Physicists Utilize Machine Learning Tool to Detect Elusive ‘Bragg Glass’ Phase

Cornell quantum researchers have detected an elusive phase of matter, called the Bragg glass phase, using large volumes of x-ray data and a new machine learning data analysis tool. The discovery settles a long-standing question of whether this almost–but not quite–ordered state of Bragg glass can exist in real materials.

graphic of a material showing yellow and purple balls connected by lines, Click to open gallery view
Crystal structure of pure ErTe3
The paper, “Bragg glass signatures in PdxErTe3 with X-ray diffraction Temperature Clustering (X-TEC),” published in Nature Physics on Feb. 9. The lead author is Krishnanand Madhukar Mallayya, postdoctoral researcher in the Department of Physics in the College of Arts and Sciences (A&S). Eun-Ah Kim, professor of physics (A&S), is the corresponding author. The research was conducted in collaboration with scientists at Argonne National Laboratory and at Stanford University.

The researchers present the first evidence of a Bragg glass phase as detected from X-ray scattering, which is a probe that accesses the entire bulk of a material, as opposed to just the surface of a material, in a systematically disordered charge density wave (CDW) material, PdxErTe3. They used comprehensive X-ray data and a novel machine learning data analysis tool, X-ray Temperature Clustering (X-TEC).

“Despite its theoretical prediction three decades ago, concrete experimental evidence for CDW Bragg glass in the bulk of the crystal remained missing,” Mallayya said.