Synthesis of Fluorine‐Containing Molecular Rotors and Their Assembly on Gold Nanoparticles
Bibliographic record
Abstract
Abstract A series of eight rotors containing thiol groups for attachment to gold surfaces and fluorine atoms for solid‐state 19F NMR spectroscopy have been prepared through linear, multistep synthesis. The common rotating part of the rotors (rotator), consisting of a 2,6‐difluorobenzene moiety, is introduced into the rotor structure through an unusual regioselective Sonogashira coupling with 2,6‐difluoro‐1,4‐diiodobenzene. Rotors with different bulky trityl headgroups were prepared, along with their linear, less hindered analogues. These molecular rotors were assembled on gold nanoparticles (AuNPs) and preliminary characterization was performed on these AuNPs in order to study the effects of the sizes of the molecules on the packing behaviour on the AuNP surfaces. As expected, we found that linear molecules adopt more closely packed structures on the surfaces than their bulky analogues. This offers a very promising opportunity to study rotation dynamics at the molecular level by solid‐state NMR spectroscopy.
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 | 0.001 |
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".