Rhenium‐boosted electrocatalytic activity and durability of pyrolytic IrO <sub>2</sub> for acidic oxygen evolution
Bibliographic record
Abstract
摘要 IrO 2 以其在酸性介质中的出色稳定性而闻名，但是析氧反应（OER）活性有限。为了在保持其超高稳定性的同时增强本征OER活性，本文报道了一种使用热分解方法合成的掺入杂原子铼（Re）的热解IrO 2 。由此方法合成的Ir 0.928 Re 0.072 O 2 电极在0.5 M H 2 SO 4 溶液中表现出了明显的本征OER活性提高，比原始IrO 2 高出4倍，10 mA·cm ‐2 对应的过电位仅为209 mV。重要的是，Ir 0.928 Re 0.072 O 2 电极可以在200 mA·cm ‐2 的大电流密度下维持400小时以上的酸性OER。这些发现为降低IrO 2 基电催化剂在酸性OER电化学工业领域的能耗带来了巨大的希望。
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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".