Sandwich-structured nanoparticles-grafted functionalized graphene based 3D nanocomposites for high-performance biosensors to detect ascorbic acid biomolecule
Bibliographic record
Abstract
We present a highly sensitive and selective nano-biosensor for rapid, stable and highly reproducible detection of ascorbic acid (AA) in the presence of dopamine, uric acid and other interferences by a three-layer sandwich arrangement of nitrogen-doped functionalized graphene (NFG), silver nanoparticles (AgNPs) and nanostructured polyaniline (PANI) nanocomposite. The enhanced AA electrochemical properties of the NFG/AgNPs/PANI electrode is attributed to the superior conductivity of the NFG-PANI and the excellent catalytic activity of AgNPs. The critical modification of the AgNPs-grafted NFG-PANI coated on very low-cost fluorine doped tin oxide electrode (FTOE) increased the charge transfer conductivity of the electrode (the resistance drops down from 11,000 Ω to 6 Ω). The nano-biosensor was used to accurately detect AA in vitamin C tablets with the recovery of 98%. The sensor demonstrated a low detection limit of 8 µM (S/N = 3) with a very wide linear detection range of 10-11,460 µM, good reproducibility and excellent selectivity performance for AA detection. The results demonstrate that this nanocomposite is a promising candidate for rapid and selective detection of AA in practical clinical samples.
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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 | 0.001 |
| 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 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".