Enhanced Urea Oxidation Reaction Through Layered Double Hydroxides: Insights From <scp>ZIF</scp>‐67‐Derived Nanostructures
Bibliographic record
Abstract
ABSTRACT Layered double hydroxides (LDHs) are ionic layered compounds characterized by anion‐containing intermediate regions within positively charged brucite‐like layers. LDHs have shown high electrochemical activity in energy conversion systems such as batteries and fuel cells. In this study, we developed a hierarchically porous nanostructure derived from zeolitic imidazolate framework‐67, which was subsequently transformed into an LDH structure with varying Ni concentrations. We precisely controlled the Ni‐to‐Co ratio within the LDH structure and investigated how different mole fractions of Co and Ni influence catalytic activity and selectivity for the electrochemical urea oxidation reaction (UOR). LDH structures with low Ni content (up to 40%) demonstrated high activity and selectivity for O 2 due to their structural instability and the predominant oxygen evolution reaction (OER) originating from ZIF‐67. In contrast, LDHs with high Ni content (over 60%) supressed OER and exhibited enhanced activity for UOR. The resulting hollow structure with an expanded electrochemically active surface in LDHs with high Ni content could improve mass transport and diffusion at the electrode interface, leading to better reaction kinetics and higher current densities. These findings provide a foundational design guideline for metal–organic framework‐derived nanostructure in UOR. image
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".