NiFeOx and NiFeCoOx Catalysts for Anion Exchange Membrane Water Electrolysis
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Bibliographic record
Abstract
Hydrogen production using an Anion exchange membrane (AEM) electrolyzer allows the use of non-platinum group metal catalysts for oxygen evolution reaction (OER). Nickel and Cobalt-based oxides are active in an alkaline environment for OER and are relatively inexpensive compared to IrO2 catalysts used in Polymer electrolyte membrane (PEM) electrolysis. Mixed metal oxide catalysts NiFeOx and NiFeCoOx catalysts were synthesized by the coprecipitation method using NaOH. X-ray diffraction results showed mainly NiO diffraction peaks for the NiFeOx catalyst due to the low concentration of Fe, for the NiFeCoOx catalyst, NiCo2O4 diffraction peaks were observed. NiFeCoOx catalysts showed a higher Anion exchange membrane water electrolysis (AEMWE) performance compared to NiFeOx and commercial NiO, the highest current density at 2 V was 802 mA cm−2 at 70 °C using 1 M KOH as an electrolyte. The effect of electrolyte concentration was studied by using 0.01 M, 0.1 M and 1 M KOH concentrations in an electrolysis operation. Electrochemical Impedance spectroscopy was performed along with the equivalent circuit fitting to calculate ohmic and activation resistances, the results showed a decrease in ohmic and activation resistances with the increase in electrolyte concentration. Commercially available AEM (Fumasep FAA-3-50 and Sustainion dioxide membrane X-37-50 grade T) were tested at similar conditions and their performance was compared. EIS results showed that X-37-50 offered lower ohmic resistance than the FAA-3-50 membrane.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it