Well‐Defined Pillararene‐Based Azobenzene Liquid Crystalline Photoresponsive Materials and Their Thin Films with Photomodulated Surfaces
Bibliographic record
Abstract
Photoresponsive materials (PRMs) have long been a hot topic and photo‐modulated smart surface is very appealing. Particularly, liquid crystalline PRMs are able to amplify and stabilize photoinduced orientation thanks to their self‐assembling and ordering characteristics. Herein, the first pillararene‐based azobenzene liquid crystalline PRM with well‐defined structure is presented, which can avoid the usually ill‐defined composition drawback of polymer PRMs and prevent the severe H‐aggregation from suppressing or even completely blocking photoresponse in simple azobenzene derivatives. The pillar[5]arene‐based macrocyclic azobenzenes with variant length spacers show wide temperature range smectic liquid crystalline mesophases and excellent film‐formation property. The tubular pillar[5]arene macrocyclic framework provides sufficient free volume for azobenzene moieties to achieve reversible photoisomerization and photoalignment; thus, their thin films demonstrate excellent light‐triggered modulation of surface free energy, wettability, and even photoalignment‐mediated orientation of an upper layer discotic liquid crystal columnar mesophase. Such pillararene‐based azobenzene liquid crystals represent novel and promising PRMs with extensive fascinating applications.
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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".