Investigation of Li<sub>0.6</sub>FePO<sub>4</sub> Phase Separation Kinetics Starting from Solid Solution
Bibliographic record
Abstract
The major contribution of lithium ion batteries towards sustainable energy originates in their use as energy vectors. In this context, lithium iron phosphate represents a safe, stable and environmental benign cathode material. The phase transition process during charge and discharge leads to questions regarding reactions rates, as the deintercalation/intercalation process via a phase transition mechanism is expected to strongly affect ionic and electronic transport. In order to study intrinsic properties of partially lithiated lithium iron phosphate, this study reports on factors that affect the transformation of the metastable Li0.6FePO4 solid solution prepared using both physical and chemical means. The stability of the solid solution was examined using a series of diverse experimental conditions. Crystal structure effects were examined via X-ray diffraction (XRD) while more localized changes were revealed by attenuated total reflectance infrared spectroscopy (ATR-IR). Specifically, the internal vibrations of the phosphate group were used with the aim of detecting lithium rich and lithium poor phases. These two techniques corroborate to distinguish the metastable solid solution phase relative to the olivine and heterosite phases which emerge over time. Particles morphologies and size distribution were analysed by field-emission gun scanning electron microscopy (FEG-SEM) and dynamic light scattering (DLS) respectively. In addition, lithium content was confirmed by flame emission spectrometry (AES). The developed techniques and results relative to the solid solution metastability will serve as the basis for upcoming kinetics studies. These studies will rely on imposing a uniform reaction environment on the entire particle population, in contrast to kinetics derived from electrochemical analysis using composite 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) | 0.001 | 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".