Perovskite-Type Electrolyte for Ceramic Lithium Batteries: Enhanced Microstructure and Bulk Ionic Conductivity
Bibliographic record
Abstract
Solid-state lithium batteries (SSLBs) have shown great potential in energy storage applications, having the potential to enhance energy densities, while providing superior safety compared to conventional liquid electrolyte-based lithium batteries. Perovskite-type LLTO electrolytes are a promising candidate for SSLBs, due to their excellent ionic conductivities with values in excess of 10 -3 S cm -1 at room temperature. However, their application in SSLBs is hindered by catastrophic dendrite formation and unstable interfaces during cycling with Lithium metal. It is also difficult to formulate electrolytes with desirable mechanical properties and high bulk ionic conductivity. Herein, in order to understand the microstructure, bulk ionic conductivity and mechanical properties of the most studied LLTO (Li 0.3 La 0.5 TiO 3 ), cold-press sintering was used to prepare pellets with different thicknesses using a mixture of coarse and fine LLTO powders: D50=~40μm, and D50=~1μm, respectively. This significantly enhanced the compactness and density achieved in the cold pressing stage. The sintered pellets showed a modified grain boundary pattern with an enhanced bulk ionic conductivity of 10 -4 -10 -6 S cm -1 between 20˚C and 60˚C and a low activation energy of ~0.21eV. Symmetric cells and half-cells using the as-prepared pellets are currently being assembled for further electrochemical characterization.
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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".