Review of the VO2 smart material applications with emphasis on its use for spacecraft thermal control
Bibliographic record
Abstract
It is surprising to see the wide range and versatile potential of applications of the VO2, due to its transition from a semiconductor phase at low temperature, to a metallic state at high temperature. Although this transition’s atomic mechanism is not yet well understood, the tuneability is very reproducible experimentally and can be monitored by various triggering schemes, not only by heating/cooling but also by applying a voltage, pressure, or high power single fast photonic pulse. Many of the recent applications use not only the low-temperature phase and the high-temperature phase, but also the transition slope to monitor a specific parameter. The paper starts with a summary of the VO2 thin film deposition methods and a table presenting its recent proposed applications, some of which our team had worked on. Then the development characterization and application of the VO2 as a smart thermal radiator is provided along with the recent progress. The experimental results of the emissivity were measured at low temperature and high temperature, as well as during the transition in vacuum based on the thermal power balance. These measurements were compared with those deduced from an average of Infrared Reflectance (2–30 µm) weighed with the blackbody reflection spectrum. The roadmap is to try alternatives of the multilayers in order to increase the emissivity tuneability, increase the device dimensions, have an easier application on space surfaces, while lowering cost.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".