Mechanical and thermal properties of a biomimetic multi-layered carbon nanofibers 3D networks: A novel strategy for 3D finite element analysis modeling and simulation

• Published in: Carbon trends 2021-07, Vol.4, p.100076, Article 100076
• Main Authors: Al-Qatatsheh, Ahmed, Jin, Xing, Salim, Nisa V
• Format: Article
• Language: English
• Subjects: Carbon nanofiber; Finite element; High aspect ratio; High tortuosity; Mori-Tanaka double inclusion
• ISSN: 2667-0569; 2667-0569
• DOI: 10.1016/j.cartre.2021.100076

•An innovative strategy to design highly porous 3D Carbon foam with multifunctional properties.•An accurate prediction of the morphological, mechanical, and thermal properties.•Computational modeling of Nanofibers with high aspect ratio and tourtosity.•An approach to overcome modeling difficulties, including coating thickness. Graphene-Coated carbon nanofibers (G-CNFs) Foams with interconnected 3D-networks have unique physical properties that make them suitable for a wide variety of applications. However, their design and fabrication strategies entail several parameters with different strengths, anisotropy, and thermal conductivity. Tuning functional properties to meet the desired application needs a deep understanding of their microstructure. Utilizing a microstructure modeling based on a Finite Element Analysis (FEA) requires adopting an accurate yet simple approach to overcome complications associated with the unique morphological characteristics of the G-CNFs Foam, covering graphene coating thickness and high aspect ratio and tortuosity, that can be neither disregarded nor roughly approximated. Here, we introduce an innovative strategy to predict the morphological, mechanical, and thermal properties of a G-CNFs Foam with a high aspect ratio and tortuosity, as well as a significant difference in composite materials' strength to overcome modeling difficulties including meshing, coating thickness, and homogenization, to name a few. This new modeling strategy is validated with experimental data from our work and the literature and provides a reliable and straightforward approach with less computational cost. [Display omitted]