Effect of Metal–Support Interface During CH<sub>4</sub>and H<sub>2</sub>Dissociation on Ni/γ-Al<sub>2</sub>O<sub>3</sub>: A Density Functional Theory Study
Bibliographic record
Abstract
Methane and hydrogen dissociation are important reactions in carbon nanotube (CNT) and hydrogen production. Although there is extensive literature on theoretical studies for CH 4 and H 2 dissociation on Ni, little is known about the effect of the oxide support, especially the metal–support interface, on the dissociation properties of CH 4 and H 2 . In this study, the dissociations of CH 4 and H 2 on Ni cluster supported on γ-alumina were investigated using density functional theory (DFT) calculations. Two systems: Ni 4 cluster supported on the spinel model of γ-Al 2 O 3 (100) surface, S(Ni 4 ), and on the nonspinel model of γ-Al 2 O 3 (100) surface, NS(Ni 4 ), have been used to model Ni 4 /γ-Al 2 O 3 . For both models, it was found that CH 4 and H 2 dissociations are kinetically preferred at the Ni 2 site located at the nickel–alumina interface when compared with the top of the Ni cluster. Also, the study of CH 3 and H adsorption on different sites of the S(Ni 4 ) and NS(Ni 4 ) show that CH 3 and H bonded with the Ni 2 atom at Ni 4 /γ-Al 2 O 3 interface are more stable than at the top site adsorption. Moreover, the calculation of the metal–support interaction indicates that molecular adsorption on the Ni particle weakened its interaction with the oxide. Hirshfeld charge analysis showed that the surface Al atom works primarily as a charge donation partner when CH 3 and H are bonded with the Ni 2 atom at the interface. This also resulted in an upshift of the d-orbital around the Fermi energy of the Ni 2 atom, which finally stabilized the interface adsorption by this Al (donor)–Ni–adsorbates (acceptor) effect. The results obtained from the DFT calculations indicate that the metal–oxide interface plays an essential role in the dissociation of CH 4 and H 2 .
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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 | 0.000 | 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) | 0.002 | 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".