Promoter Impact on 5Ni/SAPO-5 Catalyst for H2 Production via Methane Partial Oxidation
Bibliographic record
Abstract
Compared to steam reforming techniques, partial oxidation of methane (POM) is a promising technology to improve the efficiency of synthesizing syngas, which is a mixture of CO and H2. In this study, partial oxidation of methane (POM) was used to create syngas, a combination of CO and H2, using the SAPO-5-supported Ni catalysts. Using the wetness impregnation process, laboratory-synthesized Ni promoted with Sr, Ce, and Cu was used to modify the SAPO-5 support. The characterization results demonstrated that Ni is appropriate for the POM due to its crystalline structure, improved metal support contact, and increased thermal stability with Sr, Ce, and Cu promoters. During POM at 600 °C, the synthesized 5Ni+1Sr/SAPO-5 catalyst sustained stability for 240 min on stream. While keeping the reactants stoichiometric ratio of (CH4:O2 = 2:1), the addition of Sr promoter and active metal Ni to the SAPO-5 increased the CH4 conversion from 41.13% to 49.11% and improved the H2/CO ratio of 3.33. SAPO-5-supported 5Ni+1Sr catalysts have great potential for industrial catalysis owing to their unique combination of several oxides. This composition not only boosts the catalyst’s activity but also promotes favorable physiochemical properties, resulting in improved production of syngas. Syngas is a valuable intermediate in various industrial processes.
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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".