March 20, 2017
Researchers at The University of Texas at Austin’s Department of Aerospace Engineering and Engineering Mechanics have found that graphene can be transferred to new materials by peeling, a technique that has potential to break a bottleneck that’s limiting the use of this versatile material in the next generation of electronics.
“What we are able to bring to the table is the ability to strip the graphene in a mechanical way,” said Kenneth Liechti, a mechanics of materials professor in the ASE/EM Department. “And that has promise for speeding up the manufacture of graphene.”
Liechti, who holds the Zarrow Centennial Professorship in Engineering, collaborated on the work with fellow ASE/EM professor Rui Huang and postdoctoral research fellow Seung Ryul Na, as well as with colleagues at UT’s Texas Materials Institute and at research institutes in Korea.
Graphene is a layer of pure carbon one atom thick. It’s the strongest, thinnest, lightest and most electrically conductive material known to science—properties that make it well suited from everything from solar cells to flexible electronics, such as bendable screens.
However, there is currently no economical or efficient way to transfer graphene from the copper sheets where it’s grown to substrates used in electronic devices. The most widely used transfer method involves attaching a material to the top of a graphene sheet and then etching away the supporting copper, a slow and wasteful process with the potential to contaminate the graphene with copper atoms.
In a 2015 paper published in the journal ACS Nano, Liechti and his colleagues present an alternative method: quickly peeling graphene away from the copper plate using an epoxy-coated silicon plate.
“There are general ideas from what’s known as fracture mechanics on how you might approach this, and we made use of some of those ideas,” Liechti said. “We found that if you went quickly, you could pull the graphene off. If you went too slowly it would stay behind.”
Liechti said the method harkens back to how the first graphene layer was created by using a strip of scotch tape to remove a thin layer of carbon from graphite, which is used in pencil lead.
“The idea to strip the graphene off the copper mechanically was very attractive to us,” Liechti said. “And in essence, you can say we returned to the ‘scotch-tape’ method of producing graphene.”
Another paper, published in ACS Nano in fall 2016, builds on the understanding of graphene behavior in a strained environment—such as during the transfer process—by investigating the forces that cause a sheet of graphene to wrinkle and crack. The findings of this paper are promising because they indicate that graphene could withstand the forces and strain associated with “roll-to-roll” manufacturing, a type of production that “prints” electronic materials onto a substrate by pressing the materials together.
Liechti, UT mechanical engineering Professor Wei Li and UT chemical engineering Professor Roger Bonnecaze are now working together to apply methods from the two papers to transfer graphene to a new substrate using roll-to-roll equipment. Li is leading the design of the roll-to-roll machine, with the research happening through NASCENT, a UT center dedicated to developing nanomanufacturing technologies in partnership with other universities.
The laboratory experiments have given researchers the parameters they need to meet for successful graphene transfer. Liechti said the challenge is creating the necessary conditions using equipment and materials that are applicable to the industrial environment. For example, the team will have to find an alternative epoxy to transfer the graphene from copper to silicon; the kind used in the laboratory setting isn’t a suitable material for the roll-to-roll process.
But Liechti said that the research team is making progress through close collaboration, and by following the numbers.
“Now that we know what it takes to get graphene off a surface, we can start to design the roll-to-roll machine so that it performs in the best most efficient way,” Liechti said. “We can use that information to home in on a much narrower set of parameters for the machine to operate within and get closer to the bull’s eye.”
