Direct, Soft Chemical Route to Mesoporous Metallic Lead Ruthenium Pyrochlore and Investigation of its Electrochemical Properties
Bibliographic record
Abstract
Mesoporous, nanocrystalline metallic lead ruthenium oxide (a pyrochlore) was synthesized through the formation of a mesostructured cohydroxide network via liquid crystal templating, and subsequent “soft” chemical oxidation that crystallizes the oxide at low temperature. The stable S + I – interaction chemistry responsible for the templating methodology is elucidated. The formation of a disordered mesoporous structure with a pore volume of 0.18 cm 3 /g and walls comprised of nanocrystallites was confirmed by X-ray diffraction and conductivity, N 2 isotherm measurements, and TEM observations. The resistivity of mesoporous oxide at room temperature was 0.046 Ω·cm, only 2 orders of magnitude less than the single crystal value, and one of the only two porous metallic oxides that are known to date. The electrocatalytic properties of this material for oxygen reduction and evolution in aqueous and nonaqueous media were evaluated by cyclic voltammetry, chronoamperometry, and linear sweep voltammetry. These techniques show that the synthesized pyrochlore lowers the overall oxidation voltage by 0.7 V relative to carbon in nonaqueous, Li + -containing electrolyte. This is the result of its ability to both completely oxidize Li 2 O 2 (at a relatively low potential) and electrocatalytically oxidize all known side-products formed from electrolyte decomposition in the Li–O 2 battery. This further helps to explain the nature of “electrocatalysis” in this system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".