journal article·2023-01-02Open access

Optimal alignment for maximizing the uniaxial modulus of 2D anisotropic random nanofiber networks

Baorang Cui, Fei Pan, Jingxiu Zhang, Feng Zhang, Yong Ma, Yuli Chen

Abstract

Nanofiber networks are effective structural forms to utilize the excellent nanoscale properties of nanofibers in macro scale. Properly tuning the anisotropic degree of fiber orientation distribution can maximize the macroscopic mechanical properties of random nanofiber networks in a specific direction. However, the reinforcing mechanism of the anisotropic orientation distribution to the elastic behavior has not been fully understood. In this paper, the effect of anisotropic orientation distribution of nanofibers on the elastic behavior of network is studied based on the modulus-density scaling relation and stiffness thresholds. The uniaxial modulus of network is determined by both the orientation angle of each fiber and interconnectivity of the random fiber network. With the increase of anisotropic degree, the contribution of fiber orientation angle to the network modulus of the preferential direction increases and gradually tends to a constant, while the interconnectivity of the networks decreases, which may reduce the loadability of network. Therefore, at a given network density, the uniaxial modulus along the preferential direction first increases to a maximum value and then decreases with the increase of the anisotropic degree. Furthermore, an expression to predict the optimal anisotropic degrees corresponding to the maximum uniaxial moduli at different network densities is established.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Cellular and Composite Structures · Composite Material Mechanics · Mechanical Behavior of Composites

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Solid Mechanics, Beihang University, Beijing, China

School of Aeronautic Science and Engineering, Beihang University, Beijing, China

Funding

China Postdoctoral Science Foundation · National Postdoctoral Program for Innovative Talents

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