Formation and stability of oil‐laden foam: Effect of surfactant and hydrocarbon solvent
Bibliographic record
Abstract
Abstract Oil‐laden (OL) foams could serve an important role in various processes, particularly in enhanced oil recovery; however, OL foams are less studied than aqueous foams. In this work, the formation and stability of OL foam, by either sodium dodecyl sulphate (SDS) or Triton X‐100 (TX‐100) in water‐pentane mixture, was evaluated. We first constructed a diagram of good and poor foaminess against pentane content in the mixture and aqueous surfactant concentration. It was shown that surfactant onset concentration for good foaming was increased with increasing pentane content. The result was fitted using a mathematical model that considers the surfactant dilution and adsorption effects by pentane. Foam height decay profiles were also monitored. Results indicated that SDS resulted in a more stable foam than TX‐100 at the same critical micelle concentration (CMC). Depending on surfactant concentration, OL foams exhibited strikingly different stability behaviours. Pentane acted as an anti‐foamer at surfactant concentrations at the CMC or lower. However, very high foam stability was displayed at high surfactant concentration (e.g., 3× CMC) and medium to high pentane contents; this is a result contradictory to the predication of entering, spreading, and bridging coefficients in the classic theory. The stable OL foams of this study could be attractive to potential foam applications.
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How this classification was reachedexpand
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 | 0.000 |
| 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 teacher head, 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".