Synthesis of Mg and Mn Doped LiCoO<sub>2</sub>and Effects on High Voltage Cycling
Bibliographic record
Abstract
LiCo 1-2x Mg x Mn x O 2 (0 ≤ x ≤ 0.05) materials were prepared from Co 1-2x Mg x Mn x (OH) 2 (0 ≤ x ≤ 0.05) co-precipitated precursor materials by mixing precursor materials with stoichiometric amounts of Li 2 CO 3 and heating to 900°C for 10 h. All precursor and lithiated materials were characterized by Scanning Electron Microscopy, X-ray Diffraction (XRD), Inductively Coupled Plasma – Optical Emissions Spectroscopy and electrochemical testing. In situ XRD was performed on LiCo 1-2x Mg x Mn x O 2 (x = 0, 0.02, 0.05) electrodes while cycling to study the effects of substitution on phase transitions and unit cell variations. Increasing Mg/Mn substitution in the material was found to slightly increase the 1 st charge capacity, decrease the 1 st discharge capacity and increase the 1 st cycle irreversible capacity (3.6 V–4.7 V). Cells with even 1% Mg/Mn doping were shown to have markedly improved cycling performance, and results suggest that the improvements stem from suppressing the cell impedance growth, not from the suppression of the O3-O6-O1 phase transitions. Differences between LiCoO 2 cells and LiCo 0.9 Mg 0.05 Mn 0.05 O 2 cells become significant at 4.5 V and above, where the LiCoO 2 cells underwent the O3-O6-O1 phase transitions and the LiCo 0.9 Mg 0.05 Mn 0.05 O 2 cells appeared to undergo oxygen loss but not this series of phase transitions.
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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".