Microgel-based etalon membranes: Characterization and properties
Why this work is in the frame
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Bibliographic record
Abstract
We introduce Microgel-based Etalon Membranes (MEMs), based on the combination of stimuli-responsive microgels with an etalon, which is an optical device consisting of two reflecting plates and is used to filter specific wavelengths of light. The microgels are sandwiched between two reflective layers and, in response to a stimulus (e.g., temperature, pH, or biomarker concentration), swell or de-swell, thereby changing the distance between the two reflective layers and generating multiple peaks in the reflectance spectra. This property gives a MEM the unique capability of simultaneous separation and tunable responses to environmental changes and/or biomarker concentrations. We propose a design based on gold layers on a silicon nitride wafer membrane. Our comprehensive characterization, employing permeability experiments, in situ optical reflectance spectroscopy, in-liquid atomic force microscopy (AFM) analysis, and captive bubble contact angle measurements, elucidates the dynamic response of MEM to pH, temperature, and glucose stimuli and the corresponding effect of microgel swelling/de-swelling on the membrane properties, e.g., permeability. The AFM results confirm the dynamic changes of the microgel layer’s thickness on the membrane surface in response to the stimuli. Although the microgel’s swelling/de-swelling influences the effective pore radius, the decrease in the membrane’s permeance is limited to less than 10%. In the swollen state of the microgels, the etalon membranes show a prominent hydrophilic behavior, while they become less hydrophilic in the microgels’ de-swollen state. This work introduces MEM and provides novel insights into their behavior. The fundamental understanding that we reveal opens the way to applications ranging from point-of-care testing to continuous environmental monitoring.
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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 | 0.000 | 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 it