Systematic evaluation of inorganic salts as a heat sink for the magnesiothermic reduction of silica
Bibliographic record
Abstract
In this study, the effectivity of a series of inorganic salts, sodium chloride, calcium chloride, magnesium chloride, potassium chloride, and sodium bromide as heat sinks during magnesiothermic reduction of silica to porous silicon was investigated. The salts were chosen based on cost, thermal stability, ability to remain chemically inert during the reduction process, and ease of removal after the reaction. The structural integrity of the spherical porous silicon nanoparticles was observed using scanning electron microscopy, the surface area was determined via nitrogen adsorption experiments, and the crystallite size was determined using powder X-ray diffraction analysis; together, these were used to determine the efficacy of each salt. The ability of a salt to act as an effective heat sink was found to be highly correlated and principally dependent on the heat capacity of the salt. Calcium chloride was found to be the most effective heat sink overall among the five heat sinks investigated here.
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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 | 0.001 | 0.001 |
| 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 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".