Porosity as a Design Element for Developing Catalytic Molecular Materials for Electrochemical and Photochemical Carbon Dioxide Reduction
Bibliographic record
Abstract
Abstract The catalytic reduction of carbon dioxide (CO 2 ) using sustainable energy inputs is a promising strategy for upcycling of atmospheric carbon into value‐added chemical products. This goal has inspired the development of catalysts for selective and efficient CO 2 conversion using electrochemical and photochemical methods. Among the diverse array of catalyst systems designed for this purpose, 2D and 3D platforms that feature porosity offer the potential to combine carbon capture and conversion. Included are covalent organic frameworks (COFs), metal–organic frameworks (MOFs), porous molecular cages, and other hybrid molecular materials developed to increase active site exposure, stability, and water compatibility while maintaining precise molecular tunability. This mini‐review showcases catalysts for the CO 2 reduction reaction (CO 2 RR) that incorporate well‐defined molecular elements integrated into porous materials structures. Selected examples provide insights into how different approaches to this overall design strategy can augment their electrocatalytic and/or photocatalytic CO 2 reduction activity.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".