Factors Affecting Grafting Density in Surface‐Initiated ATRP: A Simulation Study
Bibliographic record
Abstract
In surface‐initiated atom transfer radical polymerization, knowledge of grafting density is of significant interest because it is one of the determining properties of grafted polymer. It is well known that not all of the immobilized initiators can grow into polymer chains. However, little is known about why this happens and what affects the grafting efficiency. The lack of information is partly due to the difficulty in experimental determination of grafting density on flat substrates. To circumvent the problem, Monte Carlo simulation with bond fluctuation model is used in this study to investigate the effects of various reaction conditions on the grafting density. The simulation results show lower grafting density when less deactivator is present. In systems with lower deactivator concentration, the number of monomer added per activation cycle is higher. Coupling this with close proximity of immobilized initiators results in chains initiated at earlier time to shield their neighboring initiator moieties from adding monomers, thus lowering the grafting density in such a system. These simulation results also provide an explanation to the seemingly conflicting trend reported in the literatures. image
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".