My group develops artificially-intelligent discovery machines that use active learning and high-throughput approaches to discover new, synthesizable, and processable materials in unexplored chemical and structural spaces. We investigate processing-structure-property-design (PSP-D) interrelationships in tough, strong, lightweight, multi-functional, and sustainable materials. My group couples advanced additive manufacturing techniques to control hierarchical structures from sub-nano to macro-scale with data-driven numerical approaches to discover material nature. Currently, I am an Associate Professor at the Department of Mechanical Engineering and Engineering Science, University of North Carolina at Charlotte. Let me know if you have any questions at [email protected]. Click for my Google Scholar.
Some of my current research projects are:
*. Processing discovery: Machine learning-enhanced high throughput (HT) structure control in selective laser melted titaniums, zirconias, BZT-BCT lead-free piezeocereamics, and quantum dot containing thermosets.
*. Structure discovery: HT characterization of nanoscale hierarchical toughening in quantum dot containing polymer and ceramic composites
*. Data-driven recycling planning for smart cities: How to change materials, manufacturing policies to drive sustainable socio-economic development?
*. Mechanics of additively manufactured bioinspired composites and polymers
*. Automatic discovery machines for ultrasonic mixing, nano-liter droplet deposition, and robotic sample preparation coupled with field-assisted additive manufacturing
*. Hierarchical toughening in thermosetting structural battery composites
*. Hierarchical toughening in selective laser melted (SLMed) mechanobiologically optimized metal scaffolds
*. Effects of texture on the mechanical reliability of alumina, stabilized zirconia, and lead-free piezoceramics
*. Shape memory ductile ceramics: HT-Synthesis approaches for single crystal zirconia template particles for reactive templated grain growth (RTGG)
*. Extreme value statistics vs. machine-learned Monte Carlo predictions in systems/device/material reliability
*. Electric field effects on stress distributions in high electron mobility transistors (HEMT)
*. Thin film materials, manufacturing for stochastic computing, random telegraph noise (RTN) devices, and resistive memories.
*. Virtual reality engineering education (VR-EE), Virtual learning environments for engineers and society
*. Atlas of Materials Complexity, accelerating multi-functional design, materials, manufacturing innovation