Bio
Predicting mechanical strength of materials through theory and simulations of defect microstructures across atomic, mesoscopic and continuum scales. Developing new atomistic simulation methods for long time-scale processes, such as crystal growth and self-assembly. Applying machine learning techniques to materials research. Modeling and experiments on the metallurgical processes in metal 3D printing. Understanding microstructure-property relationship in materials for stretchable electronics, such as carbon nanotube networks and semiconducting elastomers.