Kinetic Investigation of η-Al2O3 Catalyst for Dimethyl Ether Production
Bibliographic record
Abstract
Energy consumption throughout the world has been continuously increased especially for industrialized cities. The carbon-based non-renewable sources, mainly crude oil, are unsustainable because of the production of the significant amount of greenhouse gases in which is the main cause of the global warming. To meet the energy demand and decrease the air pollution an alternative renewable energy should be developed. The production of clean biofuel such as dimethyl ether (DME) is an attractive alternative for pollution mitigation. DME is an environmentally friendly fuel with clean-burning and smoke-free emissions [ 1 ]. The attractive combustion properties are due to it containing neither sulphur nor nitrogen, with very low SO x or NO x emissions. The lack of direct carbon-to-carbon bonds means it does not generate particulate matter emissions. DME can be produced by two main routes; either from syngas using a bi-functional catalyst (Eq. 1 ) or via the dehydration of methanol over solid catalysts such as Al 2 O 3 (Eq. 2 ), according to the following reactions [ 1 , 2 , 3 , 4 , 5 , 6 ]:
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".