Synthesis of Poly(<i>N</i>,<i>N</i>-dimethylacrylamide) Brushes from Charged Polymeric Surfaces by Aqueous ATRP: Effect of Surface Initiator Concentration
Bibliographic record
Abstract
We have synthesized polystyrene shell latex (PSL) surfaces with different initiator concentrations by changing the feed ratio of styrene to 2-(methyl-2‘-chloropropionato)ethyl acrylate ( HEA−Cl) in a series of shell-growth copolymerization reactions. Surfaces were characterized by conductometric titration of saponified and nonsaponified functionalized PSL to give the surface charge and initiator concentrations accessible to aqueous reagents and by 1 H NMR methods. Poly( N, N -dimethylacrylamide) brushes were grafted from the functionalized surfaces by aqueous atom transfer radical polymerization and the dependence of molecular weight and chain density determined as a function of monomer concentration, ligand type, and surface initiator concentration by analyzing the chains cleaved from the PSL by saponification. M n varies linearly with monomer concentration for most systems, and grafting density is roughly independent of monomer concentration except at the highest initiator concentration. Very high molecular weights were obtained at low initiator concentration, up to M n ∼ 1.2 × 10 6 with M w / M n < 1.3; chain separations down to 1.1 nm and brush thicknesses to ∼800 nm were found. Grafting density varies as (initiator surface concentration) 2.6 . The surface charge density also varies among the latexes synthesized and seems to play a role in this strong dependence on surface initiator concentration, perhaps by partially immobilizing the positively charged catalyst complex.
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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 | 0.001 |
| 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".