Recovery of Hydrophobicity of HTV Silicone Rubber after Accelerated Aging in Saline Solutions
Bibliographic record
Abstract
A study of the recovery of the hydrophobicity of high temperature vulcanized (HTV) silicone rubber (SIR) after immersion for 3000 h in saline solutions of different conductivities (0.005-100 mS/cm) and at different temperatures (0-98 °C) as a function of time (0 to 3000 h) is reported. The hydrophobicity characterized as the ability of the material to bead water is determined by measuring the static contact angle Θ between the tangent to the droplet of distilled water and the horizontal surface of the HTV SIR. After removal from the saline solution the recovery of the contact angle was determined at 22±3°C in air. The contact angle recovered from its lowest value of 15° after immersion in distilled water at 98°C for 3000 h to 100° after 3000 h of recovery. The percentage reduction in weight during recovery due to drying of the specimens at 22°C was determined. The surface roughness which affects the hydrophobicity was monitored during the recovery period. The changes in the weight and surface roughness of the specimens are correlated with the contact angle and hence with the recovery of the hydrophobicity of HTV SIR. The surface properties during recovery were examined using scanning electron microscopy (SEM), energy dispersive X-ray (EDS) spectroscopy and Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy.
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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) | 0.001 | 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 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".