Scientists at Caltech and Yale University have achieved a breakthrough in predicting the Kondo effect in actual materials, addressing a longstanding challenge that has limited researchers to approximate calculations using simplified models. The new computational approach operates directly from a material’s complete atomic and electronic structure, rather than relying on reduced representations of the system. This advance could enable more realistic simulations of complex quantum materials, including high-temperature superconductors where electron behavior is tightly coupled across the system.
The Kondo effect occurs when a magnetic atom, such as iron or manganese, is embedded as an impurity within a metal like copper. When cooled below a certain threshold temperature, the system exhibits unusual electrical properties: resistance stops decreasing and instead begins to increase as cooling continues further. This phenomenon arises from interactions between electrons traveling through the metal and the magnetic moment of the embedded impurity, ultimately creating a screening cloud of electrons that masks the atom’s magnetism.
Traditional computational methods have simplified the electronic structure of materials by reducing them to a limited set of electron orbitals and applying approximate mathematical frameworks. The research team pursued an alternative strategy by adapting computational tools originally developed for studying molecules in quantum chemistry and applying them to quantum materials. This allowed them to retain the full complexity of electronic interactions while treating the magnetic impurities similarly to molecular systems.
Testing their method on seven transition-metal atoms embedded in copper, the researchers achieved predictions up to two orders of magnitude more accurate than those obtained from conventional model-based approaches. The findings appear in Science, with lead authors Linqing Peng and Tianyu Peng of Yale University conducting the work under the supervision of Garnet Chan, a professor at Caltech. The results represent progress toward computationally designing materials with functions emerging from correlated electron physics.
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