Opto-Microfluidics for Monitoring Salinity and Temperature of Sea Water
Bibliographic record
Abstract
The success of ocean observation relies on effective monitoring technologies with increased functionalities, minimized size, and reduced cost, which can only be achieved through the development of new technologies.Opto-microfluidics has been increasingly recognized as powerful technologies to realize miniaturized devices for environmental monitoring, biological analyses, and chemical syntheses.By combining microfluidics and optics technologies, roomful laboratory equipment can be integrated into a palm-size chip with merits of versatile functionalities, compactness, minimized waste, and low cost.These opto-microfluidic systems are promising for applications in ocean observation.In this study, opto-microfluidic devices for monitoring salinity and temperature of liquids are proposed and demonstrated with ultrafast laser fabrication and two-photon polymerization techniques.By applying femtosecond lasers as powerful tools to achieve laser microfabrication with unprecedented high precision and quality, a Mach-Zehnder interferometer (MZI) has been fabricated and integrated into a microchannel as a miniaturized opto-microfluidic system.When saline solution or sea water is introduced to the microchannel, different phase shifts in the MZI can be resulted, which allow determination of the salinity and temperature of the solution from output optical spectra and intensities of the MZI corresponding to different phase shifts.The sensitivities of salinity and temperature have been found to be 215.744nm/RIU and 0.519 nm/ o C for the opto-microfluidic systems developed in this study, respectively.The results demonstrate the practicability of opto-microfluidic devices for real-time salinity and temperature monitoring of sea water in harsh environment.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".