Superhydrophobic Hierarchically Assembled Films of Diblock Copolymer Hollow Nanospheres and Nanotubes
Bibliographic record
Abstract
Reported are the formation of rough particulate films from cross-linked diblock copolymer vesicles and nanotubes and the wetting properties of the resultant films. The diblock copolymers used were F66M200 and F95A135, where the subscripts denote the repeat unit numbers, whereas M, A, and F denote poly(2-cinnamoyloxyethyl methacrylate), poly(2-cinnamoyloxyethyl acrylate), and poly(2,2,2-trifluoroethyl methacrylate), respectively. The precursory polymers to F66M200 and F95A135 were prepared by atom transfer radical polymerization. In 2,2,2-trifluoroethyl methacrylate (FEMA), a selective solvent for F, vesicles and tubular micelles were prepared from F66M200 and F95A135, respectively. Photo-cross-linking the M and A blocks of these aggregates yielded hollow nanospheres and nanotubes bearing F coronal chains. These particles were dispersed into CH2Cl2/methanol, where CH2Cl2 was a good solvent for both blocks and methanol was a poor solvent for F. Casting CH2Cl2/methanol dispersions of these particles yielded films consisting of hierarchically assembled diblock copolymer nanoparticles. For example, the hollow nanospheres fused into microspheres bearing nanobumps after being cast from CH2Cl2/methanol at methanol volume fractions of 30 and 50%. The roughness of these films increased as the methanol volume fraction increased. The films that were cast at high methanol contents were superhydrophobic, possessing water contact angles of ∼160° and water sliding angles of ∼3°.
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".