Comparison of the Responsivity of Solution-Suspended and Surface-Bound Poly(<i>N</i>-isopropylacrylamide)-Based Microgels for Sensing Applications
Bibliographic record
Abstract
In this submission, the phase transition behavior for poly( N -isopropylacrylamide- co -acrylic acid) (pNIPAm- co -AAc) microgels and their assemblies was investigated as a function of temperature and pH using UV–vis spectroscopy (to probe light scattering behavior) and quartz crystal microbalance with dissipation (QCM-D) measurements. PNIPAm- co -AAc microgels were “painted” onto Au-coated glass substrates (for UV–vis) and the Au electrode of a QCM crystal to generate monolayers. The subsequent deposition of another Au layer on top of the pNIPAm- co -AAc microgel layer yields what is known as an etalon. UV–vis/QCM-D measurements revealed that the temperature and pH responsivities for the microgel assemblies match well with their solution behavior. UV–vis spectroscopy shows that the transmittance of the microgel monolayers decreased with increasing solution temperature at pH 3.0. At pH 6.5, the AAc groups in the microgels were deprotonated, leading to strong Coulombic repulsive forces inside the microgels that prevented their collapse and lead to minimal change in the transmitted light intensity. However, QCM-D analysis reveals more complex behavior as it is sensitive to the viscosity/viscoelasticity and thickness changes of the microgel layer, which ultimately depends on the microgel chemical composition and the interaction of the etalon’s Au layer with the crystal. The maximum sensitivity to temperature is 0.8 × 10 –3 °C·Hz –1, which is the most sensitive pNIPAm microgel-based QCM temperature sensor thus far reported in the literature. Finally, we exploit this new understanding to characterize the pH and ionic strength of a solution using pNIPAm- co -XAAc microgel-based etalon coated crystals. The research results and the sensing demonstration can inspire new and improved sensor designs for a variety of analytes.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".