Mechanical and physical characterization of chemically treated Hibiscus Rosa-Sinensis polymer matrix composites using deep learning and statistical approach

复合材料 表征(材料科学) 材料科学 基质(化学分析) 聚合物 纳米技术
作者
J P Supriya,Raviraj Shetty,Sawan Shetty,Gururaj Bolar,Adithya Hegde
出处
期刊:Materials research express [IOP Publishing]
卷期号:11 (11): 115304-115304 被引量:3
标识
DOI:10.1088/2053-1591/ad8ffe
摘要

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.

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