A Specific Review of CO<sub>2</sub> Catalytic Conversion Reactions Based on the Concept of Catalytic Sites Contiguity
Bibliographic record
Abstract
Abstract Thermocatalytic conversions of carbon dioxide (CO 2 ) to value‐added products offer promising approaches to achieving net negative emissions. The catalysts for CO 2 conversions, particularly for CO 2 hydrogenation reactions, usually involve more than one catalytic sites working together. In this review, we first introduce the advanced characterization techniques used to identify the catalytic sites in CO 2 hydrogenation catalysts, sites for hydrogen (H 2 ) activation and CO 2 adsorption/activation. We then discuss how the dual or multiple‐site configurations influence the catalytic activity and selectivity in reactions such as reverse water‐gas shift (RWGS), CO 2 methanation, and CO 2 hydrogenation for methanol (MeOH). We finally explain the Catalytic Sites Contiguity (CSC) concept that our research group developed from the work in CO 2 reforming of methane and use it to understand the relationship between the spatial arrangement of catalytic sites and the efficiency of reactant activation and conversion in recent publications on MeOH synthesis from CO 2 hydrogenation. We hope our insights into the impact of CSC on catalytic performance lead to a potential top‐down design method in optimizing the CO 2 hydrogenation catalysts.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.004 | 0.003 |
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".