Observations of Radiation‐Dominated Rapid Cooling of Structures Based on Carbon Nanotubes and Graphene
Bibliographic record
Abstract
It is often desirable to cause rapid thermal cycles in isolated systems, and it is convenient to do so by means of radiant heating and cooling. In principle, the rate of heating is arbitrarily increased simply by applying sufficient irradiance. This is not true for cooling, wherein the radiant emittance of a surface is determined by its emissivity and temperature. In an optically thin structure, the cooling rate is determined by the ratio of the material's emissivity to its specific heat, a factor that is expected to be greater in materials with a short characteristic absorption length, such as graphite. Herein, several forms of carbon‐based nanostructures, which have very short thermal radiation attenuation lengths, and are very robust and can withstand the high temperatures required for substantial Planckian thermal radiant emittance, are examined. Rapid cooling times ranging from about 100 μs to 1 ms are observed in structures cooling from a typical high temperature of 1500 K to a low of roughly half that value. Such rapid extreme thermal cycling of isolated materials provides new opportunities, for both research and potentially practical applications.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".