Supramolecular Complexes of Multivalent Cholesterol‐Containing Polymers to Solubilize Carbon Nanotubes in Apolar Organic Solvents
Bibliographic record
Abstract
Copolymers of 2-ethylhexyl acrylate (EHA) and cholesteryloxycarbonyl-2-hydroxymethacrylate (CEM) were prepared by reversible addition-fragmentation chain-transfer (RAFT) polymerization. Supramolecular complexes of these copolymers with carbon nanotubes (CNTs) were soluble in THF, toluene, and isooctane. The colloidal solutions remained stable for months without aggregation. The rationale for the choice of CEM was based on the high adsorption energy of cholesterol on the CNT surface, as computed by DFT calculations. Adsorption isotherms were experimentally measured for copolymers of various architectures (statistical, diblock, and star copolymers), thereby demonstrating that 2-5 cholesterol groups were adsorbed per polymer chain. Once the supramolecular complex had dried, the CNTs could be easily resolubilized in isooctane without the need for high-power sonication and in the absence of added polymer. Analysis by atomic force microscopy (AFM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) indicated that the CNTs were devoid of bundles. The supramolecular complexes could also be employed in an inverse emulsion polymerization of 2-hydroxyethylmethacrylate (HEMA) in isooctane and dodecane, thereby leading to the formation of a continuous polymeric sheath around the CNTs. Thus, this technique leads to the formation of very stable dispersions in non-polar organic solvents, without altering the fundamental properties of the CNTs.
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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 | 0.000 | 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".