Supramolecular Chemistry of Polymer-Based Molecular Tweezers: A Minireview
Bibliographic record
Abstract
Polymer-based molecular tweezers have emerged as a prominent research area due to their enhanced ability to form host–guest complexes, driven by advancements in their design and synthesis. The impact of the spacer structure on the tweezers is predominant. They can be rigid, flexible, and stimuli-responsive. Herein, a new generation of molecular tweezers is introduced as polymer-based molecular tweezers. The integration of molecular tweezers onto biopolymers has significantly expanded their potential applications, making them promising candidates, especially in drug delivery, owing to their biocompatibility, adaptive structural features, and versatile interaction capabilities. The unique structure of polymer-based molecular tweezers, particularly when integrated with biopolymers, creates a unique nano-environment that enhances their interaction with guest molecules. This minireview focuses on the synthesis and applications of polymer-based molecular tweezers and examines how the incorporation of various spacers affects their binding affinity and specificity. These features highlight the advancement of these polymer-based systems, emphasizing their potential applications, particularly in drug delivery, water treatment technology, and future research opportunities.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".