Creation of Sacrificial Bonds by Viscous Flow Instability
Bibliographic record
Abstract
The multiscale structure of spider silk is widely studied because of its superior mechanical properties. Its high tenacity allows the absorption of the kinetic energy of fast and large preys. The mechanism of sacrificial bonds enhances the stretchability and toughness of spider capture-silk. With this in mind, we fabricate microstructured fibers with sacrificial bonds using the dragged viscous thread instability. A thread of viscous liquid flowing towards a perpendicular moving platform buckles repetitively and creates different periodical patterns. A solution of 25% polylactid acid (PLA) dissolved in the dichloromethane (DCM) is extruded from a 30μm diameter needle onto a moving platform. By decreasing the speed ratio between the thread extrusion speed and the platform moving speed, we obtain different instability patterns: catenary, meandering, alternating (loop falling on alternate sides of the main thread), and coiling (all the loops falling on the same side). The spatial frequency of the periodical patterns linearly increases with the speed ratio until overlapping occurs. When the thread loops on itself, it welds and fuses with itself to form a bond which solidifies as the solvent evaporates and the thread dries. Different fiber patterns are tested in an electromechanical tensile machine and their performance are compared to a straight fiber. Sacrificial bonds require significant energy to break (i.e., ranging between 0 to 110% of the yield value of a straight fiber). Finally by controlling the instability parameters, we are able to tailor the mechanical properties of the resulting fibers such as its breaking strain, rigidity and toughness which could lead to different protective wear applications.
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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".