Investigation of nano-hBN/ natural fibers reinforced epoxy composites for thermal and electrical applications using GRA and ANFIS optimization methods

Polymer composites reinforced with natural fibers have made great strides in industrial appliance use owing to the fibers exceptional composite properties, low environmental impact, and long lifespan. Five natural fibers-banana, sugar cane, coir, wood, and rice husk—are employed as short fibers in this experiment. The electrical and thermal properties of hybrid filler polymer (HFP) composites are also examined in relation to the thermal conductivity nano hBN filler weight ratio. HFP composites are prepared using the Taguchi design to select nano filler ratios and fifteen tests. Experimental results demonstrate that HFP composites with the maximum h-BN content are the most electrically and thermally robust. HFP composite material has the highest thermal conductivity and electrical resistance of 1.01 W/m-K and 346.91 Giga-Ohms respectively, with 5 % nano hBN and 2 % RH (sample 6). Nano h-BN fillers positively increase the thermal conductivity and electrical resistance of the composite structures. An improvement in thermal conductivity and electrical resistance is evident for the sample 6 composite, which increased by 16.09 % and 154.05 %, respectively, compared to the S1 interlaced multiphase hybrid polymer composite. Sample 4, containing rice husk fiber, achieves the minimal dielectric constant of 0.94, whereas sample 12, containing banana fiber, achieves a dielectric constant of 0.98. ANOVA is used to determine how such variables affect output variables. Performance measures are determined using the adaptive neuro-fuzzy inference system model with a hybrid grey base. Using the adaptive network-based fuzzy inference system, the input-output relation is modeled. After comparing experimental and ANFIS-anticipated data, the latter accurately predicted HFP composite behaviour. The combination of h-BN and natural fiber composites holds significant potential for various electrical and thermal applications due to their exceptional overall properties. • Developed hybrid filler polymer-HFP composites with nano hBN/natural fibers. • The thermal and electrical behaviours of the HFP composites were examined. • The hBN improved the thermal conductivity of the HFP composites. • GRA and ANFIS optimizations analyzed significant parameters of HFP composites. • HFP composites are suggested for electrical and microelectronic applications.

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Publication Details

Journal
Polymer Testing
Published
2024-09-06
DOI
https://doi.org/10.1016/j.polymertesting.2024.108561
Citations
18
Primary Topic
Tribology and Wear Analysis
Type
article
Field-Weighted Citation Impact
4.85
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article

Investigation of nano-hBN/ natural fibers reinforced epoxy composites for thermal and electrical applications using GRA and ANFIS optimization methods

Ramraji Kirubakaran, Aravindh Sampath, G. Venkatachalam, Dinesh Ramesh Salunke et al.
18 citations
Polymer Testing
Tribology and Wear Analysis
4.85
article

Investigation of nano-hBN/ natural fibers reinforced epoxy composites for thermal and electrical applications using GRA and ANFIS optimization methods

Ramraji Kirubakaran, Aravindh Sampath, G. Venkatachalam, Dinesh Ramesh Salunke, Shenbaga Velu Pitchumani
article en
18 citations

Abstract

Polymer composites reinforced with natural fibers have made great strides in industrial appliance use owing to the fibers exceptional composite properties, low environmental impact, and long lifespan. Five natural fibers-banana, sugar cane, coir, wood, and rice husk—are employed as short fibers in this experiment. The electrical and thermal properties of hybrid filler polymer (HFP) composites are also examined in relation to the thermal conductivity nano hBN filler weight ratio. HFP composites are prepared using the Taguchi design to select nano filler ratios and fifteen tests. Experimental results demonstrate that HFP composites with the maximum h-BN content are the most electrically and thermally robust. HFP composite material has the highest thermal conductivity and electrical resistance of 1.01 W/m-K and 346.91 Giga-Ohms respectively, with 5 % nano hBN and 2 % RH (sample 6). Nano h-BN fillers positively increase the thermal conductivity and electrical resistance of the composite structures. An improvement in thermal conductivity and electrical resistance is evident for the sample 6 composite, which increased by 16.09 % and 154.05 %, respectively, compared to the S1 interlaced multiphase hybrid polymer composite. Sample 4, containing rice husk fiber, achieves the minimal dielectric constant of 0.94, whereas sample 12, containing banana fiber, achieves a dielectric constant of 0.98. ANOVA is used to determine how such variables affect output variables. Performance measures are determined using the adaptive neuro-fuzzy inference system model with a hybrid grey base. Using the adaptive network-based fuzzy inference system, the input-output relation is modeled. After comparing experimental and ANFIS-anticipated data, the latter accurately predicted HFP composite behaviour. The combination of h-BN and natural fiber composites holds significant potential for various electrical and thermal applications due to their exceptional overall properties. • Developed hybrid filler polymer-HFP composites with nano hBN/natural fibers. • The thermal and electrical behaviours of the HFP composites were examined. • The hBN improved the thermal conductivity of the HFP composites. • GRA and ANFIS optimizations analyzed significant parameters of HFP composites. • HFP composites are suggested for electrical and microelectronic applications.

Polymer TestingVol. 139
Vellore Institute of Technology University (IN)
Openalex Percentile: Top 4%
Tribology and Wear Analysis
4.85
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