Dual-component Interlayer Enables Uniform Lithium Deposition and Dendrite Suppression for Solid-State Batteries
Bibliographic record
Abstract
β-Lithium thiophosphate (LPS) exhibits high Li+ conductivity and has been identified as a promising ceramic electrolyte for safe, and high-energy density all-solid-state batteries. Integrating LPS into solid-state lithium (Li) batteries would enable the use of a Li electrode with the highest deliverable capacity. However, LPS-based batteries operate at a limited current density before short-circuiting, posing a major challenge for the development of application-relevant batteries. In this work, we designed a dual-component interfacial protective layer called LiSn-LiN, that forms in-situ between the Li electrode and LPS electrolyte. The LiSn component, Li22Sn5, exhibits enhanced Li diffusivity compared to the metallic Lithium and facilitates a more uniform lithium deposition across the electrode surface, thus eliminating Li dendrite formation. Meanwhile, the LiN component, Li3N, shows enhanced mechanical stiffness compared to LPS and functions to suppress dendrite penetration. This chemically robust LiSn-LiN interlayer provides a more than doubled deliverable critical current density compared to systems without interfacial protection. Through a combined XPS and XAFS analysis, we determined the local structure and the formation kinetics of the key functional Li22Sn5 phase formed via the electrochemical reduction of a Sn3N¬¬¬4 precursor. This work demonstrates an example of structural-specific design of a protective interlayer with a desired function – dendrite suppression. The structure of a functional protective layer for a given solid-state battery should be tailored based on the given battery configuration and its unique interfacial chemistry.
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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".