A high capacity silicon–graphite composite as anode for lithium-ion batteries using low content amorphous silicon and compatible binders
Bibliographic record
Abstract
In this study, silicon–graphite composites were prepared and investigated as anode materials for Li-ion batteries with small amounts of silicon and different binders. The silicon powders were prepared by ball-milling crystalline silicon for 100 h and 200 h. After 200 h, an average silicon particle size of 0.73 μm was obtained and XRD measurements confirmed the formation of an amorphous powder embedded within nanocrystalline regions. XPS analysis of the silicon samples showed that silicon particles were covered with a native silicon oxide layer that grows during ball-milling. Battery cycling of the silicon powders in half cells showed that the powder ball milled for 200 h gave the lowest first-cycle irreversible capacity and the highest reversible capacity reaching over 500 mA h g−1 after 50 cycles at C/12. Composites were made using graphite and only 5 wt% silicon powders. The silicon was found to be uniformly dispersed into the composites as evidenced by X-ray mapping and SEM. When tested in half cells using different binders, it was found that the polyetherimide binder showed the highest capacity reaching 514 mA h g−1 after 350 cycles at C/12, which is 1.6 times greater than commercial graphite anode. High rate cycling showed good capacity retention reaching half the capacity at 5 C.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".