Design of lightweight and ultrastrong nanoarchitected carbon by a coarse-grained model

Sihan Liu, Yujin Hu, Zhao Qin

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Cellular solids are commonly observed in nature and have wide applications in industry. While there is an unavoidable tradeoff between their weight and strength, it is feasible to use carbon nanomaterials as the constituent building blocks to guarantee both strength and lightweight. However, there is a lack of design tools to efficiently consider their hierarchical chemical structures and reveal how they relate to mechanical features. Here, we develop a coarse-grained (CG) model of covalently bonded carbon nanotube (CNT) networks. The CG model includes bead–spring chains for CNTs and nodal beads for carbon junctions. The effect of different nodal connectivities has been parameterized, yielding consistent modulus, tensile strength, and deformation with fully atomic CNT lattices. The CG model can be used to efficiently investigate the mechanics of CNT lattices and reveal their scaling law with density. We notice that all CNT lattices have specific tensile strengths 2 orders of magnitude higher than that of steel, and a larger nodal connectivity generally makes the material stiffer but weaker for the same density. The method can be effectively used to design the mechanics of CNT-based cellular solids as well as other covalently bonded network structures with a large length scale, high complexity, and varying nodal connectivity.

Original languageEnglish (US)
Article number107066
JournalComposites Part A: Applied Science and Manufacturing
Volume161
DOIs
StatePublished - Oct 2022
Externally publishedYes

Keywords

  • Carbon nanotube
  • Coarse grain
  • Connectivity
  • Lattice
  • Molecular dynamics
  • Network
  • Node

ASJC Scopus subject areas

  • Ceramics and Composites
  • Mechanics of Materials

Fingerprint

Dive into the research topics of 'Design of lightweight and ultrastrong nanoarchitected carbon by a coarse-grained model'. Together they form a unique fingerprint.

Cite this