Preparation of Multi-Wall Carbon Tubes-Nanogold Particles Modified Glassy Carbon Electrode and Its Electrocatalytic Oxidation toward Paracetamol
Bibliographic record
Abstract
Paracetamol (PCM, acetaminophen) is widely used in Chinese and west medicines, which is a well-known antipyretic, non-steroidal and anti-inflammatory drug Both multi-wall carbon nanotubes(CNTs) The electrocatalytic activity of this modified electrode is related to the size of gold nanoparticles and the amount of gold deposited on the CNTs/GCE surface. On the basis of cyclic voltammograms(CV). The oxidation peak potential of PCM on AuNPs/CNTs/GCE is 0.241 V lower than that at the bare GCE and 0.275 V lower than that at the bare Gold electrode, which is strong evidence for the electrocatalytic oxidation of PCM at this modified electrode. The modified electrode shows the largest electrocatalytic activity at pH 7.0 in the pH region 5.0-8.0. The AuNPs/CNTs/GCE exhibits two liner regions, one is 0.005-0.1 mM PCM with the correlation coefficient 0.998, and another one is 0.20-3.0 mM PCM with the correlation coefficient 0.999. The experimental results demonstrate that the AuNPs-CNTs modified GCE (AuNPs/CNT/GCE) shows the high detection sensitivity for PCM and good repeatability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".