Evolution of Spinel LiMn<sub>2</sub>O<sub>4</sub> Single Crystal Morphology Induced by the Li<sub>2</sub>MnO<sub>3</sub> Phase during Sintering
Bibliographic record
Abstract
The most severe problems for adoption of LiMn 2 O 4 (LMO) as a low-cost and sustainable cathode in lithium-ion batteries are manganese dissolution and structural degradation, especially at an elevated temperature. Developing large single crystals (SCs) for LMO could be a feasible solution since it significantly reduces electrode/electrolyte interfaces where degradation can occur, while exceptionally high ionic diffusivity of its spinel structure could guarantee decent kinetics. In this work, we discovered a unique correlation between morphology and synthesis conditions, especially oxygen partial pressure in a successful development of defect-free faceted LMO SCs. Further experimental and theoretical studies identified that crystal growth of spinel LMO can be dramatically promoted by the Li 2 MnO 3 impurity, which is spontaneously generated at low oxygen partial pressure during high temperature synthesis. Meanwhile, electrochemical performances were found to be controlled by both impurity and crystallite size. We believe that with more understanding of synthesis parameters, LMO single crystals could achieve optimal electrochemical performance.
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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) | 0.000 | 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".