Statistically Equivalent Representative Volume Element Modeling of Carbon Nanotube-Copper Composite Fibers Based on Cross-Sectional Microstructures

초록

Carbon nanotube (CNT) fibers coated with metals represent a promising class of multifunctional materials that combine enhanced mechanical strength with high electrical conductivity. In this study, we develop a computational framework for porous CNT fibers and metal-coated CNT fibers by integrating statistically equivalent representative volume element (SERVE) models with finite element methods. The SERVE framework generates synthetic cross-sectional microstructures that reproduce key statistical descriptors extracted from microscopy images, enabling representative simulations. For short fiber models where axial variation is assumed negligible, the synthetic cross-sectional microstructures are uniformly extended along the fiber axis. Then, the tensile response of pristine CNT fibers and copper (Cu)/CNT fibers is numerically evaluated as a function of packing density and copper volume fraction, assuming a porosity-induced necking failure mechanism. For pristine CNT fibers, tensile strength increases with packing density, whereas for Cu/CNT fibers, tensile strength is strongly dependent on microstructural morphology. Among the configurations studied, Cu/CNT fibers featuring a high-packing-density CNT core encapsulated by a copper shell exhibit the highest performance index, indicating the most favorable balance between tensile strength and electrical conductivity. Although the SERVE approach is demonstrated using cross-sectional microstructures without accounting for axial structural variations, it establishes a framework for modeling stochastically porous Cu/CNT fiber microstructures that can be extended to fully three-dimensional analyses in future work. Copyright © 2026 by ASME.

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