Machine Learning for Solid-State Battery Development: Uncovering Atomic Mechanisms behind Argyrodites

A machine learning approach provides new insights into the class of materials that are being sought for solid-state battery technology

Researchers at Duke University, along with their collaborators, have discovered the atomic mechanisms behind argyrodites’ appeal as solid-state batteries and thermoelectric energy convertors.

The findings, and the machine-learning approach that was used to make them, could help usher in an era of energy-storage for applications like household battery walls or fast-charging electrical vehicles.

Nature Materials published the results online on May 18.

Source:
https://phys.org/news/2023-05-machine-approach-insights-entire-class.html

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