Enhanced Electrochemical Properties of LiFePO<sub>4</sub> as Positive Electrode of Li-Ion Batteries for HEV Application
Bibliographic record
Abstract
LiFePO4 materials synthesized using FePO4(H2O)2 and Li2CO3 blend were optimized in view of their use as positive electrodes in Li-ion batteries for hybrid electric vehicles. A strict control of the structural properties was made by the combination of X-ray diffraction, FT-infrared spectroscopy and magnetometry. The impact of the ferromagnetic clus-ters (γ-Fe2O3 or Fe2P) on the electrochemical response was examined. The electrochemical performances of the opti-mized LiFePO4 powders investigated at 60℃ are excellent in terms of capacity retention (153 mAh·g-1 at 2C) as well as in terms of cycling life. No iron dissolution was observed after 200 charge-discharge cycles at 60℃ for cells containing Li foil, Li4Ti5O12, or graphite as negative electrodes.
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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".