4.6 Article

Persistence length and stochastic fragmentation of supramolecular nanotubes under mechanical force

期刊

NANOTECHNOLOGY
卷 24, 期 19, 页码 -

出版社

IOP PUBLISHING LTD
DOI: 10.1088/0957-4484/24/19/195103

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资金

  1. National Science Foundation [CBET-1234305]
  2. Office of Science, Office of Basic Energy Sciences, of the US Department of Energy [DE-AC02-05CH11231]
  3. Departments of Civil and Environmental Engineering and Mechanical Engineering at Northwestern University
  4. Northwestern University High Performance Computing Center
  5. Initiative for Sustainability and Energy (ISEN) at Northwestern University
  6. ASME Applied Mechanics Division Haythornthwaite Research Initiation Grant
  7. Div Of Chem, Bioeng, Env, & Transp Sys
  8. Directorate For Engineering [1234305] Funding Source: National Science Foundation

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Cyclic peptide nanotubes (CPNs) exhibit impressive structural, mechanical and chemical properties in resemblance to beta-sheet proteins found in silks and amyloids, and show potential as supramolecular nanotubes that can be utilized to generate novel nanocomposites and nanoporous thin films. Quantifying the persistence length and thermomechanical fragmentation of CPNs is of great importance for establishing a theoretical basis of how to generate rectilinear nanostructures with controlled aspect ratio and rigidity. However, factors governing the elasticity and dynamical breaking of these supramolecular nanostructures remain to be fully understood. Here we present a statistical analysis of the Young's modulus and persistence length of CPNs using fully-atomistic molecular dynamic simulations in explicit solvent. We show that the measured properties exhibit a dependence on the magnitude of the shear force applied, and extrapolation to the quasi-static deformation case yields 0.46 mu m for the persistence length and 7.8 GPa for the Young's modulus, in agreement with our experimental observations from TEM images. We establish a theoretical model for the spatial and temporal distribution of stochastic fracture, which we use to explain the simulation-based observations of spontaneous fragmentation under an applied shear force. Our methodology, blending theory, simulation and experiments provide a framework that can be utilized to investigate the mechanical behavior of self-assembling protein materials, paving the way for their design towards biological and industrial applications.

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