Catalytic activity of Co-åkermanite and Co-pyroxene in oxidation reactions
Bibliographic record
Abstract
Two calcium–cobalt silicates were synthesized in which cobalt occupies different structural positions. The crystal phases belong to two main structural silicate types. In the Co-åkermanite structure (Ca2CoSi2O7), cobalt cations take tetrahedral coordination toward oxygen atoms. In the Co-pyroxene structure of CaCoSi2O6, cobalt displays octahedral coordination. Ca2CoSi2O7 was prepared by solid-phase synthesis and CaCoSi2O6 was prepared by sol–gel method. The synthesis of the phases was confirmed by XRD, FTIR, and EPR data. On the basis of the XPS analysis, it can be concluded that Co2+ cations exist in the studied silicates. Thus, it is possible to study the catalytic activity of two silicate phases containing Co2+ cations in different coordinations: tetrahedral and octahedral. It was found that cobalt silicates with crystal structures corresponding to pyroxene and åkermanite possess catalytic activity in the reactions of complete oxidation of CO and toluene. Co-pyroxene exhibits higher catalytic activity than Co-åkermanite, but the higher cobalt content on the surface of Co-pyroxene should also be taken into account. Then, it turns out that catalytically active complexes with Со2+ ions in tetrahedral coordination are more efficient than those with such ions in octahedral coordination when equal concentrations of cobalt were used on the surface of the catalysts.
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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".