Long-Period Gratings and Microcavity In-Line Mach Zehnder Interferometers as Highly Sensitive Optical Fiber Platforms for Bacteria Sensing
Bibliographic record
Abstract
Selected optical fiber sensors offer extraordinary sensitivity to changes in external refractive (RI), which make them promising for label-free biosensing. In this work the most sensitive ones, namely long-period gratings working at (DTP-LPG) and micro-cavity in-line Mach-Zehnder interferometers (µIMZI) are discussed for application in bacteria sensing. We describe their working principles and RI sensitivity when operating in water environments, which is as high as 20,000 nm/RIU (Refractive index unit) for DTP-LPGs and 27,000 nm/RIU for µIMZIs. Special attention is paid to the methods to enhance the sensitivity by etching and nano-coatings. While the DTP-LPGs offer a greater interaction length and sensitivity to changes taking place at their surface, the µIMZIs are best suited for investigations of sub-nanoliter and picoliter volumes. The capabilities of both the platforms for bacteria sensing are presented and compared for strains of Escherichia coli, lipopolysaccharide E. coli, outer membrane proteins of E. coli, and Staphylococcus aureus. While DTP-LPGs have been more explored for bacteria detection in 102–106 Colony Forming Unit (CFU)/mL for S. aureus and 103–109 CFU/mL for E. coli, the µIMZIs reached 102–108 CFU/mL for E. coli and have a potential for becoming picoliter bacteria sensors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 | 0.001 |
| 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 teacher head, 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".