Effects of different manganese precursors as promoters on catalytic performance of CuO–MnO<sub>x</sub>/TiO<sub>2</sub> catalysts for NO removal by CO
Bibliographic record
Abstract
Two different precursors, manganese nitrate (MN) and manganese acetate (MA), were employed to prepare two series of catalysts, i.e., xCuyMn(N)/TiO2 and xCuyMn(A)/TiO2, by a co-impregnation method. The catalysts were characterized by XRD, LRS, CO-TPR, XPS and EPR spectroscopy. The results suggest that: (1) both xCuyMn(N)/TiO2 and xCuyMn(A)/TiO2 catalysts exhibit much higher catalytic activities than an unmodified Cu/TiO2 catalyst in the NO + CO reaction. Furthermore, the activities of catalysts modified with the same amount of manganese are closely dependent on manganese precursors. (2) The enhancement of activities for Mn-modified catalysts should be attributed to the formation of the surface synergetic oxygen vacancy (SSOV) Cu(+)-□-Mn(y+) in the reaction process. Moreover, since the formation of the SSOV (Cu(+)-□-Mn(3+)) in the xCuyMn(N)/TiO2 catalyst is easier than that (Cu(+)-□-Mn(2+)) in the xCuyMn(A)/TiO2 catalyst, the activity of the xCuyMn(N)/TiO2 catalyst is higher than that of the xCuyMn(A)/TiO2 catalyst. This conclusion is well supported by the XPS and EPR results.
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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) | 0.000 | 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 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".