Produced Water Treatment by Micellar-Enhanced Ultrafiltration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A water treatment approach combining ultrafiltration (UF) and micellar-enhanced ultrafiltration (MEUF) techniques was used for the removal of organic contaminants in field produced water samples from Canada and the United States. Free oil droplets and suspended solids were separated by initial UF treatments while MEUF was necessary for the removal of dissolved organics. It was shown that the amphiphilic characteristics of some organics commonly existing in produced water contributed to lowering the critical micelle concentration (CMC) of the surfactant employed. Lower surfactant concentrations could, therefore, be employed leading to lower fouling and back contamination and higher permeate flux. In addition, the incorporation of organic contaminants into the structure of cetylpyridinium chloride (CPC) micelles resulted in larger size and higher dissolution capacity of the "mixed micelles". The performance of polymeric and ceramic membranes of different molecular weight cutoffs (MWCOs) was evaluated by analyzing the permeate flux, recovery ratio, and solute percent rejection as functions of trans-membrane pressure (TMP). A mathematical model based on Darcy's law and the resistance in-series model successfully described the flux decline as a function of TMP for the two field samples and the two membranes studied.
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.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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 it