“Click” methodologies: efficient, simple and greener routes to design dendrimers
Bibliographic record
Abstract
Designing dendrimers that are monodisperse hyperbranched macromolecules and offer significant potential in numerous scientific fields, is becoming a major topical area in modern research. Among the challenges of the 21st century, synthetic methodologies that increase efficiency of conversion and a greener chemistry approach, are expected to lead the way in the quest to build novel nanomaterials. The recent entry of so-called "click" reactions that include Diels-Alder, Cu(I)-catalyzed Huisgen cycloaddition and thiol-ene coupling, have generated real stimulus not only in developing elegant materials of choice, but also in making the leap to industrial scale build-up of dendritic macromolecules. This tutorial review takes on the task of demonstrating the simplicity of these "click" reactions and the advantages they offer from a synthetic view point in developing mono- to multifunctional dendrimers. A brief introduction to "click" chemistry is followed by a chronological survey of developments in the field, and the impact these have had in designing novel dendritic macromolecules. The review is intended to introduce scientists to these highly efficient methodologies with demonstrated potential, and provide impetus for further growth of the area.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".