His project will use discrete dislocation dynamics (DDD) and crystal plasticity (CP) modeling to predict the performance of structural metals at length and time scales relevant to engineering applications. CP models, while often used to simulate deformation in precipitation-strengthened metals such as high-strength aluminum alloys, are not physics-based. By analyzing large-scale DDD simulations, Sills intends to advance the understanding of aluminum and other performance-critical alloys by developing new, predictive, physics-based CP models that can serve as guides for alloy and process design for the next generation of high-performance alloys.
“I am driven by the world’s need for better materials and better models to predict material performance,” says Sills who conducts research in his Mechanics of Deformation lab (mMOD). By significantly advancing the predictive capabilities of material models, his project will likely lead to reduced-cost and lighter-weight engineering structures with less conservative designs.