Enhancement of mechanical and tribological properties in glass fiber-reinforced polymer composites with multi-walled carbon nanotubes and ANN-based COF prediction

The study investigated the effects of incorporating multi-walled carbon nanotubes (MWCNTs) into glass fiber-reinforced polymer composites on their mechanical and tribological properties. Experimental results demonstrated significant enhancements across various parameters. Microhardness increased by 25.03%, attributed to improved interfacial bonding and load transfer facilitated by MWCNTs. Tensile strength and modulus improved by 10.58% and 28.2%, respectively, indicating reinforced load-bearing capacity. Flexural strength and modulus increased by 33.78% and 36.29%, respectively, due to enhanced interfacial bonding. Inter-laminar shear strength (ILSS) exhibited a notable increase of 20.79% with MWCNT incorporation. Ity mpact toughness improved by 19.41% in Izod and 32.32% in Charpy tests, attributed to MWCNTs' energy-dissipating properties and enhanced interfacial bonding. Tribological tests showed decreased wear and friction coefficients, along with reduced debris formation and fiber breakage in SEM analysis, indicating improved bonding between the matrix and fibers. Furthermore, an artificial neural network (ANN) model accurately predicted the coefficient of friction, aligning well with experimental values, offering potential for predictive modeling in composite material analysis. Overall, the incorporation of MWCNTs significantly enhanced mechanical properties and wear resistance of the composite material. [GRAPHICS]