The flexible connectors are made by directly transferring vertical carbon nanofibre (CNF) forests grown on silicon substrates to plastic substrates. The arrays stick strongly to surfaces in the shear direction thanks to the fact that they efficiently interpenetrate. However, they can be easily pulled off, which is useful for making reversible connections.

The researchers, led by Ali Javey of the Department of Electrical Engineering and Computer Sciences, employed CNF forests 50–100 nm across and 10–12 µm long vertically grown on silicon substrates. They successfully managed to transfer the CNFs onto flexible plastic substrates without destroying the original morphology of the nanostructures.

The CNF connectors do not easily attach to perfectly flat surfaces because of low Van der Waals interactions and binding forces. However, when placed on structures similar to themselves – for example, nanofibrillar surfaces with similar aspect ratios and dimensions – the contact area increases by more than 1000 times, resulting in strong shear binding. The connectors do not bind in the normal direction.

"These anisotropic adhesion properties can be controlled by the stiffness of the CNF arrays and how they are positioned," Javey told nanotechweb.org. "For instance, we showed that we could control adhesion within the shear regime by uniformly tilting the arrays."

When the titled CNFs are parallel to each other, the connectors have a strong shear adhesion strength of around 16 N/cm2. This drops to just 4 N/cm2 when the arrays are anti-parallel.

According to the team, which includes scientists from Lanzhou University in China and ELORET Corp. in Sunnyvale, California, the connectors could be used as bendable backing layers to bind electronic components together in a lightweight, robust way.

The researchers are now looking at how to better control the normal-to-shear adhesion strength while making the connectors even more robust, and reusable. "We will also investigate how to add further functionalities to the connectors – for instance, making them responsive to external stimuli," said Javey.

The work was reported in Small.