Dehydration of methanol to dimethyl ether over γ‐Al<sub>2</sub>O<sub>3</sub> catalyst: Intrinsic kinetics and effectiveness factor
Bibliographic record
Abstract
Abstract Dehydration of methanol to dimethyl ether (DME) over a commercial γ‐Al2O3 catalyst was studied at the temperature interval 513–613 K, liquid hourly space velocity (LHSV) of 0.9–6.0 h−1 and pressures between 0.1 and 1.0 MPa. The effect of different operation conditions on the dehydration of methanol was investigated in an isothermal fixed bed reactor. A kinetic equation which describes a Langmuir–Hinshelwood surface controlled reaction with dissociative adsorption of methanol was found to fit the experimental results quite well. An activation energy of 62.4 kJ/mol was obtained for the catalyst. A two‐dimensional reaction–diffusion model was established for a cylindrical‐shaped methanol dehydration catalyst. The internal effectiveness factor and the concentration distribution of methanol in the catalyst were obtained by the finite element method in MATLAB. The reaction–diffusion model was verified by the global kinetics data. The calculation data agreed well with the experimental data, so the model can be used to describe the processes of reaction and diffusion in the cylindrical‐shaped catalyst.
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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".