Catalytic Cracking of Hydrocarbons in a CREC Riser Simulator Using a Y-Zeolite-Based Catalyst: Assessing the Catalyst/Oil Ratio Effect
Bibliographic record
Abstract
The present study investigates the effects of the changes of the catalyst to feedstock ratio (C/O) on FCC cracking using a Y-zeolite-based catalyst. Experiments are developed in a CREC Riser Simulator. This bench-scale mini-fluidized batch unit mimics the operating conditions of large-scale FCC units as follows: It uses temperatures ranging from 510 to 550 °C and reaction times from 3 7 s. For every experiment, 0.2 g of 1,3,5-TIPB is contacted with a 0.12–1g catalyst amount. This is done to achieve a C/O ratio in the range of 0.6–5. Experiments show the effects of increasing the C/O ratio on 1,3,5-TIPB conversion, coke formation, and product selectivity. On this basis, a mechanism involving single catalyst sites for cracking and two sites for coke formation is considered. Coke formation is postulated as an additive process involving coke precursor species, which are either adsorbed on sites in the same particle or adsorbed in close sites in different particles. The proposed mechanism helps explain the results obtained, introducing a rationale for the selection of optimum C/O ratios to yield the highest possible 1,3,5-TIPB conversions with controlled amounts of coke formation. It is anticipated that the findings of this study will have a significant influence on the selection of an optimum C/O ratio for the design and operation of the most advanced FCC risers and downers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".