In Situ Polymerization of Molecular Macroclusters on a Silica Surface: Poly(<i>N</i>-isopropylacrylamide) Nanofilms
Bibliographic record
Abstract
We have found that alcohols, carboxylic acids, and amides self-assemble into a unique molecular architecture, a hydrogen-bonded molecular macrocluster, when they are selectively adsorbed onto silica (glass and oxidized silicon) surfaces in nonpolar solvents such as cyclohexane. In our previous study, this phenomenon could be successfully applied to fabricate molecularly flat and defect-free nanofilms of several tens of nanometers thickness. In this study, we prepared a poly(N-isopropylacrylamide) [poly(NIPAAm)] film on the basis of in situ polymerization of a monomer macrocluster layer formed on silica surfaces and investigated how the molecular arrangement of the adsorbed NIPAAm monomers affects the efficiency of the polymerization of them. Poly(NIPAAm) films were prepared by the following two methods: (1) the one-solution method, the in situ photopolymerization of an NIPAAm monomer adsorption layer on silica in one solution (chloroform, cyclohexane, and toluene), and (2) the solution exchange method, adsorption of NIPAAm monomers onto a silica surface from NIPAAm (0.1 mol %) in chloroform, exhange of the solution to 0.005 mol % NIPAAm in cyclohexane, and then polymerization by UV irradiation. By the solution exchange method, molecularly flat, defect-free, and thermoresponsive films were obtained and the thickness could be controlled by the irradiation time, while only several nanometers thickness could be attained by the one-solution method. The structure of NIPAAm adsorption layers formed in each solution condition was characterized by attenuated total reflection Fourier transform infrared spectroscopy. It was revealed that only the solution exchange procedure induced the beta-sheet-like adsorbed structure of NIPAAm in which the double bonds of neighboring NIPAAm monomers were closely located, which should have resulted in effective polymerization.
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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".