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Record W4311511282 · doi:10.3389/fmats.2022.1013848

Review of the VO2 smart material applications with emphasis on its use for spacecraft thermal control

2022· article· en· W4311511282 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Materials · 2022
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsInstitut National de la Recherche ScientifiqueMPB Technologies & Communications (Canada)
Fundersnot available
KeywordsEmissivityMaterials scienceOptoelectronicsBlack-body radiationLow emissivitySpacecraftSemiconductorPhase transitionOpticsEngineering physicsAerospace engineeringPhysicsThermodynamicsEngineering

Abstract

fetched live from OpenAlex

It is surprising to see the wide range and versatile potential of applications of the VO 2 , 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 VO 2 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 VO 2 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.017
GPT teacher head0.241
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it