Preparation and Evaluation of the Composite Containing USL Zeolite-Supported NiW Catalysts for Hydrotreating of FCC Diesel
Bibliographic record
Abstract
Two different ways, including an in situ synthetic method and a mechanical mixing method, were used to combine zeolite USL (ultra stable L) with alumina for preparation of a new composite support material of hydrotreating catalyst. The physicochemical properties of samples were characterized by means of XRD, N 2 physisorption, SEM, FT-IR, 27 Al MAS NMR, NH 3 -TPD, H 2 -TPR, and UV−vis DRS. Composite supports containing different contents of zeolite USL and Al 2 O 3 were prepared by in situ synthetic method based on a modified pH-swing method, which showed a higher specific surface area, pore volume, as well as average pore diameter compared with the supports prepared via a mechanical mixing method. Corresponding NiW/γ-Al 2 O 3 −USL series catalysts were obtained by the incipient-wetness impregnation method, and the activities of these catalysts for FCC diesel hydrodesulfurization (HDS) and hydrodenitrogenation (HDN) were evaluated in a high-pressure microreactor system. The assessment results indicated that the catalyst with 10 m% USL in the support prepared by the in situ method showed the highest HDS and HDN conversions, which reached a maximum of 99.3% and 94.1% for HDS and HDN, respectively. In addition, the swing pH method plays an important role in preparation of the Al 2 O 3 support, and NiW/γ-Al2O3(P) (prepared by the swing pH method) catalyst also gave better performance for the HDS and HDN of diesel oil. These activities were much higher than those over a kind of industrial catalyst of RN10 and were also better than the corresponding catalyst in which the support was obtained by the mechanical mixing method.
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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".