A Combinatorial Ab Initio Study of Methane Dehydroaromatization Pathways on Wurtzite Gallium Nitride
Bibliographic record
Abstract
Methane dehydroaromatization (MDA) offers a direct route for the non-oxidative valorization of methane into aromatic hydrocarbons. Wurtzite gallium nitride has been reported experimentally to catalyze MDA near 450°C, yet the later stages of the reaction remain poorly understood. Here, we developed and applied a high-throughput combinatorial ab-initio framework to propose two thermally accessible MDA pathways on GaN: the C₃+C₃ and C₄+C₂ mechanisms. Methylene and ethylene, which form readily with barriers of 1.79eV and 1.44eV, respectively, emerge as key C₁ and C₂ intermediates. The rate-determining step in the C₃+C₃ pathway is ethyl formation (3.41eV), whereas the C₄ + C₂ route proceeds through a lower-barrier vinyl dehydrogenation (2.89eV) involving strongly bound acetylene intermediates. The unique geometry of the GaN surface, characterized by the spacing and orientation of surface Ga-N bonds, stabilizes both C₃ and C₄ intermediates and promotes the coupling steps that yield benzene. Several thermodynamically stable intermediates may act as kinetic traps, rationalizing observed by-products such as ethylene and cyclohexane. These findings provide a comprehensive mechanistic framework for MDA on GaN and underscore the catalytic potential of non-oxide nitrides for hydrocarbon activation and coupling.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".