Understanding how complex carbon nanostructures form

Promises better control over carbon nanotube properties, such as stiff (for wires) or soft (for wearables)
April 10, 2015

Scanning electron micrographs demonstrate diverse CNT forest morphologies which may be (left) generally aligned to the growth axis or (right) highly tortuous, with persistently wavy CNTs intermixed with straight and aligned CNTs. (credit: Matthew R. Maschmann/Carbon)

A University of Missouri researcher has developed a way to predict how complicated carbon nanotube (CNT) structures (called “forests”) are formed when “grown” in a high-temperature furnace.

This understanding promises to enable designers and engineers to better incorporate the appropriate form of this highly adaptable material into devices and products such as aerospace wiring, combat body armor, computer logic components, and micro sensors used in biomedical applications.

Seeing the forest for the CNTs

CNTs naturally form “forests” when they are created in large numbers. These forests, held together by a nanoscale adhesive force known as the van der Waals force, are categorized based on their rigidity or how they are aligned.

For example, if CNTs are dense and well aligned, the material tends to be more rigid and can be useful for electrical and mechanical applications. If CNTs are disorganized, they tend to be softer, so they could be useful in biomedical applications or wearable devices, for example.

“Scientists are still learning how carbon nanotube arrays form,” said Matt Maschmann, assistant professor of mechanical and aerospace engineering in the College of Engineering at MU.

“As they grow in relatively dense populations, mechanical forces combine them into vertically oriented assemblies known as forests or arrays. The complex structures they form help dictate the properties the CNT forests possess. We’re working to identify the mechanisms behind how those forests form, how to control their formation and thus dictate future uses for CNTs.”

Better models

Currently, most models that examine CNT forests analyze what happens when you compress them or test their thermal or conductivity properties after they’ve formed. However, these models do not take into account the process by which that particular forest was created and struggle to capture realistic CNT forest structure.

A numerically simulated CNT forest (credit: Matt Maschmann)

Experiments conducted in Maschmann’s lab will help scientists understand the process and ultimately help control it, allowing engineers to create nanotube forests with desired mechanical, thermal and electrical properties.

He uses modeling to map how nanotubes grow into particular types of forests before attempting to test their resulting properties.

“The advantage of this approach is that we can map how different synthesis parameters, such as temperature and catalyst particle size, influence how nanotubes form while simultaneously testing the resulting CNT forests for how they will behave in one comprehensive simulation,” Maschmann said.

“I am very encouraged that the model successfully predicts how they are formed and their mechanical behaviors. Knowing how nanotubes are organized and behave will help engineers better integrate CNTs in practical, everyday applications.”

The study was funded in part by the Missouri Research Board and MU College of Engineering startup funds.


Abstract of Integrated simulation of active carbon nanotube forest growth and mechanical compression

Carbon nanotube (CNT) forests are CNT populations that self-assemble into vertically oriented cellular arrays during growth. The anisotropic and inhomogeneous morphology of forests arises from complex mechanical interactions between CNTs during their collective growth and influences many forest properties. A time-resolved simulation is developed to model actively growing CNT populations having distributed properties and growth characteristics. The model considers van der Waals (vdW) attraction between neighboring CNTs and allows the growing and deforming CNTs to interact and react based on a balance of forces. Parametric variations of growth rate distribution and CNT occupation density generate variable CNT forest morphology in manners consistent with experimental observations. The forces opposing vdW bonding between contacting CNTs during forest growth are found to diminish with distance from the growth substrate and are proportional to CNT bending stiffness. Axial and transverse compression of simulated forests capture experimentally observed phenomena of coordinated axial buckling, transverse densification, and the foam-like force–displacement response that is typical of CNT forests. This new paradigm in CNT forest modeling may be used as an analytical tool to examine CNT forest growth kinetics, multi-physics CNT forest performance, and the post-synthesis processing and forming of CNT forest microstructures.