Supported IrO<sub>2</sub> Nanocatalyst with Multilayered Structure for Proton Exchange Membrane Water Electrolysis
Bibliographic record
Abstract
Abstract The design of a low‐iridium‐loading anode catalyst layer with high activity and durability is a key challenge for a proton exchange membrane water electrolyzer (PEMWE). Here, the synthesis of a novel supported IrO2 nanocatalyst with a tri‐layered structure, dubbed IrO2@TaOx@TaB that is composed of ultrasmall IrO2 nanoparticles anchored on amorphous TaOx overlayer of TaB nanorods is reported. The composite electrocatalyst shows great activity and stability toward the oxygen evolution reaction (OER) in acid, thanks to its dual‐interface structural feature. The electronic interaction in IrO2/TaOx interface can regulate the coverage of surface hydroxyl groups, the Ir3+/ Ir4+ ratio, and the redox peak potential of IrO2 for enhancing OER activity, while the dense TaOx overlayer can prevent further oxidation of TaB substrate and stabilize the IrO2 catalytic layers for improving structural stability during OER. The IrO2@TaOx@TaB can be used to fabricate an anode catalyst layer of PEMWE with an iridium‐loading as low as 0.26 mg cm−2. The low‐iridium‐loading PEMWE delivers high current densities at low cell voltages (e.g., 3.9 A cm−2@2.0 V), and gives excellent activity retention for more than 1500 h at 2.0 A cm−2 current density.
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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) | 0.001 | 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".