(Digital Presentation) Understanding the Chemistry and Microstructure Evolution of Cathodic Interface in All-Solid-State Batteries
Bibliographic record
Abstract
All-solid-state lithium-ion batteries (SSLIBs) are promising candidates to meet the requirement of electric vehicles due to the intrinsic safety characteristics and high theoretical energy density. A stable cathodic interface is critical for maximizing the performance of SSLIBs. In our study, operando X-ray absorption near-edge spectroscopy (XANES) combined with transmission electron microscopy (TEM) and electron energy loss spectroscopy (EELS) is employed to investigate the interfacial behavior between the Li-ion cathodes and sulfide solid-state electrolyte. Constructing a uniform interlayer by atomic layer deposition (ALD) is also employed in this study to further investigate the cathodic interface stability. These results provide new insight into the cathodic interface reaction mechanism and highlight the importance of advanced operando characterizations for SSLIBs.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.053 | 0.009 |
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".