Synthesis of silicon nanowires from carbothermic reduction of silica fume in RF thermal plasma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Silica fume, which is a by‐product of metallurgical‐grade silicon production, is a low cost material with high SiO 2 concentration and small particle size (<1 µm). These properties make it a good candidate for radio‐frequency (RF) thermal plasma processing. In this article, the use of silica fume as a reactant is promoted for the RF thermal plasma synthesis of high‐charge capacity, high cyclability anode materials for lithium‐ion batteries. In order to obtain these materials, the carboreduction of silica fume is followed by an in‐flight growth of silicon nanowires in the plasma reactor. The impact of the addition of catalysts and the use of different plasma gases on the yield and the properties of the product has been investigated by X‐ray diffractometry (XRD), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), energy dispersion spectrometry (EDS), and transmission electron microscopy (TEM). It is found that the addition of metal catalysts has a significant effect on the synthesis. It not only promoted the formation of silicon nanowires, but also improved the yield of the reaction upwards of 300%. An insight on the mechanisms leading to the silicon nanowires formation is also discussed in the results section.
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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 it