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

ABSTRACT: 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 conn

SUBMITTER: Lin S 

PROVIDER: S-EPMC4996357 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature