Optofluidic Dissolved Oxygen Sensing With Sensitivity Enhancement Through Multiple Reflections
Bibliographic record
Abstract
The development of compact and low-cost dissolved oxygen (DO) sensors is essential for the continuous in situ monitoring of environmental water quality and wastewater treatment processes. The optical detection of dynamic and reversible quenching of fluorescent dyes by oxygen has been used for DO sensing. In this paper, we have optimized a multilayer optofluidic device based on the measurement of fluorescence quenching in a Ruthenium-based oxygen sensitive dye by employing total internal reflection (TIR) of the excitation light to achieve sensitivity enhancement for the detection of 0-20-ppm DO in water. The incident angles of light and sensitive layer thickness are optimized experimentally in order to increase the path length of light in the sensitive layer of the device through multiple reflections. A model is developed to demonstrate how light propagates through different layers of the device at varying angles of excitation and to describe the mechanism of fluorescence generation for each of the types of TIR observed. The design principles identified in this paper may be applied to the development and optimization of new multilayered optofluidic sensors by employing TIR for sensitivity enhancement.
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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 | 0.001 | 0.001 |
| 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 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".