Interphase Engineering for Stabilizing Ni‐Rich Cathode in Lithium‐Ion Batteries by a Nucleophilic Reaction‐Based Additive
Bibliographic record
Abstract
Abstract Ni‐rich cathode materials are considered promising candidates for next‐generation lithium‐ion batteries because of their high energy density and low cost. However, interphase failure at the surface of Ni‐rich cathodes negatively impacts cycling performance, making it challenging to meet the requirements of long‐term applications. In this study, a strategy is developed to improve interphase properties through introduction of a nucleophilic reaction‐based additive, using an appropriate amount of the inducer lithium isopropoxide (LIP) in the commercial electrolyte to achieve long‐term cycling stability of Li||LiNi0.83Co0.11Mn0.06O2 (NCM83) cells. This strategy enables Li||NCM83 cells to maintain a capacity of 148.7 mAh g−1 with a retention of 83.3 % even after 500 cycles. This outstanding cycling stability is attributed to a robust cathode‐electrolyte interphase (CEI) constructed on NCM83 surface LIP‐induce ring‐opening polymerization of ethylene carbonate (EC). As a result, the organic‐inorganic components of the CEI effectively constrain gas evolution and the corresponding phase transformation behavior. Furthermore, the CEI also suppresses microcrack formation and eventually sustains the Ni valence and coordination environment at high voltage.
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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".