Ce–Mn coordination polymer derived hierarchical/porous structured CeO<sub>2</sub>–MnO<sub>x</sub> for enhanced catalytic properties
Bibliographic record
Abstract
Catalytic performance is largely dependent on how the structures/compositions of materials are designed. Herein, CeO2-MnOx binary oxide catalysts with a hierarchical/porous structure are prepared by a facile and efficient method, which involves the preparation of the hierarchical Ce-Mn coordination polymer (CPs) precursor, followed by a thermal treatment step. The obtained CeO2-MnOx catalysts not only well inherit the hierarchical structure of Ce-Mn CPs, but also possess porous and hollow features due to the removal of organic ligands and heterogeneous contraction during the calcination process. In addition, the effect of the Mn/Ce ratio is also studied to optimize catalytic performance. Specifically, the as-prepared CeO2-MnOx (5 : 5) catalyst exhibits excellent catalytic performance toward CO oxidation and selective catalytic reduction (SCR) of NO with NH3 at low temperatures. Based on the characterization results, we propose that the special hierarchical structure, high surface area, strong synergistic interaction between CeO2 and MnOx, and high content of active Ce3+, Mn4+ and Osurf are collectively responsible for its remarkable catalytic performance.
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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".