Producing Bimodal Molecular Weight Distribution Polymer Resins Using Living and Conventional Free-Radical Polymerization
Bibliographic record
Abstract
The shape of the molecular weight distribution (MWD) has great influence over the end-use properties of the polymer resin. Reported techniques for the production of polymer resins with bimodal MWDs are based on the manipulation of certain operating conditions, such as the chain-transfer-agent concentration, among others. Living free-radical polymerization can be successfully used to achieve control over the molecular weight and architecture of the polymer resin and produce living polymer chains. Among the available techniques, the nitroxide-mediated system is one of the most commonly used. The key feature is that the nitroxide, for example, 2,2,6,6-tetramethylpiperdinyl-1-oxy (TEMPO), reversibly deactivates the growing radical, which provides for the controlled growth of the polymer chain. In this work, we present a study involving the sequential use of nitroxide-mediated and conventional free-radical techniques, aimed at the production of bimodal molecular weight distribution polymer resins, using a miniemulsion or a suspension polymerization system. No separation/purification technique is required between the polymerization steps. It is shown that bimodal MWD polymer resins of styrene and butyl acrylate can be successfully produced with the proposed technique. Independent control of the height and position of the peaks (i.e., relative proportion and molecular weight) of the distribution was achieved by manipulating the duration of the nitroxide-mediated process and the initiator concentration of the conventional free-radical process, respectively. The low-molecular-weight peaks ranged from 2000 to 30 000 Da, while the high-molecular-weight peak ranged from 300 000 to 1 200 000 Da in miniemulsion polymerizations and from 30 000 to 150 000 Da in suspension polymerization. Trimodal MWD polymer resins can also be produced in miniemulsion with the proposed polymerization technique if the concentration of chain-transfer agents is properly manipulated.
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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 | 0.000 | 0.001 |
| 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".