Accelerated Removal of Fe-Antisite Defects while Nanosizing Hydrothermal LiFePO<sub>4</sub> with Ca<sup>2+</sup>
Bibliographic record
Abstract
Based on neutron powder diffraction (NPD) and high angle annular dark field scanning transmission electron microscopy (HAADF-STEM), we show that calcium ions help eliminate the Fe-antisite defects by controlling the nucleation and evolution of the LiFePO4 particles during their hydrothermal synthesis. This Ca-regulated formation of LiFePO4 particles has an overwhelming impact on the removal of their iron antisite defects during the subsequent carbon-coating step since (i) almost all the Fe-antisite defects aggregate at the surface of the LiFePO4 crystal when the crystals are small enough and (ii) the concomitant increase of the surface area, which further exposes the Fe-antisite defects. Our results not only justify a low-cost, efficient and reliable hydrothermal synthesis method for LiFePO4 but also provide a promising alternative viewpoint on the mechanism controlling the nanosizing of LiFePO4, which leads to improved electrochemical performances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".