Coupling of propane with CO<sub>2</sub> to propylene over Zn-promoted In/HZSM-5 catalyst
Bibliographic record
Abstract
The ZnIn/HZSM-5 catalyst was prepared by the wetness impregnation method, and the structure of catalyst was characterized by XRD, SEM, TEM, H 2 -TPR, NH 3 -TPD, XPS, TG, and N 2 adsorption–desorption and then investigated in the coupling of propane with CO 2 to propylene. It is found that the addition of Zn species is beneficial to the dispersion of In 2 O 3 over HZSM-5, which plays an important role in propene formation, and adjusts the acidity distribution of In/HZSM-5 catalyst, as well as significantly improves the activity of In/HZSM-5 catalyst. The selectivity of propylene is 68.21% in the coupling of propane with CO 2 over ZnIn/HZSM-5 catalyst when the time on stream (TOS) is 2 h, reaction temperature is 580 °C, reaction pressure is 0.3 MPa, C 3 H 6 :CO 2 :N 2 = 1:4:5, catalyst mass is 0.2 g, and space velocity is 6000 mL g cat −1 h −1 . However, the selectivity of propylene is only 63.33% and 0.25% in the propane dehydrogenation or CO 2 hydrogenation reaction, respectively. The ZnIn/HZSM-5 catalyst showed a higher stability with only 0.80% conversion drop after three cycles.
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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 | 0.000 | 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) | 0.000 | 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".