Deactivation mechanism of activated carbon supported copper oxide SCR catalysts in C<sub>2</sub>H<sub>4</sub> reductant
Bibliographic record
Abstract
Current state‐of‐the‐art NH 3 ‐SCR technology based on vanadium catalysts suffers problems associated with NH 3 slip and poisoning of the catalyst and blockage of heat recovery steam generators (HRSG). If environmentally‐friendly catalysts capable of efficient operation at lower temperatures could be developed that used a reductant other than NH 3 , the issues with current state‐of‐the‐art SCR could be significantly lessened. Hence, in this study, activated carbon (AC) supported copper oxide‐based catalysts for SCR while using C 2 H 4 as a reductant was discussed. Reaction testing of catalysts demonstrated high initial NO conversion with steeply declining activity over 2 h of testing when C 2 H 4 was used as the reductant; in comparison, with the same catalyst and NH 3 as the reductant, stable, long‐term NO conversion was achieved, but at a lower rate than the initial reactivity with C 2 H 4 . As a consequence, catalyst characterization studies were performed to assess deactivation mechanisms when C 2 H 4 was the reductant. These studies included x‐ray diffraction, BET surface area and porosity, temperature programmed reduction, scanning electron microscopy, Raman spectroscopy and x‐ray photoelectron spectroscopy of both fresh and deactivated catalysts. The analytical results showed the surface area and porosity of the catalyst remained unchanged and the initially highly‐dispersed Cu species became agglomerated and more crystalline during reaction testing. Furthermore, carbon black was also detected on the catalyst surface after testing, presumably formed during the decomposition of C 2 H 4 . Both agglomeration of the active Cu species and blockage by carbon deposits would decrease the availability of active sites and lead to decreased catalytic activity.
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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 | 0.001 | 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".