Novel natural manganese ore NH<sub>3</sub>‐SCR catalyst with superior alkaline resistance performance at a low temperature
Bibliographic record
Abstract
Abstract Potassium nitrate (KNO3) was chosen as the precursor to prepare the K‐poisoned catalysts on natural manganese ore using the impregnation method. The results demonstrate that the natural manganese ore catalyst possesses superior alkaline resistance performance with a high NOx conversion for NH3‐SCR of NOx at a low temperature. There are two factors responsible for the alkaline resistance performance. Firstly, the NH3 adsorption capacity (more acid sites) of K‐poisoned catalysts is stronger than that of fresh catalyst, which is beneficial for the NOx conversion. Secondly, the K‐poisoned catalyst has a smaller specific surface area, lower concentrations of Fe3+, Mn4+, and Oα, and lower reducibility, which leads to an inhibition effect on the NOx conversion. There exists a competition mechanism between the promotional and inhibition effect on the NOx conversion. The combination of these two effects leads to natural manganese ore exhibiting a superior alkaline resistance 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".