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

Shangchao Lin, Seunghwa Ryu, Olena Tokareva, Greta Gronau, Matthew M. Jacobsen, Wenwen Huang, Daniel J. Rizzo, David Li, Cristian Staii, Nicola M. Pugno, Joyce Y. Wong, David L. Kaplan and Markus J. Buehler ()
Additional contact information
Shangchao Lin: Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology
Seunghwa Ryu: Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology
Olena Tokareva: Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology
Greta Gronau: Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology
Matthew M. Jacobsen: Boston University
Wenwen Huang: Tufts University
Daniel J. Rizzo: Center for Nanoscopic Physics, Tufts University
David Li: Boston University
Cristian Staii: Center for Nanoscopic Physics, Tufts University
Nicola M. Pugno: Laboratory of Bio-Inspired and Graphene Nanomechanics, Environmental and Mechanical Engineering, University of Trento
Joyce Y. Wong: Boston University
David L. Kaplan: Tufts University
Markus J. Buehler: Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology

Nature Communications, 2015, vol. 6, issue 1, 1-12

Abstract: 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 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.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/ncomms7892 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms7892

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/ncomms7892

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().