A reduced methane pyrolysis mechanism for above-atmospheric pressure conditions
Bibliographic record
Abstract
Methane pyrolysis has recently gained significant attention because of its potential to produce hydrogen without any CO 2 emissions. Modeling a methane pyrolysis reactor requires a detailed multi-step reaction mechanism consisting of the full reaction pathway up to soot formation. Several models have been proposed in the literature; however, they have not been validated and calibrated to above-atmospheric pressure conditions. Due to the high number of parameters, adjusting the current models parameter set to high-pressure requires mechanism reduction and optimization. In this work, an existing methane pyrolysis mechanism consisting of 1516 reactions and 325 species was reduced using the directed relation graph with error propagation within a temperature and pressure range of 1000–1400 K and 0.1–4 atm. A skeletal mechanism consisting of 343 reactions and 60 species was obtained; resulting in a reaction and species reduction ratio of 4.4 and 5.3, respectively. The target species concentrations, namely CH 4 , H 2 , C 2 H 2 , C 2 H 4 , C 2 H 6 , α -C 3 H 4 , p -C 3 H 4 , were found to be in good agreement with the original mechanism predictions. Then, the rate parameters of the reduced mechanism were fitted against in-house experimental data in the temperature range of 892–1292 K and at a pressure of 4 atm to extend the model validity to above atmospheric pressures. The optimized model showed significant improvement in capturing the experimental data profiles compared to the reduced model predictions. A carbon element flux transfer was performed to identify the importance of additional pathways under high-pressure in aiding faster methane decomposition. The proposed model can be used for the accurate prediction of methane pyrolysis products at a wide range of temperatures and pressures. • A reduced and optimized mechanism for high-pressure methane pyrolysis is presented. • The reduced mechanism provides the best initial guess for the optimization. • The improved model accurately predicts the major and minor decomposition products. • Ethylene hydrogenation is sensitive for the model accuracy at low and high-pressures.
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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 | 0.001 |
| 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 | 0.001 |
| 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".