Physicochemical Characterization of Mixed RuO<sub>2</sub>−SnO<sub>2</sub> Solid Solutions
Bibliographic record
Abstract
Mixed SnO 2 −RuO 2 oxides were prepared by high-energy mechanical alloying of various proportions of pure SnO 2 and RuO 2 powders. The physicochemical characterization of the resulting materials was conducted by X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and electrochemical surface analysis. It is shown through XRD analysis that a single-phase (tetragonal) (Sn−Ru)O 2 solid solution is formed over the whole composition range, in which the Sn 4+ and Ru 4+ ions share the same cationic sub-lattice of the rutile-like structure. The surface of the compounds was analyzed by XPS and shows a deficit of Ru atoms, with [Ru] surface = 36 at. % for an equimolar SnO 2 −RuO 2 concentration in the bulk of the sample. In the case of pure nanocrystalline RuO 2, the total surface charge, q T *, the most easily accessible surface charge, q O *, and the less easily accessible surface charge, q I *, are 35.3, 29.0, and 6.3 mC cm - 2 mg - 1, respectively. These surface charges vary linearly with the Ru content at the surface of the electrode, indicating that the surface electrochemical properties of the compounds are dominated by the redox properties of the Ru 4+ cation. The ratio q O */ q T * is close to 0.8 and independent of the surface composition, suggesting that all compounds have a similar morphology.
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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".