Surface Chemistry of LiFePO[sub 4] Studied by Mossbauer and X-Ray Photoelectron Spectroscopy and Its Effect on Electrochemical Properties
Bibliographic record
Abstract
LiFePO 4 is a promising cathode material for lithium-ion batteries despite its low intrinsic electronic conductivity. We show, using a combination of Mössbauer, X-ray diffraction, and X-ray photoelectron spectroscopy (XPS), that conductive metal phosphides which enhance its electrochemical performance ( FeP , and metallic Fe 2 P ), are generated on the surface of the parent LiFePO 4 by reaction with in situ carbon from iron citrate and reducing gases such as hydrogen. Their relative fraction, nature, and location was quantified. Under the most mild reducing conditions, nanosized FeP is formed on the surface along with Li 3 PO 4 , and carbon resulting from the precursor. Under more aggressive reducing conditions, FeP is still present, but thermodynamics now favor the formation of Fe 2 P , with fractions varying from 4 to 18 wt % depending on the temperature and atmosphere used for treatment. Both large ( 0.5 μ m ) crystallites, and amorphous or nanodimensioned particles are present. XPS studies reveal that the amorphous or nanodimensioned Fe 2 P lies on the inner surface adjacent to the LiFePO 4 , and the residual carbon lies on the outer surface. The resulting LiFePO 4 “composites” show significantly enhanced electrochemical rate properties as well as outstanding cyclability, which allows a high discharge capacity of ∼ 105 mAh g − 1 at a 14.8C rate ( 2500 mA g − 1 ) .
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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) | 0.003 | 0.001 |
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".