Competitive Adsorption of Naphthenic Acids and Polyaromatic Molecules at a Toluene–Water Interface
Bibliographic record
Abstract
The early-stage competitive co-adsorption of interfacially active naphthenic acids (NAs) and polyaromatic (PA) molecules to a toluene-water interface from the bulk toluene phase was studied using molecular dynamics (MD) simulation. The NA molecules studied had the same polar functional group but different cycloaliphatic nonpolar tails, and a perylene bisimide (PBI)-based molecule was used as a representative PA compound. The results from our simulations suggest that the size and structural features of NA molecules greatly influence the interfacial activity of PA molecules and partitioning of NA molecules at the toluene-water interface. At low concentrations of PA (∼2.3 wt %) and NA (∼0.4 wt %) molecules, NA molecules containing large cycloaliphatic rings (e.g., four rings) or with a very long aliphatic tail (e.g., carbon chain length of 14) were observed to impede the migration of PA molecules to the interface, whereas small NA molecules containing two cycloaliphatic rings had little effect on the adsorption of PA molecules at the toluene-water interface. At high NA concentrations, the adsorption of PA molecules (∼5.75-17.25 wt %) was greatly hindered by the presence of small NA molecules (∼1.6-4.8 wt %) due to the solvation of PA nanoaggregates in the bulk. Adsorption mechanisms of PA and NA molecules at toluene-water interfaces were clarified through a detailed analysis on the interactions among different species in the system. The results obtained from this work provide insights into designing appropriate chemical demulsifiers or co-demulsifiers for breaking water-in-oil emulsions of great industrial applications.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".