Athermal and Soft Multi‐Nanopatterning of Azopolymers: Phototunable Mechanical Properties
Bibliographic record
Abstract
Abstract Imprinting nanopatterns on flexible substrates has diverse applications in advanced fabrication. However, the traditional thermal nanoimprint lithography (T‐NIL) often causes shrinkage upon cooling. Here, a simple yet versatile method is introduced to fabricate multiple nanopatterns on a flexible substrate coated with an azopolymer by combining athermal nanoimprint lithography (AT‐NIL) and photolithography. The azopolymer has various mechanical properties upon photoirradiation: 1) phototunable glass‐transition temperatures ( T g ) and concomitantly photoinduced switch from glassy plastic to viscoplastic polymer; 2) prominent modulation of viscoplasticity under light illumination at different wavelengths. Regionally selective multiple nanopatterns are conveniently fabricated, presenting angle‐dependent structural color images on poly(ethylene terephthalate) (PET) substrates. The flexible, athermal and multiple nanopatterning method has the potential for on‐demand fabrication of complex nanopatterns.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".