Selective oligomerization of isobutylene in mixed <scp>C<sub>4</sub></scp> catalyzed by supported <scp>Fe(NO<sub>3</sub>)<sub>3</sub>/β</scp> catalyst
Bibliographic record
Abstract
Abstract BACKGROUND Methyl tert‐butyl ether (referred to as MTBE) is harmful to the environment and hence its use is limited in China. To avoid the waste of isobutylene as MTBE raw material and improve the utilization rate of isobutylene in mixed C 4 fraction, supported Fe(NO 3 ) 3 /β molecular sieve catalysts with different active components were prepared by the equal volume impregnation method. The catalysts were analyzed by X‐ray diffraction (XRD), Thermogravimetric analysis (TG), Temperature programmed desorption of NH 3 , Brunauer–Emmett–Teller analysis and scanning electron microscopy, and the catalytic performance of catalysts with mixed C 4 fractions as raw materials and different active component loadings for selective oligomerization of isobutylene was investigated in a fixed bed reactor. RESULTS The results show that the catalyst has the best catalytic performance when the active component loading was 6%, the reaction temperature was 60 °C, the reaction pressure was 1 MPa and the reaction space velocity was 1.5 h −1 . CONCLUSION The conversion rate of isobutylene was >90%, the selectivity of C 8 olefin was ≈80% and there was almost no loss of n ‐butene. © 2021 Society of Chemical Industry (SCI).
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".