Syngas production via microwave-assisted Dry Reforming of Methane over NiFe/MgAl2O4 alloy catalyst
Bibliographic record
Abstract
• DRM reactions performed under microwave irradiation (MW) using NiFe-MgAl catalysts. • MW power, Ni-Fe quantities and their temperature-response behavior were studied. • Fe species played a pivotal role in conferring microwave receptivity to the catalysts. • NiFe-MgAl catalysts excelled in MW-driven CH 4 -CO 2 reforming for syngas production. Dry reforming of methane (DRM) represents a promising avenue for generating syngas while simultaneously reducing CO 2 emissions. However, its industrial application has been constrained by the necessity for elevated temperatures to prevent coke. Microwave (MW)-assisted DRM emerges as a compelling solution to facilitate high-temperature reactions, capitalizing on surplus renewable electrons to heat the catalyst bed swiftly and selectively, thereby circumventing the inefficient heating of the entire reactor. In this study, DRM is conducted under MW irradiation using NiFe/MgAl 2 O 4 alloy catalysts. The impacts of MW power and catalysts' temperature-response behavior are investigated as well as the active components (Ni and Fe), and space velocity on the DRM reaction are explored. We determined the optimal quantities of Fe and Ni necessary to achieve the desired balance between MW heating and driving the DRM reaction. Under specific conditions—Ni content at 25 wt%, Fe content at 40 wt%, MW power of 286 W g −1 , a temperature of 700 °C, flow rate of 450 mL min −1 and a space velocity of 12857 mL·g −1 ·hr −1 —conversion rates of 85 % for CH 4 and 62 % for CO 2 are achieved. NiFe/MgAl 2 O 4 catalysts demonstrated high potential to be used in the MW-driven DRM as compared to conventional electric heating methods.
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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) | 0.001 | 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".