Multilayer Tuneable Emittance Coatings with Low Solar Absorptance for Improved Smart Thermal Control in Space Applications
Bibliographic record
Abstract
MPB has developed advanced technologies based on smart radiator thin-film tiles (SRTs) employing V1−x−yMxNyOn, for the passive dynamic thermal control of space structures and payloads. The SRT has passed successfully the major ground tests and validated its performance for extended use in the harsh space environment, with a target of up to 15 years GEO, in preparation for a flight demonstration of this technology This paper describes the optimization of MPB's smart radiator and its validation of an efficient thermal control with the tuneability of thermo-optical properties. The thermal control of satellites is a critical subsystem that impacts on the performance and longevity of space payloads. MPB has developed advanced smart radiator devices (SRDs) for passive, dynamic thermal control of space structures and payload. The SRDs employ a nano-engineered, thin-film structure based on V1−x−yMxNyOn. Dopants, M and N, tailor the transition temperature of the IR emittance. Preliminary ground testing of the SRD tiles and assembly was completed. The objectives of the tests are to demonstrate that the VO2 based thin film SRD can withstand the space environment of a GEO Satellite, with a lifetime of 15 years (including the harsh launch conditions), towards its validation as an efficient thermal control device for space applications. A set of environmental tests was performed in order to validate the coating resistance and performance stability in space for a single layer SRD, including extended thermal cycling and thermal shock testing. This layer demonstrated good emittance tuneability (Δε), however, the single layer can exhibit a relatively high solar absorptance (α) at the larger thicknesses needed for a high Δε. Recently MPB developed a multilayer thin-film structure to decrease the net solar absorptance (α), while maintaining high emittance tuneability. The approach uses a relatively simple thin dielectric stack selective reflector based on SiO2 (e.g. SiO2(λ/4)/VO2 (λ/4) to provide peak reflectance at λ=500 nm, the spectral position of the peak solar AM0 radiation. However depositing each of these additional layers may interfere with the original properties of the lower layers, changing their residual stresses and morphology. This is the main challenge for all the technologies based on multilayer thin or thick films proposed as tuneable emittance devices. MPB demonstrated the feasibility of reducing the net solar absorptance, without any significant decrease of the emittance tuneability. Six samples based on a three-layer structure on Al (Substrate Al/VO2/SiO2(λ/4)/VO2(λ/4)) were studied. The best sample obtained has an emittance tuneability (Δε) of 0.36 (e-low = 0.38, e-high = 0.74), and a solar absorptance of 0.32. Thermal vacuum cycling (up to 4000 cycles) and thermal shock test (17 cycles between Liquid Nitrogen and 165°C) validated the stability of the emittance tuneability and solar absorptance.
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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) | 0.002 | 0.001 |
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".