Predictive modelling-based design and experiments for synthesis and spinning of bioinspired silk fibres

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Scalable computational modelling tools are required to guide the rational design of complex hierarchical materials with predictable functions. Here, we utilize mesoscopic modelling, integrated with genetic block copolymer synthesis and bioinspired spinning process, to demonstrate de novo materials design that incorporates chemistry, processing and material characterization. We find that intermediate hydrophobic/hydrophilic block ratios observed in natural spider silks and longer chain lengths lead to outstanding silk fibre formation. This design by nature is based on the optimal combination of protein solubility, self-assembled aggregate size and polymer network topology. The original homogeneous network structure becomes heterogeneous after spinning, enhancing the anisotropic network connectivity along the shear flow direction. Extending beyond the classical polymer theory, with insights from the percolation network model, we illustrate the direct proportionality between network conductance and fibre Young's modulus. This integrated approach provides a general path towards de novo functional network materials with enhanced mechanical properties and beyond (optical, electrical or thermal) as we have experimentally verified.
Publisher
NATURE PUBLISHING GROUP
Issue Date
2015-05
Language
English
Article Type
Article
Keywords

SPIDER DRAGLINE SILK; BLOCK-COPOLYMERS; BIOMATERIALS; DYNAMICS; SIMULATION; MECHANISM; PROTEINS; BEHAVIOR; SHEAR

Citation

NATURE COMMUNICATIONS, v.6

ISSN
2041-1723
DOI
10.1038/ncomms7892
URI
http://hdl.handle.net/10203/199800
Appears in Collection
ME-Journal Papers(저널논문)
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