Improving Rhodamine B Fluorescence Thermometry in PDMS Microchannels by Photobleaching Absorbed Dye
Bibliographic record
Abstract
A number of microfluidic applications require precise thermal control where in-channel temperature measurements are necessary during the prototyping stage. Rhodamine B based laser induced fluorescence is a common technique used to obtain high resolution measurement of the fluid temperature field. However, PDMS has a tendency to absorb small hydrophobic dyes, such as Rhodamine B, which results in a steady increase in the overall fluorescent signal. This increase in light intensity causes a significant problem that must be overcome to obtain reliable temperature measurements. In this work a simple technique is described to remove the fluorescent signal originating from absorbed Rhodamine B dye particles that does not require surface modification or any significant alterations to the experimental setup. Instead a high power light source is used to photobleach the particles prior to taking images for thermometry analysis. Herein we demonstrate the technique with a conventional fluorescence microscope and a 100W mercury arc lamp and study the temperature field at the intersection of a Y-channel PDMS/glass chip where hot and cold streams merge.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".