Discovering virtual Na-based argyrodites as solid-state electrolytes using DFT, AIMD, and machine learning techniques

Kee-Sun Sohn,Byung Do Lee,Deepak S Gavali,Heejeong Kim,Seonghwan Kim,Min Young Cho,Kyunglim Pyo,Young-Kook Lee,Woon Bae Park

doi:10.1039/d4ta06927g

Discovering virtual Na-based argyrodites as solid-state electrolytes using DFT, AIMD, and machine learning techniques

Kee-Sun Sohn, Byung Do Lee + Show 7 more

https://doi.org/10.1039/d4ta06927g

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Journal: Journal of Materials Chemistry A

Publication Date: Jan 1, 2025

#Solid-state Electrolytes #Machine Learning Techniques #DFT Techniques #Hypothetical Structures #DFT Calculations #Large Compositional Space #Compositional Space #Machine Learning

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In light of the current absence of experimentally synthesized Na-based argyrodites, we systematically investigated a large compositional space comprising 4375 hypothetical Na-based argyrodite structures through DFT and AIMD calculations.

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Discovering virtual Na-based argyrodites as solid-state electrolytes using DFT, AIMD, and machine learning techniques