Vacancy Driven Fast Ion Conduction in Lithium Deficient Magnesium Chloride Spinel
Bibliographic record
Abstract
Chloride solid electrolytes are promising catholytes for 4 V all-solid-state batteries due to their intrinsic stability and excellent compatibility with high-voltage cathodes. Until now, very few spinel chlorides have been reported to have good ionic conductivity. We report a simple (no ball-milling required) and effective synthetic approach to boost the ionic conductivity of nonconductive Li 2 MgCl 4 by aliovalent substitution, to adjust the Li ion carrier and vacancy concentration. Reducing the Li ion content leads to Li vacancies in the original fully occupied Li1 (8 a ) site and Li ion redistribution over a new Li2 (16 c ) site in Li 1.6 Sc 0.4 Mg 0.6 Cl 4 . The face-sharing Li tetrahedra and octahedra form a continuous 3D Li ion diffusion pathway with high Li vacancy and carrier concentration, driving nearly 2 orders of magnitude conductivity rise vs Li 2 MgCl 4 . A LiNi 0.85 Co 0.1 Mn 0.05 O 2 ASSB using a Li 1.6 Sc 0.4 Mg 0.6 Cl 4 catholyte showed good cycling stability over 180 cycles with a 4.8 V vs Li + /Li upper cutoff potential.
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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".