Suppression of Addition Reactions during Thermal Cracking Using Hydrogen and Sulfided Iron Catalyst
Bibliographic record
Abstract
Due to the complexity of the vacuum residue fraction of petroleum and bitumen, a model compound was used to probe cracking and addition reactions in the liquid phase. Hydrogenation reactions were conducted in a batch microreactor at 430 °C, 13.9 MPa H2 for 30 min using a solution of 1,3,6,8-tetrahexylpyrene (THP) in tetralin. Sulfided iron was prepared on α-alumina, γ-alumina, and glass beads as support materials. The hypothesis of this study was that addition reactions can be suppressed under hydrogenation conditions by using iron sulfide as a low-activity catalyst in the presence of hydrogen gas and a hydrogen donor solvent, by saturating olefin intermediates. The products were analyzed by high performance liquid chromatography, gas chromatography, matrix-assisted laser desorption ionization mass spectrometry, and proton nuclear magnetic resonance spectroscopy to investigate conversion and product distribution for different catalysts and without added catalyst. The results show that sulfided iron can give significant suppression of addition reactions, decreasing from 63 mol % for the noncatalytic reaction to 13 mol % under catalytic conditions, and shifting the selectivity toward cracking, without competitive hydrogenation of the aromatics. The catalysts were characterized by measuring bulk and surface composition, and by scanning electron microscopy before and after the reaction. The data show that catalyst does not have an impact on conversion; therefore, the data do not support the claim that free radicals are efficiently hydrogenated. The results confirm the presence of iron sulfide on the catalyst surface and a change in its crystalline structure from pyrite to pyrrhotite during reaction. This study shows the value of using a low-cost iron catalyst, as compared to the commercial nickel-based catalysts, as an additive to reduce the amount of coke formation in thermal cracking processes conducted in the presence of hydrogen.
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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 | 0.000 |
| 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 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".