ArticleScience advances2025
Charting the envelope of mechanical properties of synthetic silk fibers through predictive modeling of the drawing process.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Mimetic Core-Sheath Silk Sutures with Superior-Strength for Pain Management, Anti-Infection and Wound Healing.Advanced healthcare materials · 2026Article
- Hierarchical picot-fiber hydrogel coating with ultralow friction and high wear resistance.Nature communications · 2026Article
- Biomimetic polymers and their characterization: toward sustainable materials using synthetic biology.Frontiers in chemistry · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A major challenge in synthesizing strong and tough protein fibers based on spider silk motifs is understanding the coupling between protein sequence and the postspin drawing process. We clarify how drawing-induced elongational force affects ordering, chain extension, interchain contacts, and molecular mobility through mesoscale simulations of silk-based fibers. We show that these emergent features can be used to predict mechanical property enhancements arising from postspin drawing. Simulations recapitulate a purely process-dependent mechanical property envelope in which order enhances fiber strength while preserving toughness. The relationship between chain extension and crystalline domain alignment observed in simulations is validated by Raman spectroscopy of wet-spun fibers. Property enhancements attributed to the progression of anisotropic extension are verified by mechanical tests of drawn silk fibers and justified by theory. These findings elucidate how drawing enhances properties of protein-based fibers and shed light on how to incorporate this effect into predictive models.
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Registered trials
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