Programmed Synthesis of Copolymer with Controlled Chain Composition Distribution via Semibatch RAFT Copolymerization
Bibliographic record
Abstract
It is well-known that controlled/living radical copolymerization (CLRcoP) yields gradient copolymer with the composition varying along chain length. The composition distribution of the as-synthesized product is solely determined by the comonomer reactivity ratios and is thus not well controlled. This work reports the first experimental example of the control over the copolymer composition distribution through semibatch operations. Using styrene (St)/butyl acrylate (BA) as a model system, we synthesized uniform and linear gradient copolymers via semibatch reverse addition−fragmentation chain transfer radical polymerization (RAFT) mediated by benzyl dithioisobutyrate. The comonomer feeding rate profiles for the targeted distributions were designed from a newly developed computer model that was trained from the batch RAFT copolymerizations of St and BA at different monomer compositions. The semibatch copolymerization yielded precise copolymer products having their composition distributions exactly as targeted and the polymerization rate and molecular weight profiles as predicted by the model.
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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) | 0.000 | 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 | 0.000 |
| 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 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".