<i>n</i>‐butane partial oxidation in a fixed bed: A resolved particle computational fluid dynamics simulation
Bibliographic record
Abstract
Abstract Maleic anhydride (MA) is an important chemical intermediate, which is mainly produced by the highly exothermic partial oxidation of n‐butane in fixed bed reactors. Production of maleic anhydride is limited by problems of temperature control and loss of selectivity. Here we present three‐dimensional resolved‐particle computational fluid dynamics (CFD) simulations of n‐butane partial oxidation in a randomly packed bed of 807 spherical catalyst particles. We used a semi‐empirical two‐site surface mechanism from the literature and obtained distributions of temperature, gas phase species, and surface species in the bed. The local selectivity patterns are strongly controlled by the changes in the gas phase flow field, the temperature in the fixed bed, and the weakly adsorbed oxygen surface coverage fraction (λO) profiles inside the particles. Most of the selectivity loss due to product combustion happens in the interior of the catalyst particles, as opposed to the production of MA, which is mainly in the near‐surface layers. We observed loss of selectivity and yield in the centre of the bed at increased bed depths, because of the temperature increase and decrease in gas phase oxygen there. The simulations show sharp λO gradients inside the particles. Near the cooled tube wall λO is strongly affected by the temperature, while at the bed centre gas phase oxygen diffusion limitations contribute to a depleted oxygen surface resulting in lower selectivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".