Zinc Hinders Deactivation of Copper-Mordenite: Dimethyl\nEther Carbonylation
Bibliographic record
Abstract
A plethora\nof previously unimaginable low-temperature C<sub>1</sub> and C<sub>2</sub> valorization reactions have become possible after\nthe discovery of metal-exchanged solid-acid catalysts, with the most\npromising candidate being copper-mordenite. We show the dramatic effect\nof zinc addition to copper-exchanged mordenite in maintaining high\nCu dispersion and reducing the catalyst poisoning as it relates to\ncarbonylation of dimethyl ether to methyl acetate. Zinc maintains\n90%+ selectivity even during deactivation versus 60% for the Cu-mordenite,\nwhich leads to 6-fold higher product yield. The concept of Zn addition\nis recommended for further exploration in the conversion of methane\nto methanol or acetic acid.
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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 | 0.001 |
| 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) | 0.018 | 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".