Binary Carbon Modification Promoting the Electrochemical Performance of Silicon Anode for Lithium‐Ion Batteries
Bibliographic record
Abstract
Abstract As the research on lithium‐ion battery cathode materials gradually breaks through the saturation, the anode materials for lithium‐ion batteries have received wide attention because of their promising future. Silicon electrodes, in particular, are attracting increasing attention. In this paper, the Si/G precursor was achieved by simple mechanical ball milling. Two silicon based composite electrode materials Si@TA and Si@TA‐G were synthesized by spontaneous polymerization of tannic acid on precursor surface in Tris buffer solution. For the poor electrical conductivity of silicon, graphite was added as a carbon source to avoid the direct contact between silicon and electrolyte during charge/discharge process by forming tannic acid coating on silicon surface.The Si@TA composites achieve a discharge specific capacity of 927.4 mAh g −1 at 100 mA g −1 current density after 50 cycles with a retention rate of 87.1 % while the reversible capacity of Si@TA‐G is 1249.8 mAh g −1 with a retention rate is 93.6 %. This unique composite method provides new insights into the modification of silicon anode materials.
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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".