Award-winning supercomputer solves superconductor homogeneity puzzle

An award winning high-performance computing application developed by scientists has been used to examine the nanoscale inhomogeneities in superconductors that had long been noticed but left unexplained.

Thomas Maier and colleagues Gonzalo Alvarez, Michael Summers and Thomas Schulthess from Oak Ridge National Laboratory rewrote computational code for the numerical Hubbard model that previously assumed copper-compound superconducting materials known as cuprates to be homogenous - the same electron density - from atom to atom.

"Cuprates and other chemical compounds used as superconductors require very cold temperatures, nearing absolute zero, to transition from a phase of resistance to no resistance," said Jack Wells.

Liquid nitrogen is used to cool superconductors into phase transition - the colder the conductive material has to get to reach the resistance-free superconductor phase, the less efficient and more costly the superconductor power infrastructures.

"The goal following the Gordon Bell Prize was to take that supercomputing application and learn whether these inhomogenous stripes increased or decreased the temperature required to reach transition," Wells said.

In an ideal world, a material could become superconductive at an easily achieved and maintained low temperature, eliminating much of the accompanying cost of the cooling infrastructure.

"The next step in our progress is a hard problem," Wells said.

"But from our lab's point of view, all of the major tools suited for studying this phenomenon - the computational codes we've written, the neutron scattering experiments that allow us to examine nanoscale properties - are available to us here."

The paper is published in Physical Review Letters.