A data-mining approach to understanding the impact of multi-doping on the ionic transport mechanism of solid electrolytes materials: the case of dual-doped Ga0.15/Scy Li7La3Zr2O12

Henry A. Cortés*, Mauricio R. Bonilla, Herbert Früchtl, Tanja van Mourik, Javier Carrasco, Elena Akhmatskaya

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study presents novel computational methods applied to the technologically significant solid electrolyte materials, Li6.55+yGa0.15La3Zr2−yScyO12 (Ga0.15/Scy-LLZO), in order to investigate the effect of the distribution of Ga3+ on Li-ion dynamics. Utilizing a specifically designed first-principles-based force field, molecular dynamics, and advanced hybrid Monte Carlo simulations, we systematically examine the material's transport properties for a range of Ga3+ and Sc3+ cationic concentrations. Additionally, we introduce innovative post-processing methods employing data mining clustering techniques, shedding light on Li+ ion behavior and conductivity mechanisms. Contrary to prior assumptions, the presence of Ga3+ in octahedral sites, not tetrahedral junctions, optimally enhances Li-ion conductivity, unlocking Li-ion diffusion pathways. The research illuminates how dopant distribution influences Li+ site occupancy and conductivity, offering key insights for advanced solid electrolyte design.
Original languageEnglish
Number of pages13
JournalJournal of Materials Chemistry A
VolumeAdvance Article
Early online date19 Jan 2024
DOIs
Publication statusE-pub ahead of print - 19 Jan 2024

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