| Literature DB >> 29127324 |
Johannes A Wagner1,2, Sandeep P Patil3, Imke Greving4, Marc Lämmel5, Konstantinos Gkagkas6, Tilo Seydel7, Martin Müller4,8, Bernd Markert3, Frauke Gräter9,10.
Abstract
The emergence of order from disorder is a topic of vital interest. We here propose that long-range order can arise from a randomly arranged two-phase material under mechanical load. Using Small-Angle Neutron Scattering (SANS) experiments and Molecular Dynamics based finite element (FE) models we show evidence for stress-induced ordering in spider dragline silk. Both methods show striking quantitative agreement of the position, shift and intensity increase of the long period upon stretching. We demonstrate that mesoscopic ordering does not originate from silk-specific processes such as strain-induced crystallization on the atomistic scale or the alignment of tilted crystallites. It instead is a general phenomenon arising from a non-affine deformation that enhances density fluctuations of the stiff and soft phases along the direction of stress. Our results suggest long-range ordering, analogously to the coalescence of defects in materials, as a wide-spread phenomenon to be exploited for tuning the mechanical properties of many hybrid stiff and soft materials.Entities:
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Year: 2017 PMID: 29127324 PMCID: PMC5681667 DOI: 10.1038/s41598-017-15384-8
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Scheme to illustrate the hypothesis of stress-induced order. Tensile loading can lead to ordering of the stiffer (blue) and softer (orange) components in a two-component system. The material builds up periodic density fluctuations featuring more soft regions with fewer stiffer particles (arrows), resulting in long-range order along the loading direction at a length scale larger than the stiffer components’ dimension.
Figure 2Increased long-range order in FE fiber models during loading. (a) A simplified 3D FE fiber model (see Suppl. Methods for details) with crystallites immersed into the amorphous phase was subjected to tensile load and the crystal distribution monitored. (b) Fluctuating crystallinity along the fiber axis of a fiber with 11% overall crystallinity for two different strains. Arrows exemplify cross-sections with increased amplitudes in crystallinity variations during loading. We note that even though this data representation does not straightforwardly reflect ordering, the quantification by MAD strongly suggests long-range ordering in all cases. (c) Mean absolute deviations (MAD) of crystallinity along the fiber axis as a function of external strain. For each overall crystallinity, values have been averaged over five individual fiber models. See Suppl. Figure 4 for the MAD of fibers with larger crystals and crystallinity.
Figure 3Scattering intensities from SANS and FE corroborate stress-induced long-range order. (a) Meridional long period peaks of I(q) recorded by SANS on a D2 O humid spider silk sample for varying strain values ε in % elongation. Inset: 2D scattering image at no strain (top) and maximum strain (bottom), respectively. The peak position shifts towards lower q with increasing tensile load. In addition, the peak becomes slightly sharper. The yellow arcs represent the azimuthal integration angle of 45°. (b) Long period peaks of I(q) calculated from FE calculations of a strained fiber model of 11% crystallinity. Inset: I(q) over a larger q-range also including peaks from intra-crystallite scattering. (c) Small-angle strain ε as manifested by the relative change in the long period peak position versus macroscopic fiber strain ε, calculated from SANS (a) and the FE model (b). (d) Relative increase of scattering intensity, I(q)/I (q), as recorded by SANS or calculated for FE models of different crystallinity. As a reference, the intensity increase predicted by a simplified analytical model (see Suppl. Methods), by a fully amorphous model, in which the originally crystalline parts still yield the scattering contrast, and by a perfectly ordered serial model is also shown. (Note: the relative intensity increase from the analytical model is a function of the number of scatterers N, but this dependency vanishes for large N. We chose N = 60 in Eq. 1, which is large enough to avoid this dependency.