Once again, the Department of Energy’s Titan supercomputer has helped propel a scientific breakthrough with far-ranging implications. Researchers with Rutgers University have used the 27-petaflops supercomputer, a key resource of Oak Ridge National Laboratory (ORNL), to advance their understanding of the link between spin dynamics and superconductivity.
As explained in this feature article from ORNL’s Katie Elyce Jones, spin dynamics refers to the ways that electrons within a material orient and correlate their spins. These spin patterns were found to be key predictors of superconductivity, the ability to conduct electricity with little or no resistance at higher temperatures. There is a big push to identify “natural” superconductors that do not require expensive cooling in order to demonstrate this desired trait.
The team from Rutgers computed the dynamic spin structure factors of 15 iron-based materials, including several high-temperature superconductors. Their findings are published in a recent edition of Nature Physics.
Materials science has come a long way in the last decade, largely as a result of increased computational power. The field tends toward complex problems, better suited for supercomputers, like Titan, than for smaller clusters. The team employed several methods to carry out their work, including Dynamical Mean Field Theory and Monte Carlo sampling.
“Our computational results are in good agreement with experimental results for experiments that have been performed, and we have several predictions for compounds that have not yet been measured,” team member Gabriel Kotliar reported in the ORNL piece. “Once we validate the theory that our computational models are based on with experiments, then we can investigate materials computationally that are not being studied experimentally.”