In Situ Building Halide‐Alloy Dual‐Phase Interfaces for Dendrite‐Free Sulfide Solid‐State Batteries
Bibliographic record
Abstract
Abstract Argyrodite‑type sulfide solid electrolytes are promising candidates for all‑solid‑state lithium‑metal batteries due to their high Li‑ion conductivity and favorable mechanical compliance. Nevertheless, their inherent chemical reactivity toward Li metal induces continuous interfacial degradation and filamentary Li growth, undermining their practical viability. Herein, a surface‐modified Li 6 PS 5 Cl electrolyte is engineered via co‐treatment with GaCl 3 and InCl 3 , enabling the in situ formation of a multifunctional interphase upon contact with lithium metal. These conversion reactions produce a LiCl‐rich, electronically insulating matrix interlaced with lithiophilic Li‐Ga and Li‐In alloys. The LiCl matrix enhances interfacial energy to inhibit dendrite formation, while the alloy network promotes continuous and uniform lithium‐ion transport. Concurrently, this interfacial layer scavenges irregular Li deposits formed during initial plating and acts as a conformal interlayer to maintain intimate contact. Consequently, Li||Li symmetric cells achieve exceptional cycling stability (>2600 h at 0.5 mA cm −2 ). Paired with a Nickel‐rich LiNi 0.9 Mn 0.05 Co 0.05 O 2 cathode, full cells retain 80% capacity retention after 1000 cycles at 0.5 C with an ultra‐thin 50 µm Li anode. This study highlights the effectiveness of engineered surface coating layers in stabilizing the anode interface with minimal disruption to the sulfide electrolyte framework.
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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".