Nanoraspberry‐like palladium/spongy nickel oxide for electrooxidation of five light fuels
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The spongy nickel oxide (SNO) was synthesized the solution combustion method. The SNO was selected as a promoter to boost the catalytic activity of nanoraspberry‐like palladium (NRPd) toward electrooxidation of five light fuels (LFs): methanol, ethanol, formaldehyde, formic acid, and ethylene glycol. The X‐ray powder diffraction, Fourier‐transform infrared spectroscopy (FT‐IR), scanning electron microscopy, and field emission scanning electron microscope techniques were used for the materials characterization. In comparison with nonpromoted Pd, the NRPd‐SNO electrocatalyst shown an excellent efficiency in parameters like the electrochemical active surface area and anti‐CO poisoning behavior. The turnover data and the parameters, including reaction order, activation energy, and the coefficients of electron transfer and diffusion, were evaluated for the each process of LFs electrooxidation. The outcome for NRPd‐SNO activity toward LFs electrooxidation was compared to some reported electrodes. The SNO increases the removal of intermediates created in the oxidation of LFs that can poison the surface of palladium catalyst. This is due to the presence of the lattice oxygens in SNO structure and Ni switching between its high and low valances. The compatibility of the adsorption process of LFs on the surface of the NRPd‐SNO catalyst with different isotherms was determined by studying the Tafel polarization and calculating the surface coverage.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it