Direct decomposition of nitric oxide in low temperature over iron-based perovskite-type catalyst modified by Ru
Bibliographic record
Abstract
Iron-based perovskite-type compounds modified by Ru were prepared through sol-gel process to study its catalytic activity of NO_x direct decomposition at low temperature and evaluate the conversion of NO under the experimental conditions. The catalytic activity of La_ 0.9Ce_ 0.1Fe_ 0.8-nCo_ 0.2Ru_nO_3 (n=0.01,0.03,0.05,0.07,0.09)series for the NO, NO-CO two components, CO-HC-NO three components were also analyzed. The catalytic investigation evidenced that the presence of Ru is necessary for making highly activity in decomposition of nitric oxide even at low temperature(400 ℃)and La_ 0.9Ce_ 0.9Fe_ 0.75Co_ 0.2Ru_ 0.05O_3 (n=0.05) has better activity in all the samples, the conversion of it is 58.5%. With the reducing gas(CO,C_3H_6)added into the gas, the catalyst displayed very high activity in decomposition of NO and the conversion of it is 80% and 92.5% separately.
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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) | 0.003 | 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".