Structure and Reactivity of Mixed ω-Carboxyalkyl/Alkyl Monolayers on Silicon: ATR-FTIR Spectroscopy and Contact Angle Titration
Bibliographic record
Abstract
The structure, reactivity, and acid-base properties of mixed monolayers prepared by photochemical reaction of hydrogen-terminated silicon with mixtures of ethyl undecylenate and n-alkenes were studied by ATR-FTIR spectroscopy and contact-angle measurements. The surface composition of the mixed monolayers and its correlation with the hydrolysis reactivity of terminal ethoxycarbonyl (ester) groups were investigated by systematically varying the mole fraction of ethyl undecylenate and the chain length of the unsubstituted alkenes in the binary deposition solution. It has been shown that the mole fraction of ester groups on the surface deviates only slightly from the mole fraction of ethyl undecylenate in the solution. The efficiency of ester hydrolysis under acidic conditions is significantly influenced by the monolayer structure, i.e., the surface density of ester groups and length of the unsubstituted alkyl chains. In addition, we find that mixed omega-alkanoic acid/alkyl monolayers on silicon (prepared via hydrolysis) exhibit well-defined contact angle titration curves from which the surface acid dissociation constants were determined. The results were compared with the acid-base properties reported in the literature for carboxylic acid-terminated alkylsiloxane monolayers on hydroxylated silicon and for omega-mercaptoalkanoic acid/alkanethiolate monolayers on gold. The weak pKa dependence (deltapKa approximately 1) on the surface density of carboxylic acid groups and on the length of unsubstituted alkyl chains is attributed to variations of the microenvironment of the acid moieties. These experimental findings provide fundamental knowledge at the molecular level for the preparation of bioreactive surfaces of controlled reactivity on crystalline semiconductor substrates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".