The effect of photonic crystal fibre structure on the performance of Mach-Zehnder interferometer fibre optic gas sensors
Bibliographic record
Abstract
A compact refractive index (RI) sensor, based on the Mach-Zehnder Interferometer (MZI), has been developed and experimentally evaluated for the highly sensitive detection and quantification of gases (Helium, Methane, and Carbon Dioxide). The RI sensor utilizes a variety of fibre types: Single Mode Fibre (SMF), Photonic Crystal Fibre (PCF), and Hollow-Core Photonic Crystal Fibre (HC-PCF). In order to fabricate the MZI sensors, a short length of sensing fibre was positioned between a lead-in and a lead-out single mode fibre (SMF) with an air gap at each interface. Three types of sensors were fabricated using this configuration employing 4 mm stub of: (i) PCF, (ii) 10 µm HC-PCF, and (iii) 20 µm HC-PCF as the sensing elements. The performance of these sensors, for detecting and measuring the quantity of gas present, were compared. The transmission spectrum of MZI sensors are formed by interference between the cladding and core modes. These transmission signals correspond to the frequency components in the sensor’s Fast Fourier Transform (FFT) spectrum. The effect of gap distance on the number and amplitude distribution of the modes was examined in an effort to optimize the design elements. The resulting fiber sensors can measure the RI of a gas-filled cavity and they showed high-sensitivity to helium, methane, and carbon dioxide. The highest RI sensitivity of 3210 nm/RIU was demonstrated in the RI range of 1.0000347-to-1.000449 by a sensor with a 4 mm long sensing stub element of 10 µm HC-PCF. Cyclic tests with the group of gases demonstrated that the measurements are highly repeatable. The measurement response and recovery times for all sensors were determined, and it was concluded that the 20 µm HC-PCF sensor has the fastest response/recovery time and the PCF sensor has the slowest. This research illustrates that the sensors fabricated by the proposed method have potential for improving the ability to detect and quantify pure gases. Additionally, the sensors are highly sensitive to low percentages of CO2, making them suitable for greenhouse gas measurement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".