Functionalized CVD monolayer graphene for label-free impedimetric biosensing
Why this work is in the frame
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Bibliographic record
Abstract
Recent advances in large area graphene growth have led to many applications in different areas. In the present study, chemical vapor deposited (CVD) monolayer graphene supported on glass substrate was examined as electrode material for electrochemical biosensing applications. We report a facile strategy for covalent functionalization of CVD monolayer graphene by electrochemical reduction of carboxyphenyl diazonium salt prepared in situ in acidic aqueous solution. The carboxyphenyl-modified graphene is characterized using Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM), as well as electrochemical impedance spectroscopy (EIS). We also show that the number of grafted carboxyphenyl groups on the graphene surface can be controlled by the number of cyclic voltammetry (CV) scans used for electrografting. We further present the fabrication and characterization of an immunosensor based on immobilization of ovalbumin antibody on the graphene surface after the activation of the grafted carboxylic groups via EDC/NHS chemistry. The binding between the surface-immobilized antibodies and ovalbumin was then monitored using Faradaic EIS in [Fe(CN)6]3−/4− solution. The percentage change of charge transfer resistance (R ct) after binding exhibited a linear dependence for ovalbumin concentrations ranging from 1.0 pg·mL−1 to 100 ng·mL−1, with a detection limit of 0.9 pg·mL−1. Our results indicate good sensitivity of the developed functionalized CVD graphene platform, paving the way for using CVD monolayer graphene in a variety of electrochemical 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 | 0.002 | 0.002 |
| 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