A review on catalyst development for conventional thermal dry reforming of methane at low temperature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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