Complexation of Surfactant/β‐Cyclodextrin to Inhibit Surfactant Adsorption onto Sand, Kaolin, and Shale for Applications in Enhanced Oil Recovery Processes. Part I: Static Adsorption Analysis
Bibliographic record
Abstract
Abstract Surfactant adsorption onto solid surfaces is a major issue during surfactant flooding in enhanced oil recovery applications; it decreases the effectiveness of the chemical injection making the process uneconomical. Therefore, it was hypothesized that the adsorption of surfactant onto solid surfaces could be inhibited using a surfactant delivery system based on the complexation between the hydrophobic tail of anionic surfactants and β‐cyclodextrin (β‐CD). Proton nuclear magnetic resonance spectroscopy was used to confirm the complexation of sodium dodecyl sulfate (SDS)/β‐CD. Surface tension analysis was used to establish the stoichiometry of the complexation and the binding constant ( K a ). Static adsorption testing was applied to determine the adsorption of surfactant onto different solids (sandstone, shale, and kaolinite). The release of the surfactant from the β‐CD cavity was qualitatively evaluated through bottle testing. The formation of the inclusion complex SDS/β‐CD with a 1:1 stoichiometry was confirmed. The K a of the complexations increases as salinity and hardness concentration increases. The encapsulation of the surfactant into the β‐CD cavity decreases the adsorption of surfactant onto solid surfaces up to 79 %. Qualitative observations indicate that in the presence of solid adsorbents partially saturated with crude oil, the β‐CD cavity releases surfactant molecules, which migrate towards the oil–water interface.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".