Electro‐Oxidation of Ni42 Steel: A Highly Active Bifunctional Electrocatalyst
Bibliographic record
Abstract
Janus type water‐splitting catalysts have attracted highest attention as a tool of choice for solar to fuel conversion. AISI Ni42 steel is upon harsh anodization converted into a bifunctional electrocatalyst. Oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) are highly efficiently and steadfast catalyzed at pH 7, 13, 14, 14.6 (OER) and at pH 0, 1, 13, 14, 14.6 (HER), respectively. The current density taken from long‐term OER measurements in pH 7 buffer solution upon the electro‐activated steel at 491 mV overpotential (η) is around four times higher (4 mA cm−2) in comparison with recently developed OER electrocatalysts. The very strong voltage–current behavior of the catalyst shown in OER polarization experiments at both pH 7 and at pH 13 are even superior to those known for IrO2‐RuO2. No degradation of the catalyst is detected even when conditions close to standard industrial operations are applied to the catalyst. A stable Ni‐, Fe‐oxide based passivating layer sufficiently protects the bare metal for further oxidation. Quantitative charge to oxygen (OER) and charge to hydrogen (HER) conversion are confirmed. High‐resolution XPS spectra show that most likely γ−NiO(OH) and FeO(OH) are the catalytic active OER and NiO is the catalytic active HER species.
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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) | 0.001 | 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 | 0.001 |
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".