Cost-Effective Single-Step Synthesis of Metal Oxide-Supported Ni Catalyst for H2-Production Through Dry Reforming of Methane
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Bibliographic record
Abstract
Abstract Preparing catalysts from cheap metal precursors in a single pot are an appealing method for reducing catalytic preparation costs, minimizing chemical waste, and saving time. With regards to the catalytic conversion of dry reforming of methane, it offers the prospect of significantly reducing the cost of H 2 production. Herein, NiO-stabilized metal oxides like Ni/TiO 2 , Ni/MgO, Ni/ZrO 2 , and Ni/Al 2 O 3 are prepared at two different calcination temperatures (600 °C and 800 °C). Catalysts are characterized by X-ray diffraction, Raman spectroscopy, surface area-porosity analysis, Temperature program experiments, infrared spectroscopy, and thermogravimetry analysis. The MgO-supported Ni catalyst (Ni/MgO-600), ZrO 2 -supported Ni catalyst (Ni/ZrO 2 -600), and Al 2 O 3 -supported Ni (Ni/Al 2 O 3 -600) catalyst calcined at 600 °C show initial equal H 2 yields (~ 55%). The population of CH 4 decomposition sites over ZrO 2 -supported Ni catalyst remains highest, but H 2 -yield drops to 45% against high coke deposition. The catalytic activity remains constant over the Ni/MgO-600 catalyst due to the enrichment of “surface interacted CO 2 -species”. MgO-supported Ni catalyst calcined at 800 °C undergoes weak interactions of NiO-M′ (M′ = support), serious loss of CH 4 decomposition sites and potential consumption of H 2 by reverse water gas shift reaction, resulting in inferior H 2 yield. H 2 -yield remains unaffected over an Al 2 O 3 -supported Ni catalyst even against the highest coke deposition due to the formation of stable Ni (which exsolves from NiAl 2 O 4 ) and proper matching between carbon formation and rate of carbon diffusion.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it