An Air‐Stable and Li‐Metal‐Compatible Glass‐Ceramic Electrolyte enabling High‐Performance All‐Solid‐State Li Metal Batteries
Bibliographic record
Abstract
Abstract The development of all‐solid‐state Li metal batteries (ASSLMBs) has attracted significant attention due to their potential to maximize energy density and improved safety compared to the conventional liquid‐electrolyte‐based Li‐ion batteries. However, it is very challenging to fabricate an ideal solid‐state electrolyte (SSE) that simultaneously possesses high ionic conductivity, excellent air‐stability, and good Li metal compatibility. Herein, a new glass‐ceramic Li3.2P0.8Sn0.2S4 (gc‐Li3.2P0.8Sn0.2S4) SSE is synthesized to satisfy the aforementioned requirements, enabling high‐performance ASSLMBs at room temperature (RT). Compared with the conventional Li3PS4 glass‐ceramics, the present gc‐Li3.2P0.8Sn0.2S4 SSE with 12% amorphous content has an enlarged unit cell and a high Li+ ion concentration, which leads to 6.2‐times higher ionic conductivity (1.21 × 10−3 S cm−1 at RT) after a simple cold sintering process. The (P/Sn)S4 tetrahedron inside the gc‐Li3.2P0.8Sn0.2S4 SSE is verified to show a strong resistance toward reaction with H2O in 5%‐humidity air, demonstrating excellent air‐stability. Moreover, the gc‐Li3.2P0.8Sn0.2S4 SSE triggers the formation of Li–Sn alloys at the Li/SSE interface, serving as an essential component to stabilize the interface and deliver good electrochemical performance in both symmetric and full cells. The discovery of this gc‐Li3.2P0.8Sn0.2S4 superionic conductor enriches the choice of advanced SSEs and accelerates the commercialization of ASSLMBs.
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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".