Fabrication of a Self-Healing, 3D Printable, and Reprocessable Biobased Elastomer
Bibliographic record
Abstract
A novel self-healable, fully reprocessable, and inkjet three-dimensional (3D) printable partially biobased elastomer is reported in this work. A long-chain unsaturated diacrylate monomer was first synthesized from canola oil and then cross-linked with a partially oxidized silicon-based copolymer containing free thiol groups and disulfide bonds. The elastomer is fabricated through inkjet 3D printing utilizing the photoinitiated thiol-ene click chemistry and reprocessed by compression molding exploiting the dynamic nature of disulfide bond. Self-healing is enabled by phosphine-catalyzed disulfide metathesis. The elastomer displayed a tensile strength of ∼52 kPa, a breaking strain of ∼24, and ∼86% healing efficiency at 80 °C temperature after 8 h. Moreover, the elastomer showed excellent thermal stability, and the highest thermal degradation temperature was recorded to be ∼524 °C. After reprocessing through compression molding, the elastomer fully recovered its mechanical and thermal properties. These properties of the elastomer yield an ecofriendly alternative of fossil fuel-based elastomers that can find broad applications in soft robotics, flexible wearable devices, strain sensors, health care, and next-generation energy-harvesting and -storage devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".