Predicting Room‐Temperature Conductivity of Na‐Ion Super Ionic Conductors with the Minimal Number of Easily‐Accessible Descriptors

Abstract

Given the vast compositional possibilities NanMmMm′′Si3−p−aPpAsaO12, Na‐ion superionic conductors are attractive but complicated for designing materials with enhanced room‐temperature Na‐ion conductivity σNa,300 K. An explicit regression model for σNa,300 K with easily‐accessible descriptors is proposed by exploiting density functional theory molecular dynamics (DFT‐MD). Initially, it is demonstrated that two primary descriptors, the bottleneck width along Na‐ion diffusion paths d1 and the average Na–Na distance ⟨dNa−Na⟩, modulate room‐temperature Na‐ion self‐diffusion coefficient DNa,300 K. Then, two secondary easily‐accessible descriptors are introduced: Na‐ion content n, which influences d1, ⟨dNa−Na⟩, and Na‐ion density ρNa; and the average ionic radius ⟨rM⟩ of metal ions, which impacts d1 and ⟨dNa−Na⟩. These secondary descriptors enable the development of a regression model for σNa,300 K with n and ⟨rM⟩ only. Subsequently, this model identifies a promising yet unexplored stable composition, Na2.75Zr1.75Nb0.25Si2PO12, which, upon DFT‐MD calculations, indeed exhibits σNa,300 K>10−3 S cm−1. Furthermore, the adjusted version effectively fits 140 experimental values with R2=0.718.

Keywords

• beta regression modeling
• materials design
• materials informatics
• solid electrolytes