Methanol dehydration to dimethyl ether over KFI zeolites. Effect of template concentration and crystallization time on catalyst properties and activity
Bibliographic record
Abstract
The transition to renewable energy from fossil fuels in the transportation industry is crucial for the environment. Dimethyl ether (DME) is a promising substitute for fossil fuels as it can be produced from green hydrogen and CO2 from direct air capture, and in addition has reduced CO, SOx, and NOx emissions upon combustion. This study investigated KFI-type zeolites as catalysts for methanol dehydration to DME while comparing ZSM-5 and γ-Al2O3 as benchmarks. The influence of template (18-Crown-6) concentration and hydrothermal crystallization time were examined on catalyst properties using characterization techniques including XRD, SEM, BET, DRIFTS, NH3-TPD, and TGA. Activity and stability tests revealed that an optimum KFI zeolite, synthesized with a molar Si/Template ratio of 10:1 and 7 days of crystallization, has superior performance compared to traditional catalysts. The catalyst achieved thermodynamic equilibrium conversion at approximately 185 ℃ (91%) due to high acidity (2466 μmol g–1) and maintained activity for > 100 h. The stable and superior activity is attributed to mesoporous structure and numerous weak acid sites.
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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 | 0.000 | 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".