Modeling analysis of chain transfer in reversible addition‐fragmentation chain transfer polymerization
Bibliographic record
Abstract
Abstract The validity of simplifying the reversible addition‐fragmentation chain transfer (RAFT) polymerization as a degenerative chain transfer process was verified in this work. The simplified chain transfer mechanism enabled the direct modeling investigation of chain transfer coefficient in the RAFT polymerization. It also gave the analytical expressions for concentration, chain length, and polydispersity of various chain species. The comparison between the simulations based on chain transfer mechanism and those from general RAFT mechanism showed that this simplified mechanism can accurately predict RAFT polymerization in the absence of side reactions to adduct radicals other than fragmentation. However, significant errors are introduced at high conversion when side reactions to adduct are present. The chain transfer coefficient of RAFT agent is the key factor in RAFT polymerization. The polydispersity is more sensitive to chain transfer coefficient at low conversion. At high conversion, however, the polydispersity is mainly determined by termination, which can be controlled by RAFT agent concentration and the selection of initiator. At last, an analytical equation is derived to directly estimate chain transfer coefficient of RAFT agent from the experimental data. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".