Part II: NiMoO4 Nanostructures Synthesized by the Solution Combustion Method: A Parametric Study on the Influence of Material Synthesis and Electrode-Fabrication Parameters on the Electrocatalytic Activity in the Hydrogen Evolution Reaction
Bibliographic record
Abstract
Earth-abundant NiMo-oxide nanostructures were investigated as efficient electrocatalytic materials for the hydrogen evolution reaction (HER) in acidic media. Synthesis and non-synthesis parameters were thoroughly studied. For the non-synthesis parameters, the variation in Nafion loading resulted in a volcano-like trend, while the change in the electrocatalyst loading showed that the marginal benefit of high loadings attenuates due to mass-transfer limitations. The addition of carbon black to the electrocatalyst layer improved the HER performance at low loadings. Different carbon black grades showed a varying influence on the HER performance. Regarding the synthesis parameters, a calcination temperature of 500 °C, a calcination time between 20 and 720 min, a stoichiometric composition (Ni/Mo = 1), an acidic precursor solution, and a fuel-lean system were conditions that yielded the highest HER activity. The in-house NiMoO4/CB/Nafion electrocatalyst layer was found to offer a better long-term performance than the commercial Pt/C.
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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) | 0.002 | 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".