预拉伸对丝蛋白力学性能影响的全原子网络模型

Silk protein builds one of the strongest natural fibers based on its complex nanocomposite structures. However, the mechanical performance of silk protein, related to its molecular structure and packing is still elusive. In this study, we constructed an atomistic silk protein network model, which reproduces the extensive connection topology of silk protein with structure details of the β-sheet crystallites and amorphous domains. With the silk protein network model, we investigated the structure evolution and stress distribution of silk protein under external loading. We found a pre-stretching treatment during the spinning process can improve the strength of silk protein. This treatment improves the properties of silk protein network, i.e., increases the number of nodes and bridges, makes the nodes distributed homogeneously, and induces the bridges in the network well aligned to the loading direction, which is of great benefit to the mechanical performances of silk protein. Our study not only provides a realized atomistic model for silk protein network that well represents the structures and deformations of silk proteins under loading, but also gains deep insights into the mechanism how the pre-loading on silk proteins during spinning improves the mechanical properties of silk fibers.