Kinetic Assessment of the Dry Reforming of Methane over a Solid Solution Ni–La Oxide Catalyst
Bibliographic record
Abstract
The dry reforming of methane is a promising technology for the abatement of CH<sub>4</sub> and CO<sub>2</sub>. Solid solution Ni–La oxide catalysts are characterized by their long–term stability (100h) when tested at full conversion. The kinetics of dry reforming over this type of catalysts has been studied using both power law and Langmuir–Hinshelwood based approaches. However, these studies typically deal with fitting the net CH<sub>4</sub> rate hence disregarding competing and parallel surface processes and the different possible configurations of the active surface. In this work, we synthesized a solid solution Ni–La oxide catalyst and tested six Langmuir–Hinshelwood mechanisms considering both single and dual active sites for assessing the kinetics of dry reforming and the competing reverse water gas shift reaction and investigated the performance of the derived kinetic models. In doing this, it was found that: (1) all the net rates were better fitted by a single–site model that considered that the first C–H bond cleavage in methane occurred over a <a>metal−oxygen </a>pair site; (2) this model predicted the existence of a nearly saturated nickel surface with chemisorbed oxygen adatoms derived from the dissociation of CO<sub>2</sub>; (3) the dissociation of CO<sub>2</sub> can either be an inhibitory or an irrelevant step, and it can also modify the apparent activation energy for CH<sub>4</sub> activation. These findings contribute to a better understanding of the dry reforming reaction's kinetics and provide a robust kinetic model for the design and scale–up of the process.
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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 | 0.000 |
| 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 | 0.001 |
| 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".