Synthesis of a simply modified electrochemical nicotine sensor based on silver nanoparticles
Bibliographic record
Abstract
An innovative electrochemical nicotine modified sensor was created by chemically mixing a carbon paste with silver nano powder to prepare an Ag nanoparticle modified carbon paste electrode. Different electrochemical techniques including cyclic voltammetry, linear sweep voltammetry, and electrochemical impedance spectroscopy in both aqueous and micellar media were used. The surface morphology was also detected using scanning electron microscope and energy dispersive X-ray analysis techniques. Nicotine measurements were investigated in Britton–Robinson buffer solutions with a pH range of 2.0–8.0 containing 1.0 mmol/L sodium dodecyl sulfate. The electrode-based NIC sensor exhibited a high sensitivity in quantitative analysis, and its detection limit could be as low as 0.0036 μmol/L with linearity ranging from 0.8 μmol/L to 800 μmol/L. In addition, due to its good reproducibility, anti-interference performance, and long-term stability, the proposed sensor is capable of detecting trace levels of nicotine in urine samples and different brands of commercial cigarettes.
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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) | 0.001 | 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".