The objective of this work is to enhance the thermal conductivity and electrical properties of polymer hybrid composites through a systematic novel grey relation grade analysis (GRGA) optimization approach. This involves reinforcing the hybrid composites with hexagonal boron nitride (hBN) and various kinds of natural fibers or fillers. The development of a unique technology to produce multiphase composites using 2% of natural fibers or fillers such as coir fiber, rice husk filler, wood filler (WF), banana fiber (BF) and sugarcane fiber along with hBN (1, 3, 5 wt.%) particulates as reinforcements in epoxy matrix. The Taguchi L15 matrix array is utilized to fabricate interlaced composite samples via hand layup molding. Ultrasonic waves are used to ensure the uniform distribution of hBN filler into the matrix. Analysis of variance and GRGA reveal the significant results. It shows that the multiphase hybrid composites exhibit good thermal conductivity when higher content of hBN (5 wt.%) particulate for all the micro particulate polymer (MPP) composites. Multi-response optimization shows that the micro BF (2 wt.%) interlaces with hBN (5 wt.%) composite exhibits the higher thermal conductivity and electrical resistance compared to all other natural fiber interlaced composites. The aforementioned MPP composite has thermal conductivity of 1.03 W (m·K)⁻¹ and electrical resistance of 279.88 Giga Ohms. Besides, the WF interlaced hBN (5 wt.%) composite shows the minimum dielectric constant compared to all other natural fiber composites. This desirable result is caused by the proper dispersion of hBN with the matrix which encourages interlocking with the fiber and the matrix. Maximum electrical resistance is observed for composite containing 5 wt.% of h-BN and 2 wt.% of BF. The developed MPP composite could be used in heat shields, electrical insulation components, and interior automotive components like dashboards, luggage compartments and interior walls.

In this work, recent developments in area of thermally conductive polymer matrix composite are discussed. Thermally conductive Boron Nitride (BN)/ Banana fiber (BF)/ reinforced environment friendly epoxy polymer matrix composite is prepared. Scanning electron microscope (SEM) analysis of BN is carried out to ensure desired particle size. The effect of wt. % of BN/ BF on thermal conductivity is investigated. Box Behnken Model (BBD) from Response surface methodology (RSM), an approach of design of experiments (DOE), is used for preparation of sample to choose possible wt. % of BN/ BF and ANOVA is carried out using MINITAB software to get optimized levels of parameters through regression model. Validation of optimized results with experimental one is discussed. Thermal conductivity of 1.06741 W/m-K is obtained for optimum combination of 5 wt. % of BN with particle size of 5 μm and 1.2 wt. % of BF.

Composite materials have a wide range of applications in emerging eco-friendly environments. Composites that created from naturally available materials are easily decomposed over time and very cost-effective. Fly ash and sugarcane fiber are widely available waste materials produced on a massive scale. This research was aimed to find an optimal mixture of reinforced composites (fly ash, sugarcane fiber and CNTs) in order to maximize yield strength, ultimate tensile strength and Young’s modulus using a Multi-Objective Evolutionary Algorithm with Decomposition (MOEA/D). Optimizing one objective may have a negative impact on another objective, so the authors used the sophisticated MOEA/D algorithm to simultaneously find optimal values on all three objectives. The Design of Experiments (DOE) method was performed using ANOVA, and then regression equations were generated. The regression equations were optimized using the MOEA/D algorithm to obtain optimal values. Using the optimal compositional values produced by the algorithm, materials were fabricated. The fabricated materials were tested using a Shimadzu UTM machine to cross-validate the findings. A combination of 0.2 wt.% of fly ash, 2 wt.% of SCF, and 0.39 wt.% of CNTs showed a maximum yield strength of 7.52 MPa and Young’s modulus of 1281.18 MPa, with a quite considerable ultimate tensile strength of 10.54 MPa compared with the optimized results obtained through the response surface methodology.