Color‐shifting Crystalline Colloidal Arrays from Polymers With Upper Critical Solution Temperature
Bibliographic record
Abstract
Crystalline colloidal arrays (CCAs) composed of core-shell microspheres with thermoresponsive structural iridescence governed by Bragg's law have garnered significant attention for diverse applications. While core-shell microspheres with lower critical solution temperature (LCST) properties are extensively studied, upper critical solution temperature (UCST) counterparts remain unexplored, offering the potential to expand the application scope of thermoresponsive CCAs. In this study, poly(N-acryloyl glycinamide) (PNAGA), a UCST homopolymer, is employed for the first time to synthesize core-shell microspheres. By copolymerizing NAGA with the hydrophilic co-monomer acrylamide (AM) to form the shell, microspheres with soft shells capable of assembling into CCAs with bright iridescence are obtained. Owing to Bragg's law and the UCST properties of the shell, the diffraction wavelength of these CCAs depends on concentration, observation angle, and temperature. The CCAs exhibit thermoresponsive behavior, with a size transition temperature around 14°C. Upon heating, the shells swell, and the microspheres transition from a rigid to a soft state, leading to an increase in interparticle distance and enhanced stabilization of the ordered microsphere packing. This process results in a red shift and a significant increase in the intensity of the diffraction peak. The thermoresponsive properties of these CCAs highlight their potential as intelligent temperature-sensing materials.
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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".