Ni-NiO Heterojunction: A Binder-Free Catalyst for Enhanced Oxygen Evolution Reaction
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide In this study, we applied a two-step electrochemical anodization process to produce highly porous nanostructured nickel suboxides. We then annealed these materials in different environments: air, Ar, and Ar/H 2 . Annealing in a reductive environment (Ar/H 2 ) resulted in a Ni-NiO heterojunction with a high defect density, as confirmed by the Mott–Schottky analysis. Our results demonstrate that these defects and active sites significantly enhance the electrocatalytic activity for the oxygen evolution reaction (OER). Utilizing X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), high-resolution transmission electron microscopy (HR-TEM), and electrochemical analysis, we demonstrate that the heterojunction system containing Ni-NiO, formed through annealing in an Ar/H 2 atmosphere, acts as a highly efficient electrocatalyst for the OER. This catalyst achieves an impressively low overpotential of 293 mV at 10 mA cm –2, a Tafel slope of 74 mV dec –1, and exhibits outstanding stability, maintaining performance over 1000 cycles. Notably, our most optimized NiO x electrode outperforms the conventional reference RuO 2 electrode by a factor of 1.72. Our findings demonstrate the potential of binder-free Ni-NiO heterojunctions in developing high-performance electrocatalysts for alkaline electrolysis.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".