Plug-and-Play Heterogeneous Catalysis Enabled by Metal–Organic Cage-Crosslinked Polymers
Bibliographic record
Abstract
The immobilization of homogeneous catalysts onto solid supports to improve recyclability while maintaining catalytic efficiency is often a trial-and-error process limited by poor control of the local catalyst environment and a lack of modular strategies to append catalysts to support materials. Here, we introduce a “plug-and-play” heterogenous catalysis platform that overcomes these challenges. Our approach leverages the well-defined interiors of self-assembled Pd12L24 metal–organic cages/polyhedra (MOCs): through a simple combination of catalyst-ligands, polymeric ligands, and spacer ligands, we demonstrate facile self-assembly of a diverse range of polymer gels featuring endohedrally-catalyst-functionalized junctions. Through decoupling catalyst incorporation and environment from the physical properties of the support (polymer matrix), this simple strategy is shown to enhance the recyclability of various catalyst systems (e.g., TEMPO-catalyzed oxidation and Au(I)-catalyzed cyclization) and enable catalysis in environments where homogeneous catalyst analogs are not viable.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".