An Advanced Ni–Fe Layered Double Hydroxide Electrocatalyst for Water Oxidation
Bibliographic record
Abstract
Highly active, durable, and cost-effective electrocatalysts for water oxidation to evolve oxygen gas hold a key to a range of renewable energy solutions, including water-splitting and rechargeable metal-air batteries. Here, we report the synthesis of ultrathin nickel-iron layered double hydroxide (NiFe-LDH) nanoplates on mildly oxidized multiwalled carbon nanotubes (CNTs). Incorporation of Fe into the nickel hydroxide induced the formation of NiFe-LDH. The crystalline NiFe-LDH phase in nanoplate form is found to be highly active for oxygen evolution reaction in alkaline solutions. For NiFe-LDH grown on a network of CNTs, the resulting NiFe-LDH/CNT complex exhibits higher electrocatalytic activity and stability for oxygen evolution than commercial precious metal Ir catalysts.
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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) | 0.000 | 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 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".