Understanding the Reactivity of a Thin Li<sub>1.5</sub>Al<sub>0.5</sub>Ge<sub>1.5</sub>(PO<sub>4</sub>)<sub>3</sub> Solid‐State Electrolyte toward Metallic Lithium Anode
Bibliographic record
Abstract
Abstract The thickness of solid‐state electrolytes (SSEs) significantly affects the energy density and safety performance of all‐solid‐state lithium batteries. However, a sufficient understanding of the reactivity toward lithium metal of ultrathin SSEs (<100 µm) based on NASICON remains lacking. Herein, for the first time, a self‐standing and ultrathin (70 µm) NASICON‐type Li1.5Al0.5Ge1.5(PO4)3 (LAGP) electrolyte via a scalable solution process is developed, and X‐ray photoelectron spectroscopy reveals that changes in LAGP at the metastable Li–LAGP interface during battery operation is temperature dependent. Severe germanium reduction and decrease in LAGP particle size are detected at the Li–LAGP interface at elevated temperature. Oriented plating of lithium metal on its preferred (110) face occurs during in situ X‐ray diffraction cycling.
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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 | 0.001 |
| 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".