Preparation and application of copper hydroxide (oxide) / multiwalled carbon nanotubes nanocomposite-modified glassy carbon electrode as a nitrite sensor
Bibliographic record
Abstract
Copper hydroxide (oxide) / multiwalled carbon nanotubes nanocomposite-modified glassy carbon electrode (Cuhydroxide/oxide/MWCNTs/GCE) was successfully prepared by a novel film plating / cyclic voltammetry (CV) method, which exhibited marked synergistic catalytic effects on the electro-oxidation of NO2–. The preparation process, impedance behavior, and surface morphology of Cuhydroxide/oxide/MWCNTs/GCE were investigated by CV, electrochemical impedance spectroscopy, and scanning electron microscopy (SEM), respectively. The optimum preparation and test conditions for the electrode to have high catalytic activity were acquired. The linear range between the anodic current (Δia, µA) and NO2– concentration (c, mmol L−1) was 1.0 × 10−4 to 14.0 mmol L−1, and the corresponding calibration curve was Δia = −0.1504 + 57.954c (R = 0.9990, n = 32) with a detection limit of 0.03 µmol L−1 (S/N = 3). The Cuhydroxide/oxide/MWCNTs/GCE prepared in the optimal conditions showed good stability, high selectivity, low detection limit, and quick response (<0.2 s) to NO2– in phosphate buffer (pH 5.29) at 0.78 V, which has been successfully applied to the determination of NO2– in pickled vegetables with satisfactory results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".