ArticleACS omega2024
Plain-Woven Areca Sheath Fiber-Reinforced Epoxy Composites: The Influence of the Fiber Fraction on Physical and Mechanical Features and Responses of the Tribo System and Machine Learning Modeling.
Article in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 22 citations in OpenAlex.
- Experimental Investigation on Thermo-Mechanical, Visco-Elastic, and Acoustic Properties ofPolymers · 2026Article
- Experimental investigation and optimization of mechanical and tribological performances of bio-based sustainable hybrid composites incorporating Nano-SiO₂ fillers.Scientific reports · 2026Article
- An investigation into the physico-chemical characteristics and performance of surface-treated areca fibers.Scientific reports · 2026Article
- Extraction of carbon powder from pyrolysis of low-density polyethylene plastics and its application in composite laminates.MethodsX · 2025Article
- Optimization of tribo-mechanical properties of kenaf/jute-SiC hybrid composites using integrated grey-fuzzy approach.Scientific reports · 2025Article
- Mechanical Evaluation of Epoxy Polymer Composites Reinforced with Areca Leaf Sheath Fiber.ACS omega · 2025Article
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Authors and funding
9 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent studies focus on enhancing the mechanical features of natural fiber composites to replace synthetic fibers that are highly useful in the building, automotive, and packing industries. The novelty of the work is that the woven areca sheath fiber (ASF) with different fiber fraction epoxy composites has been fabricated and tested for its tribological responses on three-body abrasion wear testing machines along with its mechanical features. The impact of the fiber fraction on various features is examined. The study also revolves around the development and validation of a machine learning predictive model using the random forest (RF) algorithm, aimed at forecasting two critical performance parameters: the specific wear rate (SWR) and the coefficient of friction (COF). The void fraction is observed to vary between 0.261 and 3.8% as the fiber fraction is incremented. The hardness of the mat rises progressively from 40.23 to 84.26 HRB. A fair ascent in the tensile strength and its modulus is also observed. Even though a short descent in flexural strength and its modulus is seen for 0 to 12 wt % composite specimens, they incrementally raised to the finest values of 52.84 and 2860 MPa, respectively, pertinent to the 48 wt % fiber-loaded specimen. A progressive rise in the ILSS and impact strength is perceptible. The wear behavior of the specimens is reported. The worn surface morphology is studied to understand the interface of the ASF with the epoxy matrix. The RF model exhibited outstanding predictive prowess, as evidenced by high
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Registered trials
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