Patterning Block Copolymer Aggregates via Langmuir−Blodgett Transfer to Microcontact-Printed Substrates
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Bibliographic record
Abstract
We demonstrate a new strategy for producing hierarchical polymer nanostructures, which combines nanoscale self-assembly of amphiphilic block copolymers at the air-water interface with microscale templated assembly of the resulting aggregates on chemically patterned substrates. Aggregates are formed via interfacial self-assembly of 141k polystyrene-b-poly(ethylene oxide) (PS-b-PEO, MW = 141k, 11.4 wt % PEO) or a blend of 185k PS-b-PEO (MW = 185k, 18.9 wt % PEO) and PS-coated CdS nanoparticles to form strandlike copolymer or copolymer-nanoparticle aggregates. Using Langmuir-Blodgett (LB) techniques, the aggregates are then transferred to patterned substrates possessing alternating hydrophilic/hydrophobic stripes, obtained by microcontact printing octadecyltrichlorosilane (OTS) on glass. The aggregates are transferred under various conditions of surface pressure, orientation of the patterned substrate, and withdrawal speed. Templated assembly of aggregates into the hydrophilic substrate domains is achieved when the hydrophilic/hydrophobic stripes are oriented perpendicular to the water surface during LB transfer; this is explained by surface energy heterogeneities along the subphase-substrate contact line, which induce selective dewetting and concomitant monolayer rearrangement at the drying front. In contrast, parallel orientation of stripes results in nonselective transfer of the monolayer without registration to the underlying surface pattern. By studying the effect of surface pressure, we show that packing constraints imposed by compression of aggregates to high surface densities prevent the formation of patterned LB films that match the established periodicity of the OTS-patterned glass. As well, it is shown that efficient transfer of aggregates to the patterned glass requires slower substrate withdrawal speeds compared to transfer to unpatterned hydrophilic glass.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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 it