A Fluidizable Catalyst for N-Butane Oxidative Dehydrogenation under Oxygen-Free Reaction Conditions
Bibliographic record
Abstract
This study evaluates the effectiveness of fluidizable VOx/MgO-γAl2O3 catalysts for C4-olefin production via n-butane oxidative dehydrogenation (BODH). Catalysts were prepared via vacuum incipient wetness impregnation and then characterized by employing several techniques such as BET (Brunauer–Emmett–Teller) method, XRD (X-ray diffraction), LRS (laser Raman spectroscopy), XPS (X-ray photoelectron spectroscopy), TPR/TPO (temperature-programmed reduction/temperature-programmed oxidation), NH3-TPD (temperature-programmed desorption), NH3 -desorption kinetics and pyridine-FTIR. The BET analysis showed the prepared catalysts’ mesoporous structure and high surface areas. The XRD, LRS and XPS established the desirable presence of amorphous VOx phases. The TPR/TPO analyses corroborated catalyst stability over repeated reduction and oxidation cycles. The NH3-TPD and NH3 desorption kinetics showed that the catalysts had dominant moderate acidities and weak metal-support interactions. In addition, Pyridine-FTIR showed the critical influence of Lewis acidity. The VOx/MgO-γAl2O3 catalysts were evaluated for BODH using a fluidized CREC Riser Simulator, operated under gas-phase oxygen-free conditions, at 5 to 20 s reaction times, and at 450 °C to 600 °C temperatures. The developed VOx/MgO-γAl2O3 catalysts demonstrated performance stability throughout multiple injections of butane feed. Catalyst regeneration was also conducted after six consecutive BODH runs, and the coke formed was measured using TOC (Total Organic Carbon). Regarding the various BODH catalyst prepared, the 5 wt% V-doped MgO-γAl2O3 yielded in a fluidized CREC Riser Simulator the highest selectivity for C4-olefins, ranging from 82% to 86%, alongside a butane conversion rate of 24% to 27%, at 500 °C and at a 10 s reaction time.
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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 | 0.000 |
| 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 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".