Role of promoters and catalyst supports for selective synthesis of higher alcohols over molybdenum carbides
Bibliographic record
Abstract
Abstract The synthesis of higher alcohols from syngas is a very promising avenue as syngas can be derived from renewable (biomass) and non‐renewable feedstock (coal, natural gas). To date no commercial process exists for the conversion of syngas into higher alcohols due to poor alcohols yield and selectivity. The search for selective catalysts requires fundamental insight into how to enhance active sites for the formation of alcohols. In the present work, the dispersion of K 2 CO 3 promoted molybdenum carbides over three different supports i.e., highly acidic (ɣ‐alumina), neutral (activated carbon), and basic (magnesium oxide) has been studied. The results revealed that acid sites of ɣ‐alumina expedited the dispersion of the K 2 CO 3 promoter over the molybdenum carbide catalyst and facilitated carbon monoxide dissociation to form C 2+ alcohols. The effect of the incorporation of cobalt into the textural and catalytic properties of alumina supported K‐Mo 2 C was also investigated. The elemental mapping of Co into the K‐Mo 2 C structure showed the presence of segregated Co and Mo 2 C islands, but an interaction was observed at the molecular level, resulting in a different H 2 temperature‐programmed desorption pattern. With the decreased availability of surface adsorbed hydrogen of the Co promoted K‐Mo 2 C/Al 2 O 3 , the concentration of methanol was significantly reduced and the product selectivity shifted more towards higher alcohols.
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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".