Molecularly Imprinted Polymeric Nanospheres by Diblock Copolymer Self-Assembly
Bibliographic record
Abstract
Novel molecularly imprinted polymeric nanospheres (MIPNs) were prepared combining both molecular imprinting and block copolymer self-assembly techniques. A diblock copolymer, poly[( tert -butyl methacrylate)- block -(2-hydroxylethyl methacrylate)] (PtBMA- b -PHEMA), was synthesized by living free radical polymerization. Further postfunctionalization introduced 2-acrylamido-6-carboxylbutylamidopyridine (ACAP) and cross-linkable methacryloyl side groups into the polymer. The resulting final diblock copolymer was able to interact with 1-alkyluracil or 1-alkylthymine derivatives in chloroform to form triple hydrogen bonding complexes. Addition of cyclohexane, a block selective solvent, to this solution produced spherical micelles with uracil or thymine compounds embedded within the core, which was cross-linked in the solution in order to lock-in the MIP structures. The cross-linking has also made the core−shell structure of the micelle particles sufficiently stable for the subsequent extraction and rebinding process, which was confirmed by TEM and FTIR study. After cross-linking and extraction, these uniform nanospheres showed good dispersibility in organic solvents and demonstrated specific rebinding preponderancies to the target molecules of nucleotide bases, uracil, or thymine compounds. Comparing with the traditional bulk MIPs, these MIPNs demonstrated higher rebinding capacities and comparable size and shape selectivity.
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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) | 0.000 | 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".