Zipper-like linker self-assembly to obtain low interfacial tensions with partially neutralized naphthenic acids.
Bibliographic record
Abstract
The presence of naphthenic acid in crude oil is considered one of the most important factors in the formation and stabilization of water in bitumen emulsions. While naphthenic acids (NAs) are oil-soluble lipophilic amphiphiles, their neutralized form, sodium naphthenates (NaNs), has highly hydrophilic components. The right NA/NaN proportion should produce a balanced, net-zero curvature at the oil-water interface, leading to ultra-low interfacial tensions (IFTs<0.1 mN/m). A previous study showed that such an expectation is not achievable in model oil systems with NA and NaN, likely because of the partition of NA and NaN species. This work explores the hypothesis that it is possible to achieve ultralow IFTs using surfactants with balanced hydrophilic-lipophilic interactions that can trigger a "zipper-like" self-assembly of hydrophilic and lipophilic amphiphiles at the interface. A second hypothesis is that by producing these ultralow IFTs one can achieve fast dewatering of emulsions of oil containing partially neutralized NAs. After introducing sodium dihexyl sulfosuccinate (SDHS) and sodium dioctyl sulfosuccinate (Aerosol OT or AOT) as balanced surfactants, it was noted that one could produce ultralow IFTs in partially neutralized NAs. Using the hydrophilic-lipophilic difference (HLD) and net-average curvature (NAC) framework, it was possible to reproduce the experimental trends when using appropriate values for the critical micelle concentration (CMC) for NaN and SDHS. The best zipper assembly performance was obtained when the intrinsic HLD of the balanced surfactant is near zero. Under those conditions, it was possible to find ultralow IFTs and fast dewatering of emulsions with NA content and pH relevant to diluted bitumen emulsions obtained during naphthenic froth treatment.
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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 | 0.001 |
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".