Scalable Routes to Acrylate and Methacrylate Block Copolymers via Copper-Mediated Reversible Deactivation Radical Polymerization
Bibliographic record
Abstract
Cu-mediated reversible deactivation radical polymerization (RDRP) is investigated as a method to produce (meth)acrylic polymers of high chain-end functionality and well-defined structure, enabling the production of uniform block copolymer materials. The use of inexpensive reagents with scale-appropriate reactor configurations is a key feature in overcoming the hurdles to commercialization. Using methyl acrylate (MA) as a model system, reaction conditions and feeding strategies were optimized in a semibatch system to reach >95% monomer conversion and 70 wt % polymer in solution in 1.5 h with excellent control ( Đ = 1.10). It was concurrently demonstrated that prepolymerization in the copper tube reactor could be eliminated while still providing a chain-extendible species, a result that simplifies reactor operation, offers greater flexibility in initiator choice, and improves compositional control of the final product. The conditions developed for the homopolymerization system were applied to produce acrylate-acrylate and acrylate-methacrylate block copolymers, also exploring the influence of block order. Achieving high conversions for each monomer fed, reactions were completed in 4 h or less with no intermediate purification or additional catalyst, thus yielding a scalable method of producing block copolymer materials at Cu levels <100 ppm.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".