γ-Fe<sub>2</sub>O<sub>3</sub>@CNTs Anode Materials for Lithium Ion Batteries Investigated by Electron Energy Loss Spectroscopy
Bibliographic record
Abstract
Atomic layer deposition was employed to deposit maghemite (γ-Fe 2 O 3 ) nanoparticles on carbon nanotubes (CNTs) to prepare the γ-Fe 2 O 3 @CNTs composites, which exhibit a superior lithium storage performance as the anode of lithium ion batteries (LIBs). The high reversible capacity of 859.7 mA h/g was observed after 400 cycles at a current density of 500 mA/g. Even at the high current density of 10000 mA/g, the specific cyclic capacity of 464.4 mA h/g can still be obtained. Furthermore, electron energy loss spectroscopy results reveal that the Fe chemical state plays a critical role in the evolution of the capacity of γ-Fe 2 O 3 @CNTs composite anodes during the cycling process. The incomplete conversion of the chemical state in γ-Fe 2 O 3 reduces the capacity, while the recovery of the chemical state of γ-Fe 2 O 3 during the cycling process may cause the increase in capacity. This work provides insight into understanding the detailed working mechanism of transition metal oxides in LIBs, which helps in the design of electrode materials with promising lithium storage performance.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".