Highly active and durable methanol oxidation electrocatalyst based on the synergy of platinum–nickel hydroxide–graphene
Bibliographic record
Abstract
Active and durable electrocatalysts for methanol oxidation reaction are of critical importance to the commercial viability of direct methanol fuel cell technology. Unfortunately, current methanol oxidation electrocatalysts fall far short of expectations and suffer from rapid activity degradation. Here we report platinum-nickel hydroxide-graphene ternary hybrids as a possible solution to this long-standing issue. The incorporation of highly defective nickel hydroxide nanostructures is believed to play the decisive role in promoting the dissociative adsorption of water molecules and subsequent oxidative removal of carbonaceous poison on neighbouring platinum sites. As a result, the ternary hybrids exhibit exceptional activity and durability towards efficient methanol oxidation reaction. Under periodic reactivations, the hybrids can endure at least 500,000 s with negligible activity loss, which is, to the best of our knowledge, two to three orders of magnitude longer than all available electrocatalysts.
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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) | 0.001 | 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".