Adsorption of heptane–toluene binary mixtures on a hydrophobic polymer surface
Bibliographic record
Abstract
Polymer coatings offer a means to modulate the adsorption of molecules onto solid surfaces by offering a surface functionality, charge, roughness, and hydrophobicity that is different from the underlying substrate. One application is to provide anti-fouling functions for metal surfaces. Understanding solvent-surface interactions is an essential component to gaining mechanistic insight into the adsorption process. In this work, we study the adsorption of toluene-heptane binary mixtures onto a perflurorinated polymer surface. We use a combination of IR absorption and Raman scattering spectroscopy to study the mixture in the bulk phase, and surface-specific visible-infrared sum-frequency generation to probe the surface layers. Through the use of homo- and heterospectral two-dimensional correlation spectroscopy, we conclude that the adsorption of the two solvents is reversible and that the surface structure is generally independent of the surface composition, with a small change in toluene orientation as the toluene content increases. We also find that the hydrophobic fluropolymer has very little preference for either solvent, similar to previous studies on hydrophilic surfaces.
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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 | 0.000 |
| 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".