Adsorption of Non-ionic Surfactants onto Sand and Its Importance in Naphthalene Removal
Bibliographic record
Abstract
The kinetic and equilibrium adsorption studies of four NP (nonylphenyl ethoxylates) series non-ionic surfactants with different EO (ethylene oxide) groups on sand are presented here. The adsorption behavior of a NP series of surfactants is compared in batch and continuous column studies. The adsorption isotherms are found to be similar in nature in all cases, and the maximum amount adsorbed per gram of sand decreases with an increasing number of EO groups. The comparison of maximum amounts adsorbed in the batch and column shows that the amount adsorbed is the same for both cases. When two surfactants were mixed with a calculated average EO number, the mixed solution showed the same equilibrium amount adsorbed to that of the actual EO number, although transportation through the column showed different behavior. The organic removal efficiency of the surfactants from a sand column depends on the adsorption density on the sand surface and the lowering of the surface tension at the air−water interface. The order of naphthalene removal efficiency of different NP surfactants from a sand column are NP-40 < NP-15 < NP-9. The main objective of this study is to improve the knowledge of surfactant adsorption and its importance in organic removal from the sand surface for the application of soil and groundwater remediation.
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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 | 0.001 |
| 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 | 0.000 |
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".