Facile Fabrication of Flexible Polymeric Membranes with Micro and Nano Apertures over Large Areas
Bibliographic record
Abstract
Freestanding, flexible and open through-hole polymeric micro- and nanostructured membranes were successfully fabricated over large areas (>16 cm2) via solvent removal of sacrificial scaffolds filled with polymer resin by spontaneous capillary flow. Most of the polymeric membranes were obtained through a rapid UV curing processes via cationic or free radical UV polymerisation. Free standing microstructured membranes were fabricated across a range of curable polymer materials, including: EBECRYL3708 (radical UV polymerisation), CUVR1534 (cationic UV polymerisation) UV lacquer, fluorinated perfluoropolyether urethane methacrylate UV resin (MD700), optical adhesive UV resin with high refractive index (NOA84) and medical adhesive UV resin (1161-M). The present method was also extended to make a thermal set polydimethylsiloxane (PDMS) membranes. The pore sizes for the as-fabricated membranes ranged from 100 µm down to 200 nm and membrane thickness could be varied from 100 µm down to 10 µm. Aspect ratios as high as 16.7 were achieved for the 100 µm thick membranes for pore diameters of approximately 6 µm. Wide-area and uniform, open through-hole 30 µm thick membranes with 15 µm pore size were fabricated over 44 × 44 mm2 areas. As an application example, arrays of Au nanodots and Pd nanodots, as small as 130 nm, were deposited on Si substrates using a nanoaperture polymer through-hole membrane as a stencil.
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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".