Functionally Graded

Functionally graded materials (FGMs) are advanced composites with properties that vary smoothly and continuously across their structure, offering enhanced performance compared to traditional composites. Current research focuses on optimizing FGM design and fabrication, particularly using additive manufacturing techniques and machine learning algorithms like deep neural networks to predict material behavior and guide the design process. This work is driven by the need for improved efficiency and accuracy in creating FGMs for applications across diverse fields, including aerospace, biomedical engineering, and automotive manufacturing, where tailored material properties are crucial. The integration of data-driven methods and advanced computational models is significantly advancing the design and manufacturing of these complex materials.