Evanescent-Field Excited Surface Plasmon-Enhanced U-Bent Fiber Probes Coated with Au and ZnO Nanoparticles for Humidity Detection
Bibliographic record
Abstract
We report the design, fabrication, and testing of a humidity sensor based on an optical fiber-based evanescent wave probe. The fiber was bent into a U-shape and de-cladded at the location of the bending. The de-cladded section was coated either with Au or with ZnO nanoparticles. Humidity is detected based on the interaction in the surface plasmon resonance of the Au/ZnO nanoparticles excited by an evanescent wave of light passing through the optical fiber. The response of the U-bent fibers to humidity was investigated using a specifically designed low-voltage portable interrogation box. We found that the fibers coated with ZnO nanoparticles were able to detect a minimum 0.1% change in humidity with an average sensitivity of 143 µV/%RH and 95% linearity over the 10% to 80% humidity range. In comparison, samples coated with Au and Au + ZnO nanoparticles demonstrated a minimum change detection of 0.3% RH and 2% RH respectively. The response and recovery time of the sensor were measured to be 3 s and 4 s, respectively, for a 60% change in humidity from 20% to 80%. The entire measurement system was operated by consuming an electrical power of 1.62 W at an input voltage of 12 Vdc.
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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 | 0.000 | 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 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".