The critical role of interfaces in advanced Li-ion battery technology: A comprehensive review
Bibliographic record
Abstract
The passivation layer in lithium-ion batteries (LIBs), commonly known as the Solid Electrolyte Interphase (SEI) layer, is crucial for their functionality and longevity. This layer forms on the anode during initial charging to avoid ongoing electrolyte decomposition and stabilize the anode-electrolyte interface. However, repeated charging and discharging can destabilize the SEI, thereby increasing internal resistance and reducing capacity. Similarly, the Cathode Electrolyte Interphase (CEI) layer is crucial for the performance, safety, and durability of LIBs. The formation, stability, and evolution of the SEI and CEI layers are critical for the efficiency and lifespan of LIBs. Research has focused on optimizing these interphases through advanced materials , interface modifications, and improved electrolyte formulations. Enhancing our understanding of SEI and CEI formation and degradation can lead to significant advancements in LIB performance, lifespan, and safety, thereby satisfying the demands for high-performance power storage in electronic appliances and electric vehicles. Future innovations promise to improve energy density , charge-discharge efficiency, and overall battery reliability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".