Surface Modification Technologies for Space and Planetary Applications
Bibliographic record
Abstract
This paper presents an overview of processes developed in our company for applications in various space and planetary environments. A number of materials including polymers, paints and other organic-based materials undergo dramatic changes and irreversible degradation of physical and functional characteristics when exposed to space or planetary environments, like in LEO, GEO or on Moon, or Mars. Protective schemes including protective coatings, mechanical metal foil wrapping or cladding, specially synthesized bulk materials, etc. are used to reduce the effects of space environment on materials and their properties. However, the protection of polymers, paints and other organic-based materials in space still remains a major challenge, especially for future long duration exploration missions to other planets or permanent space stations or for an ever-growing array of nano-, micro- and macro-satellites in VLEO, LEO and GEO orbits. Surface modification processes and advanced coatings are used increasingly to protect existing or provide new properties to polymers, paints and other organic-based materials.A number of surface modification solutions that include treatment of the surfaces by chemical or physical processes and that differ from the traditional protective coating approaches were developed by ITL in the last 30 years that change the surface properties of treated materials, protecting them from the hazards of low Earth orbit (LEO) and Geostationary orbit (GEO) environments or providing dust mitigation properties when used in Lunar environment. Examples of their testing, characterization and applications are provided. In addition, a surface treatment process for mitigation of lunar dust effects in lunar environment was developed and will be discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".