Multi‐stimuli‐responsive self‐immolative polymer assemblies
Bibliographic record
Abstract
ABSTRACT Self‐immolative polymers (SIPs) undergo depolymerization in response to the cleavage of stimuli‐responsive end‐caps from their termini. Some classes of SIPs, including polycarbamates, have depolymerization rates that depend on environmental factors such as solvent and pH. In previous work, hydrophobic SIPs have been incorporated into amphiphilic block copolymers and used to prepare nanoassemblies. However, stimuli‐responsive hydrophilic blocks have not previously been incorporated. In this work, we synthesized amphiphilic copolymers composed of a hydrophobic polycarbamate SIP block and a hydrophilic poly(2‐(dimethylamino)ethyl methacrylate) (PDMAEMA) block connected by a UV light‐responsive linker end‐cap. It was hypothesized that after assembly of the block copolymers into nanoparticles, chain collapse of the PDMAEMA above its lower critical solution temperature (LCST) might change the environment of the SIP block, thereby altering its depolymerization rate. Self‐assembly of the block copolymers was performed, and the depolymerization of the resulting assemblies was studied by fluorescence spectroscopy, dynamic light scattering, and NMR spectroscopy. At 20 °C, the system exhibited a selective response to the UV light. At 65 °C, above the LCST of PDMAEMA, the systems underwent more rapid depolymerization, suggesting that the increase in rate arising from the higher temperature dominated over environmental effects arising from chain collapse. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018, 56, 1868–1877
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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".