Performance of alkali‐free natural petroleum sulfonates: Ultra‐low interfacial tension on oil/water interface
Bibliographic record
Abstract
Ultra‐low interfacial tension (IFT) is one of the most important conditions relating to surfactant flooding for enhanced oil recovery. In this paper, the dynamic interfacial tension (DIT) of an alkali‐free petroleum sulfonate surfactant was studied with the spinning drop method aimed at the Daqing oil/water system. The effects of various experimental conditions, such as surfactant concentration, inorganic salt concentration, polar organic compounds, oil‐soluble sulfonates, and time stability were investigated. It was shown that the aqueous phase has little effect on DIT. The high molecular weight petroleum sulfonates play an important role in the lowering of oil/water IFT. The non‐uniform changes of the oil droplets in DIT measurements were also discussed from the aspects of petroleum sulfonate composition and diffusion rate. The increase of aqueous phase viscosity could only ease the rebound phenomenon, while the increase of heavy components of petroleum sulfonates could both eliminate the non‐uniform changes of the oil droplets and reduce the values of the IFT. These results may be helpful in explaining the reasons behind producing ultra‐low interfacial tension and the preparation of formulations for practical applications.
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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".