Synthesis of Dense and Chiral Dendritic Polyols Using Glyconanosynthon Scaffolds
Bibliographic record
Abstract
Most classical dendrimers are frequently built-up from identical repeating units of low valency (usually AB2 monomers). This strategy necessitates several generations to achieve a large number of surface functionalities. In addition, these typical monomers are achiral. We propose herein the use of sugar derivatives consisting of several and varied functionalities with their own individual intrinsic chirality as both scaffolds/core as well as repeating units. This approach allows the construction of chiral, dense dendrimers with a large number of surface groups at low dendrimer generations. Perpropargylated β-D-glucopyranoside, serving as an A5 core, together with various derivatives, such as 2-azidoethyl tetra-O-allyl-β-D-glucopyranoside, serving as an AB4 repeating moiety, were utilized to construct chiral dendrimers using "click chemistry" (CuAAC reaction). These were further modified by thiol-ene and thiol-yne click reactions with alcohols to provide dendritic polyols. Molecular dynamic simulation supported the assumption that the resulting polyols have a dense structure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".