Multifunctional materials research is focused on the design, synthesis and modeling of novel materials such as self-sensing and self-healing materials (mechanophores), stress-responsive “smart” materials, shape morphing nanopolymers, carbon nanotube buckypapers.
Multiscale modeling research focusses on developing comprehensive multiphysics framework, bridging length scales from atomistic to the structural scale, including geometric and material variability, and damage for accurate prediction of material behavior and failure under service conditions for a wide range of materials such as polymer matrix composites (PMC), ceramic matrix composites (CMC), metallic alloys and superalloys.
Research in this area is focused on developing active and passive damage assessment techniques and residual life estimation methodologies for a wide range of applications. Topics include sensors and sensor architecture, information fusion, machine learning techniques, and automated decision making technologies.
Research includes microstructural analysis, material characterization and testing of a wide range of material systems for comprehensive understanding of material characteristics and damage under complex loading using state-of-the-art load frames such as the biaxial-torsion and ultrasonic fatigue frame, and advanced characterization techniques such as digital image correlation (DIC), confocal laser scanning microscopy (CLSM), scanning probe microscope (SPM).