A Biosensing Platform Based on Metamaterials BioNEMS for Lab-on-Chip Systems
Why this work is in the frame
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Bibliographic record
Abstract
An optical nanoelectromechanical platform relied on a SRR metamaterial system is presented in this paper as a label-free biosensor. This structure includes a flexible BioNEMS (Bio-Nano-Electro-Mechanical Systems) transducer and a proposed SRR metamaterials for detection of biological changes. Metamaterial cells consist of two parts which are coupled with an air gap distance. A functionalized BioNEMS beam supports one part of the proposed metamaterial cells. When patient samples including target analytes is exposed to the NEMS beam surface, the specific bio-interactions are happened and the energy (surface stress type) is released on the surface. This energy, which is induced only to the one side of the movable beam, causes a differential surface stress and thus displaces the nanomechanical beam. As a result, the air distance between two separated cells of the metamaterial unit is changed. This leads to varying the cell coupling effect which excites plasmon modes in a different wavelength. Therefore, biological quantities can be measured by detecting the resonance wavelength changes. Moreover, analyzing the device by various approaches results its functional characteristics as follows: detection sensitivity of 4251 nm/RIU, figure of merit (FOM) of 500.1 RIU <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{-{1}}$ </tex-math></inline-formula> , mechanical 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">$1.4 \mu \text{m}$ </tex-math></inline-formula> /Nm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{-{1}}$ </tex-math></inline-formula> and resonant frequency of 17.1 kHz. Consequently, this mechanism is important for label-free biosensing due to its high potential for sensitive and quantitative detection of target analytes which leads to accurate diagnosis of diseases or identification of drugs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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