A Long-Period Waveguide Grating Sensor for Accurate Simultaneous Detection of Dual Analytes
Bibliographic record
Abstract
To the best of our knowledge, we are the first to report the existence of two dispersion turning points (DTPs) in an optimized planar waveguide long-period grating (LPG) sensor for the lowest order cladding mode. Using numerical simulation, we investigate the potential of the sensor structure for bulk refractive index (RI) and surface sensing, with the goal of predicting its possible application as an integrated photonic biosensor. The proposed sensor exhibits an exceptionally high RI sensitivity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 7500$ </tex-math></inline-formula> nm/RIU ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 10$ </tex-math></inline-formula> 000 nm/RIU) near lower (higher) DTP. The surface sensitivity, which is incredibly high in this form of structure, is found to be 6.5 nm/nm (7 nm/nm) near lower (higher) DTP for the RI relevant for biosensing. Utilizing the sensing characteristics of both the DTP, we propose a dual-slot biosensor by cascading two LPGs having different grating periods. The proposed biosensor shows two independent dual-resonance phenomena and is, therefore, capable of simultaneous detection of dual analytes. Utilizing the proposed dual-slot biosensor, we present simulation results for specific detection of Hepatitis B antigen and deoxyribonucleic acid (DNA) hybridization simultaneously. The proposed biosensor will reduce the sensor cost as well as detection time, since a single source and detector are required to sense two different analytes at once.
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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) | 0.000 | 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 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".