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Sustainable development and ANN-based prediction of bio-waste-filled flax–pineapple–epoxy hybrid composites for enhanced mechanical performance

  • Sandeepkumar Gowda
  • , Maruthi Prashanth B. H
  • , Ramesh S
  • , Divijesh Puninchathaya P
  • , Nidhin Raj A
  • , Asif Iqbal Mulla
  • , B. Kiran Kumar
  • , Priyaranjan Sharma*
  • , Gajanan Anne*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

With the increasing demand for sustainable and cost-effective materials, natural fiber-reinforced composites are gaining traction among manufacturers and consumers. This study addresses the growing need for eco-friendly and structurally reliable composite materials. It focuses on the incorporation of bio-waste fillers into epoxy composites reinforced with flax and pineapple fibers, assessing their suitability for lightweight structural applications in automotive and construction sectors. Four fillers—coconut shell powder (CSP), teak wood dust (TWD), eggshell powder (ESP), and rice husk powder (RHP)—were added at a fixed 10 wt% to fabricate hybrid composites using a combination of hand layup and hot-pressing techniques. Mechanical properties such as tensile strength, impact resistance, interlaminar shear strength (ILSS), fracture toughness, and flexural strength were evaluated. Among all, CSP-reinforced composites showed superior mechanical performance, with enhancements ranging from 1.95% to 42.8% over other variants. Scanning Electron Microscopy (SEM) analysis revealed improved fiber–matrix bonding and minimal voids in CSP composites. In addition, an Artificial Neural Network (ANN) model was employed to predict mechanical properties with high accuracy: 95.85% (tensile), 83.9% (flexural), and 89.83% (impact). These results underscore the potential of using agricultural and industrial waste fillers in natural fiber composites for sustainable, high-performance applications in structural engineering.

Original languageEnglish
Article number16826
JournalScientific Reports
Volume16
Issue number1
DOIs
Publication statusPublished - 12-2026

All Science Journal Classification (ASJC) codes

  • General

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