Active Probing of a RuO<sub>2</sub>/CZ Catalyst Surface as a Tool for Bridging the Gap Between CO Oxidation Catalytic Tests in a Model and Realistic Exhaust Gas Stream
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Herein, we present a paper that attempts to bridge the gap between CO oxidation catalytic tests performed in a model stream and a more realistic exhaust gas stream by incorporating characterization methods that allow for active probing of the catalyst surface. The results have shown that it is not just the abundance of a given type of species on the surface that impacts the activity of a system but also the ease of extraction of ions from their surface (time-of-flight secondary ion mass spectrometry) and the response of the support to change in the feed composition (dynamic in situ X-ray diffraction (XRD) with variable atmosphere). The study utilizes the method of doping a catalyst (RuO 2 /CZ) with a small amount of alkali-metal (K + or Na + ) carbonates in order to slightly modify its surface to gain insight into parameters that may cause discrepancies between model stream activity and complex stream activity. The most pronounced difference is that in the model stream, which contains only CO and O 2 in helium, both alkali ions improve the activity of the system at temperatures around 175 °C, whereas in the complex stream, which mimics the exhaust stream from a diesel engine under oxygen lean conditions, the K + -doped catalyst is slightly worse than RuO 2 /CZ and RuO 2 + Na + /CZ and much worse in propane combustion. The total hydrogen consumption values (temperature-programmed reduction) and the O ads /O latt ratios (X-ray photoelectron spectroscopy) both place the RuO 2 + K + /CZ system between the other two and hence provided no reason for the unusual behavior of the K + -doped catalyst. In contrast, both in situ XRD measurement tests and ToF SIMS results show a pronounced difference between the RuO 2 + K + /CZ catalyst and the other two systems, which indicates that the interaction of the surfaces with the reagents might be the cause of the discrepancy. The CO 2 -TPD results show that this system retains more CO 2, i.e., the product, at adsorption sites, which might reduce the adsorption of other reagents, i.e., oxygen ions, CO, and propane, hence lowering the overall activity of the system.
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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".