Reusable Stencils Cut Waste in Carbon Nanotube Patterning, Researchers Show

Researchers from Skoltech in Russia, working with colleagues at Harbin Institute of Technology in China and ITMO University in Russia, have developed a way to pattern single-walled carbon nanotube films without wasting material. The technique, published in the journal Light: Advanced Manufacturing, could make it cheaper to produce the nanotube patterns used in optical devices and mechanical strain sensors.

Single-walled carbon nanotube films are normally patterned by depositing a continuous film and etching away the parts not needed, a process that can waste as much as 90% of the nanotubes and degrade the quality of what remains, said study co-author Dmitry Krasnikov, an associate professor at Skoltech Photonics. The new method instead presses a laser-cut hot metal stencil, carrying the inverse of the desired pattern, into a nitrocellulose membrane at about 200 megapascals, clogging the pores in areas where nanotubes should not be deposited.

The pressed membrane becomes a reusable template for aerosol chemical vapor deposition, a standard technique for producing carbon nanotube films: the nanotube aerosol passes only through the unclogged pores, depositing material exactly where wanted with no etching, solvents or foreign materials involved. An earlier version of the technique used copper sputtering to block unwanted areas, but that limited patterns to continuous shapes and let some copper stick to the nanotubes, degrading their properties; the new hot-pressing approach avoids both problems.

The team demonstrated patterns with features as small as 100 micrometers, and tested a mechanical strain sensor built from a W-shaped nanotube pattern on an epoxy substrate: its conductivity changed by at least three times more than previously reported for similar sensors, and stayed stable over 3,000 load-unload cycles. Reused stencils produced films with only a few percent variation in optical properties between runs, and lead author Nikita Raginov, a Skoltech research intern, said the method is scalable across optics, electronics and sensing applications.