A Study of the Supramolecular Approach in Controlling Diblock Copolymer Nanopatterning and Nanoporosity on Surfaces
Bibliographic record
Abstract
Thin films of poly(styrene- b -4-vinylpyridine) (PS4VP) [ M n (PS) = 71.9 kg/mol; M n (P4VP) = 30.2 kg/mol] mixed with 1,5-dihydroxynaphthalene (DHN) were dip-coated onto flat substrates from THF solutions. The resultant nanostructures were characterized by AFM, TEM, infrared spectroscopy, contact angle measurements, and cyclic voltammetry. The DHN selectively enriches the P4VP domains through hydrogen bond complexation, giving relative block compositions that should result in lamellar morphology in the bulk. However, films dip-coated from solutions of variable DHN:4VP molar ratios self-assemble into a quasi-hexagonal array of nodules of P4VP + DHN protruding above a PS matrix. This morphology can be ascribed, at least in part, to greater solubility in THF of PS compared to P4VP. The solubility difference appears to be highest for equimolar DHN:4VP. The removal of DHN from the deposited films by rinsing with methanol creates regularly patterned nanoporous films. The geometric parameters of the nanopatterns before and after DHN removal depend on the DHN:4VP ratio. Electrochemical measurements indicate that the pores penetrate the methanol-rinsed films most deeply for those prepared using an initial DHN:4VP molar ratio of 4:1. It was estimated from these measurements that a P4VP layer of about 2 nm thick is located at the film−substrate interface, through which electron tunneling can occur.
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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".