Redox-Controlled Ion-Pairing Association of Anionic Surfactant to Ferrocene-Terminated Self-Assembled Monolayers
Bibliographic record
Abstract
The redox-induced pairing from aqueous solution of a homologous series of sodium n-alkyl sulfate (NaCnSO4) surfactants of 6, 8, 10, and 12 carbons with gold-tethered self-assembled monolayers (SAMs) of ferrocenyldodecanethiolate (FcC12SAu) is investigated by cyclic voltammetry combined with surface plasmon resonance (SPR) spectroscopy. The adsorbed layer thicknesses and surface coverages are consistent with the formation of a monolayer of CnSO4(-) at the oxidized FcC12SAu SAM/aqueous solution interface. A comparison of the anodic charge density with the SPR data indicates that approximately 60% of the adsorbed surfactant anions are paired with SAM-bound ferroceniums, suggesting an interdigitated layer structure. The ion-pairing capabilities of the longer-chain NaC12SO4, NaC10SO4, and NaC8SO4 relative to the short-chain NaC6SO4 are compared using the relative ion-pair formation constants calculated from the apparent SAM redox potentials and IC50 values obtained from competitive association experiments. A longer alkyl chain increases the overall hydrophobicity of the CnSO4(-) anion, thereby increasing its ability to pair with and stabilize the ferrocenium in the nonpolar environment of the SAM. Binary mixtures of NaC12SO4 and NaC6SO4 of different compositions are used to demonstrate that the differences in ion-pairing abilities can be exploited to selectively pair and adsorb C12SO4(-).
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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".