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Record W4416390594 · doi:10.1021/acs.jpcc.6c02699

Ab Initio Insights into the Early Stages of Methane Dehydroaromatization on Gallium Nitride

2025· article· en· W4416390594 on OpenAlexafffund
Sylvester Zhang, Peter H. McBreen, Chao‐Jun Li, Rustam Z. Khaliullin

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsUniversité LavalMcGill University
FundersFonds de recherche du Québec – Nature et technologies
KeywordsMethaneAb initioGallium nitrideDehydrogenationCatalysisHydrogenDensity functional theoryGalliumHeterogeneous catalysis

Abstract

fetched live from OpenAlex

Methane dehydroaromatization (MDA) offers a promising non-oxidative route for converting methane into value-added aromatic hydrocarbons. Wurtzite gallium nitride (GaN) has demonstrated catalytic activity for this transformation at temperatures as low as 450°C, although the underlying mechanism remains incompletely understood. In this study, the initial steps of MDA on the GaN m-plane surface were investigated using density functional theory. A low-barrier pathway for methylene (CH₂) formation was identified, enabled by the migration of surface methyl and hydrogen species with similarly low barriers. This mechanism significantly lowers the activation barrier relative to previous estimates. Beyond dehydrogenation and migration, we examined the coupling of C₁ intermediates to form C₂ species, including ethyl, ethane, and ethylene. C-C bond-formation steps leading to ethane and ethylene were found to proceed with barriers comparable to that of CH₂ formation. These results indicate that methane activation on GaN is not governed by a single high-barrier step; instead, dehydrogenation, migration, and coupling each contribute comparable kinetic bottlenecks. Overall, the findings revise the mechanistic understanding of methane activation on GaN and underscore the importance of site availability and adsorbate mobility in enabling selective low-temperature reactivity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.246
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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