Rotational Stacking Faults in the Ionic Conductor Li <sub>3</sub> ScCl <sub>6</sub>
Bibliographic record
Abstract
Halide-based solid electrolytes have gained recent interest due to their promising ionic conductivity and wide electrochemical stability window, but the influence of synthesis conditions on structure is not fully characterized. Here, we report a combined experimental and computational study of the effect of thermal treatment temperature on the structure and Li + conduction dynamics of the superionic halide Li 3 ScCl 6 . Synchrotron diffraction analysis shows that samples treated between 450 °C and 750 °C form the monoclinic Li 3 ScCl 6 structure and contain rotational stacking faults, whose density increases with thermal treatment temperature and mechanical processing time. Impedance spectroscopy, nuclear magnetic resonance spectroscopy, and molecular dynamics simulations using machine-learned interatomic potentials, however, indicate that these faults have a negligible effect on long-range Li + conductivity, though local Li + dynamics are modified. This work demonstrates that Li 3 ScCl 6 maintains robust transport properties despite rotational stacking faults, and highlights the importance of in-depth structural analyses for understanding the relationships between synthesis protocols, structure, and ionic transport in halide solid electrolytes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".