Carbon nanotubes – cylindrical formations of carbon atoms with incredible strength and electrical conductivity – hold great promise for creating new micron-scale low-power electronic devices.

But finding a way to build a reliable computing platform based on the carbon material has been a major challenge for researchers.

Now, a team of mechanical and materials engineers at Georgia Institute of Technology has devised a method for identifying performance variabilities in transistors made from carbon nanotube networks. The new approach could help researchers create more reliable devices and ultimately harness that technology for a range of applications such as wearable electronics, sensors and antennas.

“Using carbon nanotubes to make thin-film transistors with good performance repeatability has been challenging because of the random imperfections in the fabrication process,” said Satish Kumar, an associate professor in the George W. Woodruff School of Mechanical Engineering. “Those random imperfections cause variations in the properties of the nanotubes – differences in length, diameter and chirality. All of those things can impact how conductive a nanotube is, which leads to these performance variations.

“What we’ve done now is created a systematic way to estimate these variations that could improve reliability for carbon nanotube network based devices,” he said.

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