Formation Kinetics of Mixed Self-Assembled Monolayers of Alkanethiols on GaAs(100)
Bibliographic record
Abstract
We report on the formation kinetics of mixed self-assembled monolayers (SAMs) comprising 16-mercaptohexadecanoic acid (MHDA) and 11-mercapto-1-undecanol (MUDO) thiols on GaAs(100) substrates. These compounds were selected for their potential in constructing highly selective and efficient architectures for biosensing applications. The molecular composition and quality of one-compound and mixed SAMs were determined by the Fourier transform infrared absorption spectroscopy measurements. The formation of enhanced-quality mixed SAMs was investigated as a function of the molecular composition of the thiol mixture and the proportion of ethanol/water solvent used during their arrangement. Furthermore, the formation of mixed SAMs has been carried out by successive immersion of MHDA SAMs in MUDO thiol solutions and MUDO SAMs in MHDA thiol solution through the process involving thiol-thiol substitution. Our results, in addition to confirming that water-ethanol-based solvents improve the packing density of single thiol monolayers, demonstrate the attractive role of water-ethanol solvents in forming superior quality mixed SAMs.
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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".