Investigating CO<sub>2</sub> Methanation on Ni and Ru: DFT Assisted Microkinetic Analysis
Bibliographic record
Abstract
Abstract A multiscale analysis combining density functional theory (DFT) and microkinetic modeling is performed to resolve the uncertainties in CO2 methanation reaction mechanism and kinetics on popular Ni and Ru catalysts. The most debated issues are the activation routes of CO2 and CO (hydrogenation or direct dissociation) and whether the reaction proceeds with or without forming a CO* intermediate. We investigated a comprehensive reaction network of 46 elementary reactions, involving multiple CO2, CO activation routes and side reactions using a benchmarked DFT functional. Our study shows that the dominant pathway at 550 K and 10 atm includes direct dissociation of CO2* to CO* on both Ni and Ru surfaces. On Ru, CO* undergoes hydrogenation to form COH* that further dissociates to C*, whereas on Ni, HCO* is formed that gives CH* upon dissociation. The rate determining steps on Ni and Ru are HCO* dissociation to CH* and O* and CH3* hydrogenation to CH4, respectively. We further find that selectivity of the reaction on Ni is higher than that on Ru, whereas activity of Ru is higher.
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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 | 0.000 | 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".