Investigation on the electrocatalytic oxidation of alcohol using zinc oxide thin films deposited by pulsed electrodeposition on an indium tin oxide surface
Bibliographic record
Abstract
To perform electro-catalytic oxidation of alcohols in an alkaline media, zinc oxide (ZnO) thin films were effectively deposited on indium tin oxide (ITO) substrates using the pulsed electrodeposition (PE) method in a zinc nitrate aqueous solution. Analyses of microstructural, photoelectrochemical, and optical characteristics of ZnO thin films were performed as a function of pulsed electrodeposition parameters. XRD analysis was applied to determine structural properties, and SEM and AFM analysis were used to investigate morphological characteristics. X-ray diffraction analyses revealed that the produced films were polycrystalline and had a (002) preferentially oriented, hexagonal wurtzite structure. The morphology of ZnO has improved in the direction of nanorod films, as evidenced by scanning electron microscopy (SEM) and atomic force microscopy (AFM) images. UV transmittance data was used using Tauc's relationship to determine the film's bandgap to be 3.26 eV. The photocurrent response shows that ZnO films have high values, at 305.17 A/cm2, and good optical characteristics. The electrocatalytic oxidation of methanol was finally evaluated on the films. After being optimized in the pulsed electrodeposition mode, ZnO thin film characteristics and methanol electrocatalytic oxidation both saw substantial improvements.
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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) | 0.000 | 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) | 0.000 | 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".