A review on catalyst development for conventional thermal dry reforming of methane at low temperature
Bibliographic record
Abstract
Abstract Carbon dioxide (CO 2 ) utilization and conversion, as one of the main parts of carbon capture, utilization, and storage (CCUS), is not only considered an important way to mitigate global warming but also an attractive industrial route to produce valuable fuels and chemical feedstocks. Catalytic dry reforming of methane (DRM) is a promising technology for carbon dioxide utilization and conversion as it can produce syngas, carbon monoxide (CO), and hydrogen (H 2 ) for widespread industrial production processes. In most studies of the DRM reaction, a relatively high operational temperature (i.e., >700°C) has been applied since the reactivity limitation of widely used Ni‐based catalysts at low temperatures and the extremely endothermic property of the DRM reaction. However, high cost and high requirement of thermal stability for catalysts have become a severe problem impeding the further commercialization of DRM technology. Decreasing the operational temperature (i.e., <700°C) is considered a promising way for further application of the DRM route to convert CO 2 and produce syngas. However, traditional Ni‐based catalysts suffered from unsatisfied reactivity and severe coke formation, leading to quick deactivation at low temperatures. Developing a catalyst with excellent catalytic activity, coke resistance, and improved thermal stability is necessary for low‐temperature DRM reactions. In recent years, with significant development in materials, catalyst design, and computational simulation, some synthesized catalysts have achieved considerable improvement in catalytic performance in low‐temperature DRM. Hence, a review of recent development on low‐temperature DRM catalysts is provided here to further guide and profoundly understand catalyst design for low‐temperature DRM.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".