Prussian blue analogue-derived Ni and Co bimetallic oxide nanoplate arrays block-built from porous and hollow nanocubes for the efficient oxygen evolution reaction
Bibliographic record
Abstract
Effective oxygen evolution reaction (OER) catalysts composed of Earth-abundant transition metals are crucial for sustainable energy conversion and storage. Metal-organic frameworks (MOFs) with tunable compositions are promising precursors for the fabrication of hollow and porous electrocatalysts. However, pulverous MOFs usually suffer from agglomeration during pyrolysis, greatly reducing the activity of their derived catalysts. In this work, Prussian blue analogue (PBA) arrays with hierarchical multidimensional architecture were directly grown on nickel foam (NF) using a template-oriented method. The subsequent calcination in air allowed for obtaining NixCo3-xO4 nanoplate arrays consisting of porous and hollow nanocubes. The derived bimetallic NixCo3-xO4/NF required only an overpotential of 287 mV to achieve a current density of 10 mA cm-2 in 1.0 M KOH solution, which is much lower than that of the monometallic NiO and the RuO2 benchmark. The 3D intersectional architecture of the NixCo3-xO4 nanoplates and the porous and hollow nanocube subunits contributed to the large specific surface area and reduced charge-transfer resistance of the NixCo3-xO4/NF electrode. Density functional theory (DFT) calculations and post-OER characterization revealed that the incorporated Co was the active sites and electrochemical active CoOOH intermediates were in situ formed during the OER. Our study provides a facile and efficient strategy for the rational design of MOF-derived materials towards effective and low-cost electrocatalysis.
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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 | 0.000 |
| 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) | 0.000 | 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".