Washington: A team of scientists led by an Indian origin is studying graphene, essentially a single layer of the graphite found commonly in our pencils or the charcoal we burn on our barbeques, to use it as an alternative to copper in creating smaller and faster smart phones, tablet computers and other devises.
The new study at Rensselaer Polytechnic Institute could hasten the downfall of copper in nearly all electronics.
As new generations of computer chips continue to shrink in size, so do the copper pathways that transport electricity and information around the labyrinth of transistors and components.
When these pathways—called interconnects—grow smaller, they become less efficient, consume more power, and are more prone to permanent failure.
To overcome this hurdle, industry and academia are vigorously researching new candidates to succeed traditional copper as the material of choice for interconnects on computer chips.
And the researchers have found graphene, an atom-thick sheet of carbon atoms arranged like a nanoscale chicken-wire fence, as one promising candidate.
A team of researchers led by Rensselaer Professor Saroj Nayak discovered that they could enhance the ability of graphene to transmit electricity by stacking several thin graphene ribbons on top of one another.
The study brings industry closer to realizing graphene nanoelectronics and naming graphene as the heir apparent to copper.
“Graphene shows enormous potential for use in interconnects, and stacking up graphene shows a viable way to mass produce these structures,” said Nayak, a professor in the Department of Physics, Applied Physics, and Astronomy at Rensselaer.
“Cooper’s limitations are apparent, as increasingly smaller copper interconnects suffer from sluggish electron flows that results in hotter, less reliable devices. Our new study makes a case for the possibility that stacks of graphene ribbons could have what it takes to be used as interconnects in integrated circuits,” he added.
The study, based on large-scale quantum simulations, was conducted using the Rensselaer Computational Center for Nanotechnology Innovations (CCNI), one of the world’s most powerful university-based supercomputers.
The study was published in the journal ACS Nano.