The Performance of Nickel and Nickel-Iron Catalysts Evaluated As Anodes in Anion Exchange Membrane Water Electrolysis
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Bibliographic record
Abstract
Anion exchange membrane water electrolysis (AEMWE) is an efficient, cost-effective solution to renewable energy storage. The process includes oxygen and hydrogen evolution reactions (OER and HER); the OER is kinetically unfavourable. Studies have shown that nickel (Ni)- iron (Fe) catalysts enhance activity towards OER, and cerium oxide (CeO2) supports have shown positive effects on catalytic performance. This study covers the preliminary evaluation of Ni, Ni90Fe10 (at%) and Ni90Fe10/CeO2 (50 wt%) nanoparticles (NPs), synthesized by chemical reduction, as OER catalysts in AEMWE using commercial membranes. Transmission electron microscopy (TEM) images of the Ni-based NPs indicate NPs roughly 4–6 nm in size. Three-electrode cell measurements indicate that Ni90Fe10 is the most active non-noble metal catalyst in 1 and 0.1 M KOH. AEMWE measurements of the anodes show cells achieving overall cell voltages between 1.85 and 1.90 V at 2 A cm−2 in 1 M KOH at 50 °C, which is comparable to the selected iridium-black reference catalyst. In 0.1 M KOH, the AEMWE cell containing Ni90Fe10 attained the lowest voltage of 1.99 V at 2 A cm−2. Electrochemical impedance spectroscopy (EIS) of the AEMWE cells using Ni90Fe10/CeO2 showed a higher ohmic resistance than all catalysts, indicating the need for support optimization.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it