Materials with enhanced performance characteristics have served as critical enablers for the successful development of advanced technologies throughout human history. Accelerated insertion of high-performance materials in advanced technologies has been identified as a priority to addressing nowadays challenges in energy, security and human welfare. Over the past few decades, understanding of material characteristics and its functionality dictated by the complex interplay of physics and mechanics at multiple scales have grown quite a bit in the scientific community. Enhanced computational capabilities, better resources, computer technology and new manufacturing technologies are key enablers advancing our understanding. Owing to these progress, advanced materials particularly nano-scale and nano-structured materials are increasingly being used in wide range of applications. The mechanical behavior of nanomaterials is strongly influenced by interface effects as interfaces occupy significant portion of the bulk material. Modelling the dependence of properties with such defects like interfaces in nanocomposites, twin boundaries in hexagonal metals, grain boundaries in nanostructured metals and free surface in nanostructures like nanorods, is among the greatest challenges in nano-mechanics.

To address these issues, multi-physics and multi-scale simulation models considering the different physical mechanisms governing the processes at different length- and time scales have been developed. For high accuracy, atomistic models we employed and whenever convenient coupled to models operating at larger scales to predict the behavior of these materials as a function of their structural constituents under operation conditions.

1. Processing, characterization and properties of ultra-fined grained high entropy alloys
2. Multi-scale modeling of stress driven grain boundary motion
3. Effect of grain boundaries on plasticity as studied by nanoindentation
4. Multi-scale, multi-physics modeling of microstructure evolution during laser metal deposition

5. Data-driven microstructure-sensitive models for multiphase materials