Magnetic demulsifier prepared by using one‐pot reaction and its performance for treating oily wastewater
Bibliographic record
Abstract
Abstract In this study, a magnetic demulsifier, called M‐DMEA, was prepared by “one‐pot” synthesis through the pyrolysis of ferric triacetylacetonate (Fe(acac)3) in DMEA 1231, which is a type of polyether demulsifier used in oil fields. The morphologies and phase compositions of the M‐DMEA nanoparticles were determined by transmission electron microscopy and X‐ray diffraction, respectively. The presence of surface coating was confirmed by using Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analyses (TGA). Magnetic property was measured by vibrating sample magnetometer. The demulsification of M‐DMEA for treating oily wastewater produced from polymer flooding (OWPF) was investigated. It was found that the oil removal of M‐DMEA reached 96.0 % at the concentration of 4.0 g/L. In addition, M‐DMEA can be recycled and reused by using an external magnet. The results showed that there was a significant decrease in the oil removal after two cycles because the polymer residue remaining in OPWF, namely partially hydrolyzed polyacrylamide (HPAM), was adsorbed onto the surface of M‐DMEA.
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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".