BNNT coating of FBGs written in tapered optical fiber for hydrophilic gas sensing
Bibliographic record
Abstract
Fiber Bragg gratings (FBGs) were fabricated in tapered fibers using the plane-by-plane technique and a fs-IR laser. A thin layer of boron nitride nanotubes (BNNTs) was deposited onto the FBGs through a dip-coating process from a BNNT water solution. The reflection spectra of FBGs were then recorded when they were placed above the water solution of ammonia (NH3), hydrogen chloride (HCl) or liquid bromine (Br2) in an open cylinder container. It was demonstrated experimentally that, due to the thin BNNT coating, the returned losses of FBGs were increased when they were surrounded with such hydrophilic gas vapors, such as ammonia, bromine and hydrogen chloride. However, when the FBGs were in other atmospheres such as air, methanol and acetone vapors, no change of the FBG reflection spectra was observed. The results of this work indicates that BNNT coating on FBGs plays an important role for hydrophilic gas detection with high sensitivity and reusability due to their quick release of adsorbed gases. The proposed sensor has the capacity of multiparameter sensing and can be used in harsh environments.
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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".