Transforming silicon slag into high‐capacity anode material for lithium‐ion batteries
Bibliographic record
Abstract
Abstract The conception of cheaper and greener electrode materials is critical for lithium (Li)‐ion battery manufacturers. In this study, a by‐product of the carbothermic reduction of SiO2 to Si, containing 65 wt% Si, 31 wt% SiC, and 4 wt% C, is evaluated as raw material for the production of high‐capacity anodes for Li‐ion batteries. After 20 h of high‐energy ball milling, C is fully converted to SiC and a micrometric powder (D50 ∼1 μm) is obtained in which submicrometric SiC inclusions are embedded in a nanocrystalline/amorphous Si matrix. This material is able to maintain a capacity >1000 mAh g−1 (>3 mAh cm−2) over 100 cycles. No crystalline Li15Si4 phase is formed upon cycling as shown from the differential dQ/dV curves. The good mechanical resiliency of the electrode is evidenced by monitoring its morphological changes from sequential focused ion beam scanning electron microscopy analyses. However, a progressive and irreversible increase in the electrode mass and thickness is observed over cycling (reaching 125% and 60% after 200 cycles, respectively), which is mainly attributed to the accumulation of solid electrolyte interphase products in the electrode.
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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".