Machine Learning Approaches to Predict Tensile Strength in Nanocomposite Materials a Comparative Analysis

Nanotechnology plays a crucial role in improving the properties of composite materials by incorporating nano-fillers, which enhance mechanical, thermal, and electrical performance. The integration of nano-fillers at different concentrations (%) significantly influences the overall properties of the composites. A precise balance of nano-filler concentration is essential, as an optimal amount leads to improved strength and durability, while excessive loading can cause agglomeration, leading to reduced performance. Generally, studies show that nano-filler concentrations ranging from 0.5% to 5% by weight yield optimal enhancements in tensile strength, toughness, and impact resistance. Processing temperature (°C) is another critical parameter in nano composite fabrication. The uniform dispersion of nano-fillers within the polymer or metal matrix requires controlled processing conditions to avoid defects and inconsistencies. Higher processing temperatures facilitate better matrix-filler interaction, enhancing the mechanical properties of the final composite. However, extreme temperatures can degrade the polymer matrix or lead to unwanted phase transformations in metal composites, thereby