Effect of Subphase Ions on Multilayer Deposition of an Anionic Gemini Surfactant on Solid Substrates
Bibliographic record
Abstract
ABSTRACT A recently reported anionic Gemini surfactant belonging to the “minimal linker” family has been shown to form closely packed crystalline monolayers at the air–water interface, like a simple fatty acid, but its ability to deposit onto solid substrates as multilayer films remains entirely unexplored. In this study, we have investigated multilayer deposition of this new surfactant, dubbed C 18 ‐0‐C 18 , onto solid substrates and explored the impact of various subphase cations, including Na + (aq) , Mg 2+ (aq) , and Zn 2+ (aq) on multilayer film formation. Multilayer deposition was assessed using a combination of approaches, including evaluation of surface pressure‐area isotherms, surface pressure kinetic stability, transfer ratio (TR) measurements, X‐ray Reflectivity (XRR), and Atomic Force Microscopy (AFM). Measurements of deposited films were further supported by measuring film structures directly at the air‐water interface using Brewster Angle Microscopy (BAM). TR, XRR, and AFM results indicated poor multilayer deposition from both a pure water and Mg 2+ enriched subphase, but effective multilayer formation from Zn 2+ and Na + subphases. The mechanism of multilayer deposition (or lack thereof) is discussed in the context of ion‐head group interactions and compared with results of film deposition from corresponding monomeric fatty acids described in the literature.
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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) | 0.001 | 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".