In Situ Li<sub>3</sub>PS<sub>4</sub> Solid‐State Electrolyte Protection Layers for Superior Long‐Life and High‐Rate Lithium‐Metal Anodes
Bibliographic record
Abstract
Abstract A thin and adjustable Li3PS4 (LPS) solid‐state electrolyte protection layer on the surface of Li is proposed to address the dynamic plating/stripping process of Li metal. The LPS interlayer is formed by an in situ and self‐limiting reaction between P4S16 and Li in N‐methyl‐2‐pyrrolidone. By increasing the concentration of P4S16, the thickness of the LPS layer can be adjusted up to 60 nm. Due to the high ionic conductivity and low electrochemical activity of Li3PS4, the intimate protection layer of LPS can not only prevent the formation of Li dendrites, but also reduces parasitic side reactions and improves the electrochemical performance. As a result, symmetric cells with the LPS protection layer can deliver stable Li plating/stripping for 2000 h. Full cells assembled with the LPS‐protected Li exhibit two times higher capacity retention in Li–S batteries (≈800 mAh g−1) at 5 A g−1 for over 400 cycles compared to their bare Li counterparts. Furthermore, high rate performances can be achieved with Li‐LPS/LiCoO2 cells, which are capable of cycling at rates as high as 20 C. This innovative and scalable approach to stabilizing the Li anode can serve as a basis for the development of next‐generation high‐performance lithium‐metal batteries.
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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".