Reducing the Rate of Mn Dissolution in LiMn<sub>0.8</sub>Fe<sub>0.2</sub>PO<sub>4</sub>/Graphite Cells with Mixed Salt and Low Salt Molarity Electrolytes
Bibliographic record
Abstract
Li-ion cells using LiMnxFe1-xPO4 (LMFP) as the positive electrode can fail via Mn dissolution from the positive electrode and subsequent deposition on the negative electrode. Developing methods to reduce the amount of Mn on the negative electrode is critical for the commercialization of this material. Blends of LiPF6 and LiFSI salts are used in varying ratios, 5%, 30%, or 40% LiPF6, and at varying concentrations, 1.5, 1.0, or 0.5 M total salt to determine the impact of reducing salt concentration on the lifetime of LMFP/artificial graphite cells. Cycle life was improved for mixed salt cells compared to cells containing pure LiPF6, and cells containing low salt concentration electrolytes showed the best performance. Mn deposition on the negative electrode was quantified by X-ray fluorescence spectroscopy, which showed that lowering the salt concentration reduced the rate of Mn deposition per cycle on the negative electrode. Nuclear magnetic resonance spectroscopy showed that LiPF6 was preferentially consumed from the electrolyte during cycling.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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".