Kinetic Modeling of Ethane Oxidative Dehydrogenation over VO<sub><i>x</i></sub>/Al<sub>2</sub>O<sub>3</sub>Catalyst in a Fluidized-Bed Riser Simulator
Bibliographic record
Abstract
This study reports kinetic modeling of ethane oxidative dehydrogenation (ODH) under an oxygen-free atmosphere employing a catalyst of 10 wt % VO x supported on c-Al 2 O 3 . The 10 wt % VO x /Al 2 O 3 catalyst is a stable catalyst over repeated reduction and oxidation cycles, having high dispersion of VO x on the support surface. Kinetic experiments are carried out in the CREC Fluidized Bed Riser Simulator at 550–600 °C and atmospheric pressure. Ethane ODH experiments are developed at 550, 575, and 600 °C, with three experimental repeats per condition; this shows that the prepared catalyst displays 6.5%–27.6% ethane conversion and 57.6%–84.5% ethylene selectivity. Under oxygen-free conditions, the oxygen from the catalyst lattice is consumed by ODH. Therefore, the oxygen availability is expressed as the extent of catalyst oxidation during the experiment. Changes in the extent of oxidation are described using an exponential decay function based on ethane feed conversion. On the basis of the data obtained, a kinetic model is proposed in which each reaction rate is related to the catalyst oxidation extent. The kinetic and decay model parameters are estimated using regression analysis. Activation energies and Arrhenius pre-exponential constants are calculated with their respective confidence intervals. The proposed series-parallel kinetic model satisfactorily predicts the ODH reaction of ethane under the selected reaction conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".