Zeolites as Catalysts for Fuels Refining after Indirect Liquefaction Processes
Bibliographic record
Abstract
The use of zeolite catalysts for the refining of products from methanol synthesis and Fisher–Tropsch synthesis was reviewed. The focus was on fuels refining processes and differences in the application to indirect liquefaction products was compared to petroleum, which is often a case of managing different molecules. Processes covered were skeletal isomerisation of n-butenes, hydroisomerisation of n-butane, aliphatic alkylation, alkene oligomerisation, methanol to hydrocarbons, ethanol and heavier alcohols to hydrocarbons, carbonyls to hydrocarbons, etherification of alkenes with alcohols, light naphtha hydroisomerisation, catalytic naphtha reforming, hydroisomerisation of distillate, hydrocracking and fluid catalytic cracking. The zeolite types that are already industrially used were pointed out, as well as zeolite types that have future promise for specific conversion processes.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 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".