Hydrogel-coated structured packing for water separation from oily liquid streams
Bibliographic record
Abstract
This work presents an innovative water separation process using a packed modular bed to remove water from oily streams. This method involves filling the beds with structured packings created through additive manufacturing and coated with poly(acrylamide-co-sodium acrylate) hydrogels. The treatment was evaluated for water removal from naphthenic insulating oil (NIO) and marine diesel oil (MDO) streams. The hydrogel-coated structured packing was able to remove more than 90 % of the water from the oils and reduced their turbidity, going from a cloudy appearance to a clearer and brighter one. In industrial scenarios where water contamination occurs, the presence of hydrogel-coated packing allows for rapid water separation, offering significant advantages for industrial applications. The ease of oil percolation through hydrogel-filled beds makes this system attractive for a wide spectrum of applications, from industrial scales to deployment at refueling stations or as filters on board motor vehicles.
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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".