New physics-based machine-learning method speeds search for 2D quantum materials

Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional materials that may host unusual quantum behavior. The work, published in Science Advances, focuses on materials with “flat bands,” electronic states where electrons have very little kinetic energy. In these materials, interactions between electrons can become much more important, creating conditions linked to phenomena such as magnetism, unconventional superconductivity and topological electronic behavior.