Study of the LiMn<sub>1.5</sub>Ni<sub>0.5</sub>O<sub>4</sub>/Electrolyte Interface at Room Temperature and 60°C
Bibliographic record
Abstract
The surface layer (Cathode-Electrolyte Interface; CEI) on LiMn1.5Ni0.5O4, a promising, high voltage positive electrode for Li-ion batteries, was studied by XPS, AC impedance spectroscopy and FTIR spectroscopy. Half cells and full cells with LiMn1.5Ni0.5O4as positive electrode material and Li4Ti5O12as a negative electrode material were assembled in conventional carbonate-based electrolytes with LiPF6or LiBF4as the salt, and the effect of cycling at different operating conditions (short and long storage time, state of charge and temperature) on the surface layer composition was assessed. Capacities reaching near the theoretical value of 140 mAh g−1were obtained in half cells cycled at C/2 and room temperature, with 85% of the capacity being retained after 100 cycles. Cycling at 60°C leads to a decrease in capacity and coulombic efficiency. The surface analysis by XPS revealed that the CEI is composed of inorganic species such as LiF and LixPFyOzor LixBFyOzas well as organic species such as polyethers and carbonates. Generally, it was found that cycling or storing the material at 60°C with an electrolyte using LiPF6as a salt yield more organic species and less LiF at the surface than the one with LiBF4.
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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) | 0.002 | 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".