Investigating the Performance of Tantalum Carbide Supported Iridium-Based Catalyst for Polymer Electrolyte Membrane Water Electrolysis
Bibliographic record
Abstract
Hydrogen from polymer electrolyte membrane (PEM) water electrolysis has been identified as a key enabler for the transition to low/no-carbon energy from renewable energies. Polymer electrolyte membrane water electrolysis can be used to generate hydrogen from surplus energy generated using renewable energy technologies. Iridium is currently considered a state-of-the-art catalyst for the oxygen evolution reaction. However, it is a rare noble metal and as such a surge in demand would increase the cost of PEM water electrolyser units. One of the main strategies employed is the reduction of the noble metal loading through the use of supports. Tantalum carbide supported iridium based catalysts have been shown to be potential candidates for use as oxygen evolution reaction (OER) catalysts for water electrolysis. In this study, the performance of IrOx/TaC catalyst prepared using a surfactant mediated method is presented. IrOx/TaC catalysts were synthesized and fabricated into membrane electrode assemblies (MEAs). Nafion 115 was used as the membrane for the MEAs. Ir:TaC ratio was varied and its effect on the electrolyser performance was observed. The ionomer loading in the anode was also varied at the different Ir:TaC ratios and the performance observed. The elemental distribution of the IrOx/TaC was determined using scanning transmission electron microscopy (STEM)/energy dispersive spectroscopy (EDS). The conductivities of the catalysts and MEAs were also determined. Scanning electron microscopy (SEM) was used to analyse the morphology and elemental distribution of the electrode surfaces and the cross-section of the MEAs. The electrochemical performance of the MEAs was then tested in a single cell electrolyser equipped with an in-situ reference electrode. Current-voltage (I-V) curves were obtained potentiostatically at 80 °C. It was observed that while the fabricated MEAs had lower loading of iridium in the electrode, their performance was comparable with those found in literature.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".