Role of Active Site and CO<sub>2</sub>‐Interacting Surface Species in Dry Reforming of Methane over Strontium Promoted Ni Catalyst Supported by Lanthanum‐Zirconia
Bibliographic record
Abstract
Abstract In the context of global warming, the dry reforming of methane (DRM) has gained significant attention due to its ability to simultaneously deplete two greenhouse gases, i. e. CH4 and CO2, and generate syngas. Herein, strontium‐promoted Lanthanum‐zirconia supported Ni catalysts are investigated for DRM and characterized by X‐ray diffraction, surface area and porosity, FTIR‐RAMAN spectroscopy, and temperature‐programmed experiments. The Ni/LaZr catalyst contains formate and oxycarbonate‐like CO2‐interacting species, while strontium‐promoted catalysts have additional ionic CO32− species. The current catalyst system of 2 % strontium‐promoted Ni/LaZr has active sites derived from three types of NiO: easily reducible, moderately interacted, and strongly interacted. During the DRM reaction over the current system, CO2 is a better oxidant than O2 for removing carbon deposits. Additionally, the catalysts attain higher reducibility under oxidizing gas (CO2) and reducing gas (H2) during the DRM reaction. For optimal hydrogen yield of approximately 60 % within 420 minutes of operation over Ni2Sr/LaZr catalyst, a balance between the population of active site Ni and CO2‐interacting surface species is necessary.
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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".