Surface Doping to Enhance Structural Integrity and Performance of Li‐Rich Layered Oxide
Bibliographic record
Abstract
Abstract The Li‐rich layer‐structured oxides are regarded as one of the most promising cathode materials for their high energy density but suffer from severe problems such as capacity fading, poor rate performance, and continuous potential dropping. These issues are addressed here by surface doping of niobium (Nb) and other heavy ions in a Li‐rich Mn‐based layered oxide, Li 1.2 Mn 0.54 Ni 0.13 Co 0.13 O 2 . The doped ions are verified to be located in the Li‐layer near the oxide surface; they bind the slabs via the strong NbO bonds and “inactivate” the surface oxygen, enhancing the structural stability. The specific capacity of the modified oxide reaches 320 mAh g −1 in the initial cycle, 94.5% of which remains after 100 cycles. More importantly, the average discharge potential drops only by 136 mV in this process. The findings of this study illustrate the importance of inactivating the surface oxygen in suppressing the cation mixing in the bulk, providing an effective strategy for designing high‐performance Li‐rich cathode materials.
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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".