Solubilization of Naphthalene by Pure and Mixed Surfactants
Bibliographic record
Abstract
Surfactant-enhanced remediation technology has shown promising potential for removing residual organics from contaminated soils and groundwater. Using a homologous series of cationic surfactants, alkylpyridinium bromide, it was found that the molar solubilization ratio (MSR) for naphthalene decreases with decreasing carbon number in the hydrophobic tail. In contrast, with nonylphenyl ethoxylates (nonionic surfactants), the MSR for naphthalene does not show appreciable changes with varying number of ethylene oxide groups in the hydrophilic head. MSR values for naphthalene in the presence of ionic surfactants with similar tail length depend on the charge of the headgroup. In addition, the behavior of naphthalene solubilization using cationic−nonionic and anionic−nonionic surfactant mixtures deviates considerably from that of ideal mixing. More interestingly, however, results from batch and column experiments reveal that the interactions between surfactant molecules and sand surfaces, particularly surfactant adsorption, play a critical role in determining the organics removal efficiency from sand matrixes.
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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 | 0.001 | 0.001 |
| 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".