Development and Evaluations of a Polydimethylsiloxane Polyurethane Surface Engineered Sponge for Enhanced Emulsified Crude Oil Removal from Water
Bibliographic record
Abstract
Oil spills are environmentally hazardous because of the toxicity of chemical constituents. Cleaning emulsified crude oil has always been challenging. Adsorbent materials can be implemented to remove oil and toxins from oily water to reach Canadian standards before discharging to the environment. This work develops and evaluates a surface-engineered sponge (SEnS) with a PDMS-PU polymer blend coating. The PDMS concentration in the coating is optimized to reduce cost, and the highest single pass oil removal efficiency attained was 62%. Toxicology tests of Artemia brine shrimp provide researchers with a foundation of the decanting standard. The mortality rate decreased from 86% in starting emulsion to 13% in filtered water and down to 0% when diluted by 90% seawater. The operating environment was also investigated by modeling two diffusion models. The efficiency of PDMS-PU coating in removing oil droplets and toxins provides the potential for implementing SEnS into an oil-water-separation system.
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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) | 0.000 | 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 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".