Understanding the Roles of Anionic Redox and Oxygen Release during Electrochemical Cycling of Lithium-Rich Layered Li<sub>4</sub>FeSbO<sub>6</sub>
Bibliographic record
Abstract
Li-rich oxides continue to be of immense interest as potential next generation Li-ion battery positive electrodes, and yet the role of oxygen during cycling is still poorly understood. Here, the complex electrochemical behavior of Li4FeSbO6 materials is studied thoroughly with a variety of methods. Herein, we show that oxygen release occurs at a distinct voltage plateau from the peroxo/superoxo formation making this material ideal for revealing new aspects of oxygen redox processes in Li-rich oxides. Moreover, we directly demonstrate the limited reversibility of the oxygenated species (O2(n-); n = 1, 2, 3) for the first time. We also find that during charge to 4.2 V iron is oxidized from +3 to an unusual +4 state with the concomitant formation of oxygenated species. Upon further charge to 5.0 V, an oxygen release process associated with the reduction of iron +4 to +3 is present, indicative of the reductive coupling mechanism between oxygen and metals previously reported. Thus, in full state of charge, lithium removal is fully compensated by oxygen only, as the iron and antimony are both very close to their pristine states. Besides, this charging step results in complex phase transformations that are ultimately destructive to the crystallinity of the material. Such findings again demonstrate the vital importance of fully understanding the behavior of oxygen in such systems. The consequences of these new aspects of the electrochemical behavior of lithium-rich oxides are discussed in detail.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".