Janus Microgels with Tunable Functionality, Polarity, and Optical Properties
Bibliographic record
Abstract
A facile self‐assembly method is presented to prepare poly(N‐isopropylacrylamide)‐based microgels modified anisotropically with gold nanoparticles (Au NPs) to yield Janus microgels. Transmission electron microscopy is used to confirm that microgels are selectively coated on one or both sides with Au NPs. This approach is able to generate microgels with the same (monopolar) or different (bipolar) charge on either side of the microgel surface. The optical properties of the Au NPs adsorbed to the microgel surface are also characterized as a function of temperature and pH. It is found that the plasmon absorption of the Au NPs depends on each, which can be explained by the microgel's solvation state dictating the distance between the Au NPs. The surface adsorption behavior of the monopolar and bipolar microgels is also investigated, and it is demonstrated that the bipolar microgels exhibit enhanced surface adsorption compared to the monopolar microgels. Finally, it is shown that the Janus microgel assembly can be controlled by modifying the Au NPs of at least two different sets of Janus microgels with complementary DNA sequences. The work here can find utility for generating surface adsorbed materials with controllable optical properties, sensors, and for studying fundamental behavior of self‐assembling 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) | 0.000 | 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 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".