Hybrid atom transfer radical polymerization system for balanced polymerization rate and polymer molecular weight control
Bibliographic record
Abstract
Abstract A hybrid polymerization system that combines the fast reaction kinetics of conventional free radical polymerization and the control of molecular weight and distribution afforded by ATRP has been developed. High‐free radical initiator concentrations in the range of 0.1–0.2 M were used in combination with a low concentration of ATRP catalyst. Conversions higher than 90% were achieved with ATRP catalyst concentrations of less than 20 ppm within 2 h for the hybrid ATRP system as compared with ATRPs where achieving such conversions would take up to 24 h. These reaction conditions lead to living polymerizations where polymer molecular weight increases linearly with monomer conversion. As in living polymerization and despite the fast rates and low ATRP catalyst concentrations, the polydispersity of the produced polymer remained below 1.30. Chain extension experiments from a synthesized macroinitiator were successful, which demonstrate the living characteristics of the hybrid ATRP process. Catalyst concentrations as low as 16 ppm were found to effectively mediate the growth of over 100 polymer chains per catalytic center, whereas at the same time negating the need for post polymerization purification given the low‐catalyst concentration. © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 48: 2294–2301, 2010
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".