Fast‐Charging Halide‐Based All‐Solid‐State Batteries by Manipulation of Current Collector Interface
Bibliographic record
Abstract
Abstract Poor rate capability is a significant obstacle for the practical application of inorganic all‐solid‐state lithium‐ion batteries (ASSLIBs). The charge transfer kinetics at the interface of current collectors is crucial for high‐rate capacity, but is typically neglected. In this paper, the interfacial evolution between Al foil current collectors and composite cathodes is studied in the LiCoO2/Li3InCl6 (LCO/LIC) ASSLIBs at both 25 and −10 °C. The results indicate that the side reactions between Al foil and LIC are the main challenges for the interfacial stability of current collector at 25 °C. The design of a graphene‐like carbon (GLC) coating for the modification of Al avoids side reactions at the interface of current collector, resulting in improved cycling stability and high‐rate capacity. GLC Al ASSLIB exhibits a high initial capacity of 102.9 mAh g–1 with a capacity retention of 89.1% after 150 cycles at 1 C. A high‐rate capacity of 69 mAh g–1 is also achieved at 5 C. At −10 °C, the low Li+/electron transfer kinetics along with side reactions is the key limitation for the rate capability. Thanks to the GLC coating, the improved electrochemical performance is achieved with the enhanced charge transfer kinetics at the interface of current collector.
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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".