Cu‐based mixed metal oxide catalysts for WGSR: Reduction kinetics and catalytic activity
Bibliographic record
Abstract
Abstract This communication reports the effects of Mn/Cr on the reducibility and catalytic activity of Cu–Fe–Mn and Cu–Fe–Cr mixed oxide catalysts for the water gas shift reaction (WGSR). The reduction kinetics of the mixed oxide catalysts is investigated using TPR data, nucleation/nuclei growth models, and a power law model. Based on the statistical indicators, it is concluded that a second‐order power law model describes the reduction of all catalysts adequately. The estimated activation energy for the reduction of the Cu–Fe–Mn catalyst is low compared to the Cu–Fe–Cr catalyst. The TPR analysis of the catalysts reveals that the addition of Mn significantly improved the reducibility of Cu‐oxide species, which is consistent with the low activation energy for reduction of the Cu–Fe–Mn catalyst. In a flow type reactor, the Cu–Fe–Mn catalyst showed highest CO conversion at around 220°C, achieving a high specific reaction rate compared to the Cu–Fe–Cr catalyst. The enhanced reducibility of Cu–Fe–Mn catalyst played the key role in the high conversion of CO. These results are comparable with the results obtained for a commercial Cu–ZnO/Al 2 O 3 catalyst, which was evaluated under the same reaction conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".