Termination of Surface Radicals and Kinetic Modeling of ATRP Grafting from Flat Surfaces by Addition of Deactivator
Bibliographic record
Abstract
Surface-initiated controlled radical polymerization has been widely used for grafting polymers from various surfaces. However, how the surface-constrained radicals are terminated remains to be further elucidated. In this work, a simple kinetic model is developed for surface-initiated atom transfer radical polymerization (SI-ATRP) with addition of excess deactivator in solution. The model describes the development of polymer layer thickness, as well as the concentrations of radical, dormant and dead chains. A simple but accurate analytical solution is obtained for the polymer layer thickness as a function of time. The model accounts for the effects of equilibrium constant, activator/deactivator concentration ratio, monomer concentration, grafting density and rate constants of propagation and termination. The model is verified with the experimental data of 2-methacryloyloxythyl phosphorylcholine (MPC), methyl acrylate, acrylamide, and N -isopropylacrylamide under various conditions. In correlating thickness versus time experimental curves at different catalyst concentrations, it is clearly demonstrated that the termination of radicals on surface is facilitated by diffusion of catalyst species in solution. Although radical chains are immobilized, radical centers “migrate” and terminate through activation and deactivation reactions. The termination rate constant is therefore proportional to catalyst concentration. It is also found that the termination is influenced by chain conformation and the rate constant is grafting density dependent.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".