TiO<sub>2</sub>–SiO<sub>2</sub>-Composite-Supported Catalysts for Residue Fluid Catalytic Cracking Diesel Hydrotreating
Bibliographic record
Abstract
Composites of TiO 2 –SiO 2 oxides (CTS) with various Ti/Si atomic ratios were prepared by the sol–gel method, and the CO 2 supercritical fluid extraction method was used to remove solvent in the gel. The effects of the Ti/Si atomic ratio and calcination temperature on the specific surface area, pore structure, acidity, and coordination status of the Ti atoms were investigated by N 2 desorption, pyridine adsorption, X-ray diffraction (XRD), and X-ray absorption fine structure (XAFS), respectively. Hydrotreating catalysts were prepared with cobalt (Co)–molybdenum (Mo) and nickel (Ni)–tungsten (W) as active metal components supported on CTS-1 and CTS-4, respectively. The hydrotreating activities of the catalysts were tested by processing residue fluid catalytic cracking (RFCC) diesel on a fixed-bed reactor. It was found that hydrodesulfurization (HDS), hydrodenitrogenation (HDN), and hydrodearomatization (HDA) were affected by the acidity of the support and/or catalyst, which was related to the Ti/Si atomic ratio. The catalysts with strong Lewis acidity had better hydrotreating activities for HDS, HDN, and HDA. The study provides insight into a fundamental understanding of the relationship between the Ti/Si atomic ratio of the support and acidity of catalysts and the effect of acidity on the hydrotreating activity of the catalyst.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".