Roll‐to‐roll nanoimprint lithography of ultrafiltration membrane
Bibliographic record
Abstract
ABSTRACT Nanoimprinting of a commercial, as supplied, polyethersulfone ultrafiltration membrane has been carried out for the first time using a roll‐to‐roll (R2R) process. To support this processing approach, we also developed a reusable flexible polyetherimide mold. We were able to pattern membrane at room temperature (∼21 °C) due to the high pressures (22 MPa) applied during the low contact times (<2 s) inherent to R2R imprinting. N2 permeance (L m−2 h−1 bar−1) testing was used as an indicator to verify retention of membrane porosity and to guide selection of imprinting parameters during initial screening studies. Further measurements showed the N2 and (scaled) deionized water permeances to have a 0.97 correlation coefficient. We scaled up the size of patterned membranes to as large as 226 cm2 area, thereby demonstrating the plausibility of continuously patterning commercial ultrafiltration membranes. We also investigated pattern stability versus aqueous heat treatment and found that time, temperature, and imparted strain (during patterning) may all influence stability, but no evidence of pattern loss was observed in electron micrographs after our filtration experiments. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018, 135, 45993.
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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".