- Computational Materials Science
Overcoming Timescale Challenges in Atomistic Simulations
Atomistic and first-principles modeling, which describe the world as assembly of atoms and electrons, provide the most fundamental answer to problems of materials. However, they also suffer the most severe timescale limitations. For instance, in molecular dynamics (MD) simulations, in order to resolve atomic vibrations, the integration time step is limited to hundredth of a picosecond, and therefore the simulation duration is limited to sub-microsecond due to computational cost. Although a nanosecond simulation is often enough (surprisingly) for many physical and chemical properties, it is usually insufficient for predicting microstructural evolution and thermo-mechanical properties of materials. There is clearly a timescale barrier between science-based simulations and practical demands such as understanding plant reliability and nuclear waste storage.
Energy Storage and Conversion
A close coupling of in situ experimental observations with modeling has proven to be a powerful paradigm for understanding materials behavior [Science 330 (2010) 1515; Nature 463 (2010) 335]. Based on such fundamental understandings, we are developing novel nanostructured materials for energy storage and conversion, in applications such as batteries, fuel cells and hydrogen-embrittlement resistant steels.
Materials in Extreme Environments and Far from Equilibrium
Materials in nuclear fission and fusion applications often involve exceptionally high stresses, high temperature and high radiation flux. We study the effects of radiation on microstructure and thermal, electrical and mass transport properties. The concept of fictive temperature(s) that characterize out-of-equilibrium materials is an intriguing statistical mechanics problem, with applications in glasses and even in soft biological materials.