Amorphous AlOCl Compounds Enabling Nanocrystalline LiCl with Abnormally High Ionic Conductivity
Bibliographic record
Abstract
LiCl is a promising solid electrolyte, providing it possesses high ionic conductivity. Numerous efforts have been made to enhance its ionic conductivity through aliovalent doping. However, aliovalent substitution changes the intrinsic structure of LiCl, compromising its cost-effectiveness and electrochemical stability. Here, we report nanocrystalline LiCl embedded in amorphous AlOCl compounds with a heterogeneous structure to enhance its ionic conductivity. Nanocrystallization enlarges the LiCl unit cell, while amorphization facilitates interfacial ion transport. As a result, the amorphous AlOCl-modified LiCl nanocrystal (AlOCl-nanoLiCl) demonstrates a high ionic conductivity of 1.02 mS cm –1, which is 5 orders of magnitude higher than that of LiCl. Additionally, it exhibits high oxidative stability, low cost ($19.87 US kg –1 ), and low Young’s modulus (2–3 GPa). When AlOCl-nanoLiCl is coupled with Li-rich cathodes (Li 1.17 Mn 0.55 Ni 0.24 Co 0.05 O 2, 4.8 V vs Li + /Li), all-solid-state batteries exhibit remarkable long-term cycling stability (>1000 cycles). This work presents a novel strategy to enhance the ionic conductivity of alkaline chlorides without compromising their intrinsic advantages.
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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 | 0.001 | 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".