Predictive and Accurate Monte Carlo-Based Simulations for Mott Insulators, Cuprate Superconductors, and Nanoscale Systems
Overview
Principal Investigator: Thomas Schulthess
Affiliation: Oak Ridge National Laboratory
Machine: Cray XT4
Allocation: 10,000,000 processor hours
Research Summary:
Better electric grid technologies, high-density magnetic hard drives, and more efficient biofuel production require that we understand and optimize relevant materials. This project will perform simulations of Mott insulators, high-temperature superconductors, magnetic nanoparticles, and select biomolecular systems that are key for meeting these goals and will accelerate development of such technologies. Applying recent advances in Monte Carlo techniques, this project will push the envelope of computational science at the petascale to understand, predict, design, and exploit complex behavior that emerges at the nanoscale.