Effect of water salinity and temperature on the hydrophobicity of ethylene propylene diene monomer insulator
Bibliographic record
Abstract
Ethylene propylene diene monomer (EPDM) is extensively used in outdoor composite polymer insulators. The effects of water salinity and temperature on the hydrophobicity of EPDM rubber were studied The hydrophobicity was determined by measuring the contact angle using a droplet of distilled water. The specimens were immersed in saline water solutions for up to 576 h. The salinity levels used were 5, 10/sup 3/, 10/sup 4/ and 10/sup 5/ /spl mu/S/cm. The aging temperatures were 0, 25, 50, 75 and 98/spl deg/C. The weight was also measured to determine the amount of water absorption in the polymer as might occur during a heavy rain. The change in the contact angle is related to the amount of water absorption, the salinity level of solution and the temperature. The absorption of saline water into the bulk is larger at higher temperatures and decreases with increasing salinity. At 25/spl deg/C and higher the absorption of saline water at all salinity levels was saturated during the aging period Generally, after long immersion the contact angle decreased. At 0/spl deg/C the decrease of contact angle was larger at higher salinity. At high temperatures (/spl ges/75/spl deg/C), the sample surface gradually changed its color from the original dark gray to white.
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 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 | 0.001 |
| 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".