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Reducing the Specular Properties of Metalized Teflon Coverings on Canadian Mobile Servicing Station on the International Space Station

2021· article· en· W4200590378 on OpenAlexaffabout
Jacob I. Kleiman

Bibliographic record

VenueMechanics and Advanced Technologies · 2021
Typearticle
Languageen
FieldMaterials Science
TopicSilicone and Siloxane Chemistry
Canadian institutionsIntegrity Testing Laboratory (Canada)
Fundersnot available
KeywordsThermal emittanceMaterials scienceOpticsThermalSpace environmentComposite materialOptoelectronicsBeam (structure)Physics

Abstract

fetched live from OpenAlex

A surface modification process was developed for the metalized Teflon coverings used for thermal protection of electronic equipment on the International Space Station [1]. The developed modification process of Teflon surfaces reduced substantially the specularity of Ag-Inconel coated Teflon thermal control films by changing the morphological appearance of their surfaces by ion-beam texturing in a controlled manner from a metallic-like and shiny to complete milky, white appearance without significantly affecting the thermal optical properties. A number of space hardware units covered with the textured Silver-Teflon were exposed to the open space environment between June 2002 and June 2006 and delivered back to Earth at the end of 2006. Remarkable performance was demonstrated by the treated Ag/Teflon, with the solar absorptance and total emittance values and the α/ε ratio remaining very close to the original values as measured before the flights [2]. In an attempt to protect further the textured surfaces of Teflon from possible erosion by atomic oxygen and VUV in LEO environment, an additional novel surface modification process was developed that created an SixOyCzFn type of structure on the treated surface. The textured Teflon samples before and after surface treatments were tested in a space simulator facility under a combined atomic oxygen/vacuum ultraviolet exposure. A number of advanced characterization techniques were used to evaluate the properties of the modified films [3].

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.016
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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