Separation of Toluene-Insoluble Solids in the Slurry Oil from a Residual Fluidized Catalytic Cracking Unit: Determination of the Solid Content and Sequential Selective Separation of Solid Components
Bibliographic record
Abstract
Removing solid impurities inside slurry oil from residual fluidized catalytic cracking (RFCC) is critical for efficient use of its aromatic hydrocarbons, and selective separation of the solid components is also an important issue of recycling valuable resources for catalyst and carbon material. Different separation methods were employed to isolate the solids and their components in the slurry oil from a RFCC unit, and the resultant solids and components were comprehensively characterized by elemental analysis, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electronic microscopy (SEM), and energy-dispersive X-ray (EDX) analysis, etc. Results show that the content of toluene-insoluble solids in the slurry oil varies from separation methods employed. The solid components, i.e., catalyst particles and coke powders, can be sequentially separated, and the choice of an appropriate separation method is critical for accurate determination of the solid content in a RFCC slurry oil. When an aliphatic solvent is used for dilution and, after filtering, an aromatic solvent is employed for extraction, the solids can be completely separated and the total content of toluene-insoluble solids is thus obtained. Also, selective separation of the two major components of the solid has also been established. When the slurry oil is digested with hot toluene, followed by filtration and extraction with hot toluene, catalyst particles can be separated at a selectivity of 71.0 wt %. Afterward, when the filtrate is digested with a substantially aliphatic solvent, followed by filtration and extraction with hot toluene, fine coke powders are separated at a selectivity of 96.9 wt %. This selective separation opens a possible way to recover catalyst and obtain fine coke powders as valuable resources from a single RFCC slurry oil. At the same time, the slurry oil may thus be highly clarified, which might find a variety of flexible applications. Finally, the mechanism for particle aggregation and clustering for the efficient separation of solids from heavy oils, such as slurry oil from a fluidized catalytic cracking (FCC)/RFCC unit, has been postulated, where upon adding an aliphatic solvent, heavy asphaltenes precipitate to be adsorbed on the surfaces of fine particles and function as natural binders to aggregate and cluster the fine particles, rendering separation of nanosized coke fines possible.
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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) | 0.000 | 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".