International Research Journal of Education and Technology

This study focuses on the characterization and machine learning-based prediction of a multi-phase hybrid polymer composite fabricated using additive manufacturing techniques. The hybrid composite consists of an organic polymer matrix (Poly-lactic Acid - PLA) reinforced with inorganic fillers (Cobalt Ferrite - CoFe₂O₄ and Barium Titanate - BaTiO₃). Experimental investigations include mechanical (tensile, hardness, and impact), thermal (thermogravimetric analysis), and structural analysis. Machine learning models are implemented to predict the material performance based on key input parameters such as composition ratio, printing parameters, and test conditions. The results aim to optimize the composite design for potential applications in aerospace, automotive, and biomedical industries.

Key Words: Hybrid Polymer Composite, Additive Manufacturing, Machine Learning, Material Characterization, Mechanical Testing, Thermal Analysis.