Nickel foam-based Ni(OH){sub 2}/NiOOH electrode as catalytic system for methanol oxidation in alkaline solution
Bibliographic record
Abstract
High energy density chemical power sources are needed in order to miniaturize electrical devices with long-life performance. NiOOH-metal hydride cells based on metal hydride anode and NiOOH cathode cells are considered to be the best sources of electrical power for hybrid electric vehicles and an alternative for electric vehicles. This study examined whether nickel foam-based cathodes used in alkaline cells have oxidative properties against methanol. It also examined the influence of methanol added to electrolytes on the performance of the cathode. In particular, the effect of methanol addition to the alkaline electrolyte was investigated in terms of the electrochemical process occurring on freshly formed nickel foam-based Ni(OH){sub 2}/NiOOH electrodes. The cyclic voltammetry method was used to examine electrochemical properties of these electrodes in 6 M KOH solution with or without methanol. The catalytic activity of these electrodes for methanol oxidation were also evaluated after the formation of active centres Ni(3) on the electrodes surface due to oxidative treatment. It was shown that the nickel foam-based Ni(OH){sub 2}/NiOOH electrode can catalyze the process of methanol oxidation in alkaline solution. The electrode activity depends on the intermediate step involving catalytic species of NiOOH and the concentration of CH{sub 3}OH in the electrolyte. In all the solutions, methanol was oxidized on the electrode in the region where the Ni(2) to Ni(3) reaction occurred, suggesting that Ni(3) ions mediate the electrochemical oxidation of methanol and electrode activity. This also indicates that electrode activity depends on the layer of NiOOH formed on the electrode surface. Products of methanol oxidation were found to weaken the efficiency and reversibility of electrode performance. 15 refs., 5 figs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".