Robust <scp><i>β</i></scp>‐myrcene block copolymer elastomeric vitrimers
Bibliographic record
Abstract
Abstract As a terpene‐based conjugated diene, β‐myrcene (Myr) is a promising renewable building block for synthetic rubbers. However, the high entanglement molecular weight of poly(Myr) limits its mechanical properties and applications. This work aims to improve the mechanical properties and dimensional stability of recyclable bio‐based Myr elastomers by incorporating vitrimer chemistry and block copolymer self‐assembly. Linear prepolymers of statistical and diblock terpolymers of Myr, styrene (S) and β‐ketoester functional (acetoacetoxy)ethyl methacrylate (AAEMA) were synthesized using nitroxide‐mediated polymerization. The resulting statistical (P(S‐co‐Myr‐co‐AAEMA)) and diblock (PS‐b‐P(Myr‐co‐AAEMA)) prepolymers had comparable number‐average molecular weights (Mn ~ 20–27 kg mol−1) and similar overall compositions. PS‐b‐P(Myr‐co‐AAEMA) underwent microphase separation into lamellae, as confirmed by small‐angle X‐ray scattering and atomic force microscopy. Vinylogous urethane vitrimers were formed by crosslinking the AAEMA units in the prepolymers with vegetable oil‐derived difunctional amines (Priamine 1075). The networks could be remolded by hot pressing at 125 °C at least 4 cycles while retaining thermomechanical properties. PS‐b‐P(Myr‐co‐AAEMA) exhibited a tensile stress of 3.1 ± 0.6 MPa, which was four times higher than that of P(S‐co‐Myr‐co‐AAEMA). The diblock vitrimer also exhibited nearly ten times higher hardness, and similar strain at break (~ 90%), compared to the statistical terpolymer‐based vitrimer. The addition of glassy PS domains effectively anchored the network, resulting in 18–35% lower creep in PS‐b‐P(Myr‐co‐AAEMA). This work highlights the potential of Myr‐based block copolymer vitrimers in creating robust, bio‐based and recyclable elastomers. © 2025 The Author(s). Polymer International published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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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".