Oxidative Desulfurization of Heavy Gas Oil over a Ti–TUD-1-Supported Keggin-Type Molybdenum Heteropolyacid
Bibliographic record
Abstract
Catalytic oxidative desulfurization (ODS) is emerging as a potential alternative to deep hydroprocessing as a result of its milder operating conditions and no hydrogen requirements. In this study, ODS catalysts based on a mesoporous TUD-1 support were developed to overcome the diffusion limitation of zeolite-based catalysts in oxidizing large-size organosulfur compounds present in real petroleum feedstocks. Different mesoporous oxidation catalysts were formed by substituting Ti in the TUD-1 framework and impregnating Keggin molybdenum heteropolyacid (HPA) on the TUD-1 support. The mesoporosity of TUD-1 and the presence of Ti(IV) and Mo Keggin units in the prepared catalysts were confirmed from the characterization results of X-ray diffraction, X-ray photoelectron spectroscopy, X-ray absorption near edge structure, and Brunauer–Emmett–Teller N2 surface area analyses. The ODS performance of catalysts was studied using a mild hydrotreated bitumen-derived heavy gas oil feedstock. The HPA-dispersed Ti–TUD-1 catalyst was found to be most active for desulfurizing the heavy gas oil feedstock as a result of a strong synergy effect of Ti and Mo Keggin ions on catalyzing oxygen transfer from an oxidant to a substrate. Oxidants, such as hydrogen peroxide, cumene hydroperoxide, tert-butyl hydroperoxide, and molecular oxygen, were screened in this study. The first two oxidants were better than others and equally efficient. The HPA/Ti–TUD-1 catalyst was found to be suitable for ODS and oxidative denitrogenation (ODN) in both the batch stirred-tank reactor and continuous fixed-bed reactor systems.
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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 | 0.001 |
| 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".