2024/04/02 by Seong‐Hoon Jang, Randy Jalem, Jang, Seong-Hoon +3 · 1 citation
Chemical Engineering · Chemistry · Materials Science · #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Ionic liquids properties and applications #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Metal-Organic Frameworks: Synthesis and Applications
paper · pdf · doi:10.48550/arxiv.2404.01627
openalex publication_date 2024/04/02 · openalex created_date 2024/04/05 · openalex updated_date 2026/07/28
Given the vast compositional possibilities NanMmMm'Si3-p-aPpAsaO12, Na-ion superionic conductors (NASICON) are attractive but complicate for designing materials with enhanced room-temperature Na-ion conductivity σ\rm Na,300K. We propose an explicit regression model for σ\rm Na,300K with easily-accessible descriptors, by exploiting density functional theory molecular dynamics (DFT-MD). Initially, we demonstrate that two primary descriptors, the bottleneck width along Na-ion diffusion paths d1 and the average Na-Na distance ⟨ d\rm Na-Na ⟩, modulate room-temperature Na-ion self-diffusion coefficient D\rm Na,300K. Then, we introduce two secondary easily-accessible descriptors: Na-ion content n, which influences d1, ⟨ d\rm Na-Na ⟩, and Na-ion density ρ\rm Na; and the average ionic radius ⟨ rM ⟩ of metal ions, which impacts d1 and ⟨ d\rm Na-Na ⟩. These secondary descriptors enable the development of a regression model for σ\rm Na,300K 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 σ\rm Na,300K > 103 S⋅cm-1. Furthermore, the adjusted version effectively fits 140 experimental values with R2=0.718.