Impact of TiO<sub>2</sub> at the Grain Boundaries in Lithium Lanthanum Titanate Solid Electrolytes
Bibliographic record
Abstract
The enhancement of Li-ion conductivity within the perovskite Li–La–Ti-O samples (LLTO) by the addition of TiO 2 remains unexplained in the literature. Herein, microscopy shows that TiO 2 appears at the grain boundaries (GB) of the perovskite, prompting a comprehensive molecular dynamics investigation. In this work, we analyzed symmetric and mixed LLTO GBs, as well as LLTO/TiO 2 interfaces, to understand the impact of the secondary phase on Li-ion conductivity compared to other factors, such as disorder or strain present in the samples due to the GBs. The rigid-ion Buckingham-type potential combined with a long-range Coulombic term was used to accurately model ionic interactions. The investigation of diffusion mechanisms through mean squared displacement (MSD) analysis unveiled that disordered TiO 2 phases significantly enhance Li-ion mobility compared with more orderly Sigma 5 or mixed GBs. This suggests that the disorder may create additional pathways for ion diffusion not present in symmetric GBs or crystalline LLTO samples. Furthermore, the enhanced Li-ion diffusion through LLTO/TiO 2 interfaces was indeed observed in the calculations and is attributed to the presence of TiO 2 phases and, to a lesser extent, to the highly disordered interface formed between them. These insights into the intricate migration mechanisms of Li ions through the exceptionally complex microstructures present in LLTO could advance the development of efficient solid-state electrolytes for Li-ion battery applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".