Researchers from Duke University and partners have discovered the atomic mechanisms which make up a group of substances known as argyrodites, making them highly suitable for solid-state battery electrolytes and thermoelectric energy converters. This groundbreaking discovery was made possible utilizing a machine learning approach and was recently published in the journal Nature Materials.
The world has a growing need for renewable energy storage and distribution technologies, yet the standard lithium-ion battery comes with significant drawbacks such as relatively low efficiency and potential fire hazards from the liquid electrolyte. To overcome this limitation, solid-state batteries are being developed from a variety of materials to offer more stable devices with higher energy density.
Argyrodites, named after a silver-containing mineral, are a promising candidate for this purpose. They are built from a combination of two elements, with a third element being free to move around. By using a combination of neutrons and x-rays, the researchers were able to observe the molecular behavior in real-time. Furthermore, a machine-learning approach was used by Mayanak Gupta, a former postdoc in Delaire’s lab, to build a computational model to match these observations using first-principles quantum mechanical simulations.
The results showed that the tin and selenium atoms remained stable while the silver ions moved freely through the material, like the silver atoms were marbles rattling around in a shallow well. This duality of a material being both liquid and solid is highly intriguing and could present a game-changer for electric vehicles, allowing them to charge faster and last longer with improved safety components.
Delaire and his team are presently looking at other promising argyrodite compounds, including one that might replace silver with lithium. If the correct combinations are found, it could be a major advancement in energy storage.
The Duke University researchers are at the forefront of this potential breakthrough, utilizing advanced experimental spectroscopy and machine learning in order to better understand argyrodite materials. This effort was funded by various sources, including the Guangdong Basic and Applied Basic Research Foundation, the U.S. National Science Foundation, the “Shuguang program” from the Shanghai Education Development Foundation and Shanghai Municipal Education Commission, and the Australian Research Council.
