MOCOFs: Crystalline porous frameworks based on double extension of metal–organic and covalent organic linkages
Bibliographic record
Abstract
Reticular chemistry is a powerful strategy to design solid materials with fine-tuned chemical functionality and porosity, such as metal–organic frameworks (MOFs) and covalent organic frameworks (COFs). While MOFs typically show high crystallinity due to their highly reversible coordinative bonds, the organic backbone of COFs provides high chemical stability. Here, we combine the best of both worlds by introducing metal–organic–covalent–organic frameworks (MOCOFs), a new class of reticular materials through the double extension of metal–organic and covalent organic linkages. Several MOCOFs are obtained by the reactions between a cobalt aminoporphyrin and dialdehydes, which are interconnected by cobalt–amine coordination and imine condensation to form 3D networks. The MOCOFs show an unprecedented chiral topological net, large surface area, high crystallinity, and chemical stability owing to the two types of extended linkages. Thus, MOCOFs present a new reticular design strategy that further diversifies the chemical and structural space of porous solids.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".