Photothermally Induced Optical Property Changes of Poly(<i>N</i>-isopropylacrylamide) Microgel-Based Etalons
Bibliographic record
Abstract
Poly(N-isopropylacrylamide) microgel-based optical devices were designed such that they can be stimulated to change their optical properties in response to light produced by a light-emitting diode (LED). The devices were fabricated by sandwiching the synthesized microgels between two Cr/Au layers all supported on a glass coverslip with gold nanoparticles (AuNPs) deposited. Here, we found that these devices can be stimulated to change their optical properties when exposed to green LED light, which excites the AuNPs and increases the local temperature, causing the thermoresponsive microgels to decrease in diameter, resulting in a change in the devices' optical properties. We also found that the sensitivity of the devices to light was more pronounced as the environmental temperature approached the lower critical solution temperature (LCST) for the microgels, although the sensitivity of the devices to light exposure dropped off dramatically as the environmental temperature was increased above the LCST. This was a direct result of the microgels already being in their collapsed state and therefore unable to decrease in diameter any further due to light exposure. Finally, we found that the sensitivity of the devices to light exposure increased with increasing number of AuNP layers in the devices. We anticipate that these devices could be used for drug delivery applications; by using light to stimulate microgel collapse, the microgel-based devices can be stimulated to release small molecules on demand.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".