Rajiv Kalia

Research Summary

Kalia and his team perform multi-scale simulations of nano-structured materials and processes using quantum molecular dynamics (QMD), reactive molecular dynamics (RMD), and dissipative particle dynamics stimulations of hard and soft materials. Current research efforts are focused on petascale simulations of: 1) synthesis of layered materials and thermo-mechanical, electrical and optical properties of layered material architectures; 2) self-healing nanoomaterials capable of sensing and repairing damage in harsh chemical environments and in high-temperature/high-pressure operating conditions; 3) structural and dynamic correlation in fluids confined in nanoporous materials; 4) nanoengineered energetic materials and munitions under extreme conditions; 5) shock propagation and pressure-induced structural transformations in nanocluster assemblies and self-assembled monolayers; 6) nucleation and growth of cracks, stress corrosion, and delamination at metal/ceramic, semiconductor/ceramic, and polymer/ceramic interfaces; 7) cholesterol flip-flop dynamics and barriers to small interfering RNA delivery across biomembranes; 8) supercrystals of DNA-functionalized metal nanoparticles; 9) AI driven design, discovery and manufacturing of quantum materials architectures; and 10) AI driven mathematical modeling of viral dynamics in COVID-19 patients.

Teaching Overview
In the education area, Kalia has designed a new graduate-level course titled Mathematical Methods for Deep Learning. Together with his CACS team, he has established a dual-degree curriculum for graduate students to obtain a Ph.D. in the physical sciences or in materials or biomedical sciences/engineering together with an M.S. in computer science.