Algal fluorescence sensor integrated into a microfluidic chip for water pollutant detection
Bibliographic record
Abstract
We report the first miniaturized fluorescent sensor based on algae, with an organic light emitting diode (OLED) and an organic photodetector (OPD) integrated into a microfluidic chip. The blue emission OLED was used as the excitation source, while a blend of PTB3/PC(61)BM was used for the fabrication of the organic photodetector. Excitation and emission color filters based on acid/base dyes and a metal complex were developed and assembled with the organic optoelectronic components in order to complete the fluorescent detection system. The detection system was then integrated in a microfluidic chip made from (poly)dimethylsiloxane (PDMS). The complete sensor is designed to detect algal fluorescence in the microfluidic chamber. Algal chlorophyll fluorescence enables evaluation of the toxicity of pollutants like herbicides and metals-ions from agricultural run-offs. The entirely organic bioassay here presented allowed detection of the toxic effects of the herbicide Diuron on Chlamydomonas reinhardtii green algae that gave 50% inhibition of the algae photochemistry (EC(50)) with a concentration as low as 11 nM.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".