An Experimental and Theoretical Approach to Investigate the Effect of Chain Length on Aminothiol Adsorption and Assembly on Gold
Bibliographic record
Abstract
Despite the numerous studies on the self-assembled monolayers (SAMs) of alkylthiols on gold, the mechanisms involved, especially the nature and influence of the thiol-gold interface are still under debate. In this work the adsorption of aminothiols on Au(111) surfaces has been studied by using surface IR and X-ray photoelectron spectroscopy (XPS) as well as by density functional theory (DFT) modeling. Two aminothiols were used, cysteamine (CEA) and mercaptoundecylamine (MUAM), which contain two and eleven carbon atoms, respectively. By combining experimental and theoretical methods, it was possible to draw a molecular picture of the thiol-gold interface. The long-chain aminothiol produced better ordered SAMs, but, interestingly, the XPS data showed different sulfur binding environments depending on the alkyl chain length; an additional peak at low binding energy was observed upon CEA adsorption, which indicates the presence of sulfur in a different environment. DFT modeling showed that the positions of the sulfur atoms in the SAMs on gold with similar unit cells [(2√3×2√3)R30°] depended on the length of the alkyl chain. Short-chain alkylthiol SAMs were adsorbed more strongly than long-chain thiol SAMs and were shown to induce surface reconstruction by extracting atoms from the surface, possibly forming adatom/vacancy combinations that lead to the additional XPS peak. In the case of short alkylthiols, the thiol-gold interface governs the layer, CEA adsorbs strongly, and the mechanism is closer to single-molecule adsorption than self-assembly, whereas for long chains, interactions between alkyl chains drive the system to self-assembly, leading to a higher level of SAM organization and restricting the influence of the sulfur-gold interface.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".