Practical Application of Li-Rich Materials in Halide All-Solid-State Batteries and Interfacial Reactions between Cathodes and Electrolytes
Bibliographic record
Abstract
Benefiting from the advanced solid-state electrolytes (SSEs), conventional cathodes have been widely applied in all-solid-state lithium batteries (ASSLBs). However, Li-rich Mn-based (LRM) cathodes, which possess enhanced discharge capacities beyond 250 mA h g –1, have not yet been studied in ASSLBs. In this work, the practical application of LRM cathodes in ASSLBs using a high-voltage-stability halide SSE (Li 3 InCl 6, LIC) is reported for the first time. Furthermore, we decipher that the active oxygen released from LRM cathodes at a high operation voltage seriously oxidizes the LIC electrolytes, thus resulting in the large interfacial resistance between cathodes and electrolytes and hindering their industrialized application in ASSLBs. Therefore, surface chemistry engineering of LRM cathodes with an ionic conductive coating material of LiNbO 3 (LNO) is employed to stabilize the LRM/LIC interface. Consequently, the LRM-based ASSLBs deliver a high specific capacity of 221 mA h g –1 at 0.1 C and a decent cycle life of 100 cycles. This contribution gives insights into studying the interfacial issues between LRM cathodes and halide electrolytes and sheds light on the application of LRM cathode materials in ASSLBs.
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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 | 0.001 |
| 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".