Interaction of CO<sub>2</sub>/CH<sub>4</sub>with steel wool in an electrocatalytic dry reforming reactor
Bibliographic record
Abstract
Dry reforming is a process allowing simultaneous conversion of hydrocarbons (methane being the prototype molecule used for this study) to syngas using carbon dioxide as an oxidizing agent. Such strategy may eventually become an opportunity for the industrial sector to produce syngas whilst valorizing residual CO 2 . As reported previously, an iron-based catalyst, i.e. steel wool, activated by an electrical current showed potential for dry reforming. As a follow up to this preliminary work, this study mainly focuses on the characterization of the lowcost thin iron wires in order to determine the robustness and stability of the iron material over extended operation. Under CO 2 /CH 4 molar feed ratios ranging from 0.8 to 1.25, coking is inhibited by high surface temperature. After 25 hours of operation at a temperature higher than 900C measured in the gas phase, XRD patterns show a preserved Fe structure along with FeO suggesting an eased redox cycle with CO 2 and CH 4 . It is also showing that a high CO 2 /CH 4 ratio favors higher oxidation states of the iron in the zone of the iron bed, which is first in contact with the gas input. Decreasing the temperature to 800C favors oxidation by CO 2 over reduction by CH 4 leading to Fe 3 O 4 formation. This disturbs the Joule dissipation through the wire mesh catalyst bed. Although high molar ratios of CO 2 over CH 4 result in fast oxidation of the catalyst, reducing the ratio may lead to increasing the catalyst lifespan which, overall, is essential to scale this process to a commercial scale.
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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 | 0.000 |
| 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".