength of 30.76 MPa, flexural strength of 50.8 MPa, Impact Strength of 119 J m−1, and a peak microhardness of 22.326 Hv. These parameters significantly enhance the composite’s structural integrity and durability. The study also highlights the critical role of fiber dimensions i.e. with greater fiber weight percentages leading to increased void content and water absorption rates, which peaked at 6.19% and 3.45%, respectively. Further, predictive modelling using Feed-Forward Artificial Neural Network (FFANN) and Response Surface Methodology (RSM) revealed that FFANN has outperformed RSM, achieving an average accuracy of 95%–98% compared to the average accuracy of RSM at 85%–90%. Finally, microstructural analysis has corroborated with the experimental results, highlighting the potential of Hibiscus Rosa-Sinensis fibers in enhancing the performance of natural fiber-reinforced composites for various industrial applications.

Details

Title
Mechanical and physical characterization of chemically treated Hibiscus Rosa-Sinensis polymer matrix composites using deep learning and statistical approach
Author
Supriya, J P; Shetty, Raviraj  VIAFID ORCID Logo  ; Shetty, Sawan  VIAFID ORCID Logo  ; Bolar, Gururaj  VIAFID ORCID Logo  ; Hegde, Adithya
First page
115304
Publication year
2024
Publication date
Nov 2024
Publisher
IOP Publishing
e-ISSN
20531591
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3130799306
Copyright
© 2024 The Author(s). Published by IOP Publishing Ltd. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.