| Literature DB >> 28083106 |
Dingjie Lu1, Yi Min Xie2, Qing Li3, Xiaodong Huang1, Yang Fan Li1, Shiwei Zhou1.
Abstract
The size effects that reveal the dramatic changes of mechanical behaviour at nanoscales have traditionally been analysed for regular beam systems. Here, the method of using finite-element analysis is explored with the intention of evaluating the size effects for complex nanostructures. The surface elasticity theory and generalized Young-Laplace equation are integrated into a beam element to account for the size effects in classical Euler-Bernoulli and Timoshenko beam theories. Computational results match well with the theoretical predictions on the size effect for a cantilever beam and a cubic unit cell containing 24 horizontal/vertical ligaments. For a simply supported nanowire, it is found that the results are very close to the experimental data. With the assumption that nanoporous gold is composed of many randomly connected beams, for the first time, the size effect of such a complex structure is numerically determined.Entities:
Keywords: finite-element method; nanostructure; size effect
Year: 2016 PMID: 28083106 PMCID: PMC5210688 DOI: 10.1098/rsos.160625
Source DB: PubMed Journal: R Soc Open Sci ISSN: 2054-5703 Impact factor: 2.963
Figure 1.The schematic of pressure q(x) resulting from the size effects.
Figure 2.The schematic of an infinitesimal edge element along the perimeter of the cross section of a beam.
Figure 3.The deflections in terms of the analytical solution and finite-element analysis (FEA) for a cantilever beam.
Figure 4.The comparison of experimental data [25] with the computational results for the effective Young's modulus of a silver nanowire.
Figure 5.The comparison of the effective Young's modulus with the prediction in [24].
Figure 6.(a) Scanning electron microscopy image of a representative nanoporous gold with ligament size D = 20 nm [35]. (b) A perspective view of a random open-cell foam generated by Voronoi tessellations.
Figure 7.The comparison of the effective Young's modulus between computational results with experiment data [7,26,35].