Synthesis and Characterization of RuO<sub>2</sub> Anode Materials with Large Surface Areas for Oxygen Evolution Reaction
Bibliographic record
Abstract
A novel olivary or petal-like RuO2 material with large surface area was successfully synthesized by surfactant-assisted homogeneous precipitation method using urea and dodecyl sulfate as the source reagent. The surface morphology, structural, and electrochemical properties of as-synthesized RuO2 materials were characterized by x-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), Cyclic voltammetry (CV), N2 adsorption–desorption isotherms and polarization curve for oxygen evolution reaction (OER). It was found that the morphology and crystalline structures and electrochemical properties of as-synthesized RuO2 materials were strongly dependent on the calcining temperature. The ruthenium-surfactant mesophase with mesoporous structure transformed from network to regular olivary or petal-like RuO2 materials and remaining partial mesoporous character after calcination at lower temperature (i.e., 300 and 400 °C). However, the mesophase transformed into RuO2 agglomeration consisted of nanosized particles after calcination at 650 °C, which may be attributed to complete deorganization and porous structure collapse of RuO2 materials. In addition, the as-synthesized RuO2 materials showed higher specific surface area and better electrochemical activities for oxygen evolution reaction compared with the RuO2 prepared without surfactant. The electrochemical activity of as-synthesized RuO2 material calcined at 400 °C is about 3 times than that of RuO2 prepared without surfactant for oxygen evolution reaction. This can be attributed to the porous structure and large surface area of as-synthesized RuO2 materials.
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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".