Carbon Nanotubes as a Basis of Metamaterials and Nanostructures: Crafting via Design Optimization

TL;DR

This paper explores the design and optimization of carbon nanotube nanotruss structures for metamaterials and nanostructures, demonstrating their exceptional mechanical properties through a novel framework combining molecular dynamics, neural networks, and finite element methods.

Contribution

It introduces a new integrated framework for optimizing carbon nanotube nanostructures, comparing heuristic methods and applying them to various innovative applications.

Findings

Optimized nanotrusses exhibit extraordinary mechanical properties.

Most heuristic optimization methods are effective despite nonlinearities.

Designs include energy trapping, auxetic, and high-strength structures.

Abstract

Nanotruss structures made of carbon nanotubes are investigated in two conceptual applications: either as building blocks of metamaterials or for nanostructural applications. The nanotrusses are optimized for different purposes, including various loadings, boundary conditions, parameterizations, objectives and constraints used to formulate optimization problems. The procedure relies on a recently developed framework consisting of molecular dynamics simulations, neural networks and finite elements. This framework is now used in the design optimization of nanostructures and the performances of different popular heuristic optimization methods are compared. Five applications of nanotrusses made of carbon nanotubes are analyzed in detail to investigate the mechanical behavior of such structures and the efficiency of the optimizations. Besides an introductory example, the design of an energy trapping carbon nanotube nanotruss, an auxetic nanotruss, a cantilever nanotruss and the maximization of the compressive strength of a metamaterial are presented. It is shown that the exceptional mechanical properties of carbon nanotubes can indeed be exploited for the development of structures and materials with extraordinary mechanical properties. Although hampered by material and geometrical nonlinearity of the problem, most of the tested optimization methods have proven to be a good choice for the design of such materials and structures.