Principles and Applications of Nanoplasmonics in Biological and Chemical Sensing: A Review
Why this work is in the frame
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Bibliographic record
Abstract
Biosensing requires a highly sensitive real-time detection of the biomolecules. These properties are granted by nanoplasmonic sensing techniques. SPR-based optical sensors have evolved as a sensitive and versatile biosensing tool. A growing number of SPR-based sensing applications in the solution of clinical problems are reported in the recent years. This refers to the point that these sensors provide label-free detection of the living cells and non-destructive analysis techniques. In this study, we will review the mechanism of the detection in SPR biosensing, followed by the methods used to develop sensors to detect gases and the chemical, biological, and molecular interaction. The device sensitivity improvement based on plasmonic effects is also addressed in this study, and accordingly, the size and material dependence of the resonance frequency are discussed. The reviewed articles are categorized into three groups, depending on the SPR excitation configuration. In the first group of the sensors, the sensitivity of LSPR-based sensors in prism coupler configurations is reviewed. The second group, SPR excitation by optical fiber, slightly improved the sensitivity of the detections. The unique capability of the third group, photonic crystal fiber SPR sensors, in providing greatly improved sensitivity, generated a vast field of researches and applications in biosensing devices.
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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) | 0.001 | 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 it