Electrochemical Sensing of Zinc Oxide and Peroxide Nanoparticles: Modification with Meso-tetrakis(4-carboxyphenyl) Porphyrin
Bibliographic record
Abstract
An electrochemical method was developed to investigate the redox properties of zinc oxide (ZnO), zinc peroxide (ZnO2), and sodium-doped zinc peroxide (Na-ZnO2) nanoparticles. The intention was to distinguish the identity of these nanoparticles among themselves, and from other transition metal oxide nanoparticles (TMONPs). Analysis of 3 mM sodium metabisulfite by cyclic voltammetry (CV) produced anodic/cathodic peak currents that are linearly related to the mass of deposited nanoparticles. A graphite working electrode was essential to the oxidation of metabisulfite. ZnO nanoparticles were crucial to the enhancement of metabisulfite oxidation current, and PPy coating could suppress the current enhancement by covering all nanoparticle surfaces. Furthermore, meso-tetrakis(4-carboxyphenyl) porphyrin was demonstrated to be a good chemical reagent that facilitates the differentiation of ZnO from ZnO2 and nanoparticles by CV analysis.
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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".