Macromolecular Structure of Dodecyltrimethylammonium Chloride at the Silica/Water Interface Studied by Sum Frequency Generation Spectroscopy
Bibliographic record
Abstract
Adsorption of the cationic surfactant dodecyltrimethylammonium chloride at the silica/water interface was studied using sum frequency generation (SFG) spectroscopy under high ionic strength (100 mM NaCl) and at pH values ranging from 3 to 11, which are conditions relevant to hydraulic fracturing in enhanced oil recovery operations. At surfactant concentrations above the critical micelle concentration, SFG spectra of the CH stretching region indicate a more noncentrosymmetric structure for the surfactant aggregate is formed at the interface under acidic or basic conditions compared to neutral conditions. The SFG spectra also indicate a change in the packing/ordering of the surfactant hydrophobic tails with pH as well. In addition, the observed changes in the SFG spectra of water upon the addition of surfactant vary depending on the pH. At pH 7 and 11, the SFG intensity decreases in the OH stretching region, indicating a decrease in the magnitude of the electrostatic potential at the interface when the cationic surfactant is adsorbed at the negatively charged silica/water interface. At pH 3, an increase in the SFG intensity in the OH stretching region is attributed to an increase in the electrostatic potential at the silica/water interface due to the adsorption of a positively charged surfactant at a pH value close to the point of zero charge for the silica surface. These results demonstrate how the pH can influence the macromolecular structure of surfactants at mineral/water interfaces through the corresponding changes in the interfacial charge density and interfacial potential. In particular, we discuss how an unequal density of surfactants on each side of the interfacial bilayer or the adsorbed micelles may exist under either acidic or basic pH conditions.
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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 | 0.001 | 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".