Strands, Networks, and Continents from Polystyrene Dewetting at the Air−Water Interface: Implications for Amphiphilic Block Copolymer Self-Assembly
Bibliographic record
Abstract
We demonstrate that nanoscale aggregates similar to those formed via amphiphilic block copolymer self-assembly at the air-water interface, including strands, networks, and continents, can be generated by the simple spreading of PS homopolymer solutions on water. Two different PS homopolymers of different molecular weight (PS-405k, M(n) = 405 000 g mol(-1) and PS-33k, M(n) = 33 000 g mol(-1)) are spread at the air-water interface at various spreading concentrations ranging from 0.25 to 3.0 mg/mL. Aggregate formation is driven by PS dewetting from water as the spreading solvent evaporates. We propose that a high spreading concentration or a high molecular weight lead to chain entanglements that restrict macromolecular mobility in the solution, enabling the kinetic trapping of nanostructures associated with early and intermediate stages of PS dewetting. Comparison of PS-405k with a mainly hydrophobic PS-b-PEO block copolymer of similar molecular weight (PSEO-392k, M(n) = 392 000 g mol(-1), 2.0 wt % PEO) allows the effect of a relatively short surface active block on aggregate formation to be investigated. We show that whereas the PEO block is not a required component for the formation of strands and other nonglobular aggregates, it does increase the number of these aggregates at a given spreading concentration and decreases the minimum spreading concentration at which these aggregates are observed, along with decreasing the dimensions and polydispersity of specific surface features. The results provide supporting evidence for the role of PS dewetting in the generation of multiple PS-b-PEO aggregate morphologies at the air-water interface, as originally described in earlier paper from our group.
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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) | 0.000 | 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 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".