<scp>SrO</scp> ‐modified Pd/ <scp> Al <sub>2</sub> O <sub>3</sub> </scp> three‐way catalyst with advanced activity for passive selective catalytic reduction operation
Bibliographic record
Abstract
Abstract Passive selective catalytic reduction (pSCR) is a promising technology for exhaust aftertreatment applied in lean burn gasoline engines, which requires the three‐way catalyst (TWC) to provide NH 3 for the downstream SCR reaction process. Consequently, in the assessment of TWC catalytic performance for pSCR operation, not only the conversion efficiency of CO, HC, and NO should be taken into account, but the generation of NH 3 is equally crucial. In this study, the modification of Pd/Al 2 O 3 catalyst was realized with the assistance of SrO, and the catalytic performance in terms of both the conversion efficiency of CO/HC/NO and the production of NH 3 was measured. Additionally, the physicochemical characteristics of the SrO‐modified catalysts were evaluated in comparison to those of the unmodified Pd/Al 2 O 3 through various analytic techniques. The findings indicate that incorporating SrO into the Pd/Al 2 O 3 system enhances the conversion efficiency for CO, HC, and NO, and more importantly, a larger generation of NH 3 is achieved, and the most effective concentration of SrO is identified as 4 wt.%. Based on the characterization results, it is found that SrO mainly interacts with tetra‐coordinated or penta‐coordinated Al sites on the surface of the catalyst, which brings about weakened surface acidity. The beneficial effect of SrO is primarily linked to its capacity to enhance the thermal durability of the Al 2 O 3 support, facilitate the distribution of Pd‐related particles, and adjust the chemical states of Pd species. Additionally, it could modify the reduction characteristics and the desorption performance of NH 3 over the catalyst.
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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".