Scientists Can Make Your Computer 1,000 Times Faster with Graphene

A team of researchers have replaced silicon with graphene to create a super transistor. The transistor can boost performance better than any other you'd find in a computer.

Scientists Can Make Your Computer 1,000 Times Faster with Graphene
Diagram showing the unzipped nanotube Nature

A collaborative team of researchers has developed a new kind of transistor that could make your computer 1,000 times faster. The transistor uses graphene instead of silicon. 

Graphene was discovered in 2004 and was soon being used in a wide range of applications, to the point where it has become known as the 'wonder material'. It possesses a unique set of properties, amongst them is the ability to conduct electricity ten times better than copper. Copper is currently the most commonly used conductor in electronics. Even more incredibly, at room temperature, graphene has the ability to conduct electricity 250 times better than silicon. This makes it the fastest conductor of any other known substance.

Scientists Can Make Your Computer 1,000 Times Faster with Graphene
Source: AlexanderAIUS/Wikimedia Creative Commons

These properties inspired the team of researchers from Northwestern University, The University of Texas at Dallas (UT Dallas), the University of Illinois at Urbana-Champaign, and the University of Central Florida (UCF) to investigate the use of graphene in transistors. The results of their study, published in the journal Nature Communications, show that a graphene base transit could outperform the silicon transistors currently used in computers. Transistors are crucial to computer circuits. They act as “switches” that allow electronic signals and power through the circuit. When placed together transistors form logic gates. These logic gates are the core of microprocessors. A microprocessor can contain millions of transistors that are in one of two states, either zero or one (binary bits). The combination of the transistors being in each state is what allows microprocessors to solve logic and computing problems.

Co-author Ryan Gelfand, an assistant professor at UCF, explains the move away from silicon.

"If you want to continue to push technology forward, we need faster computers to be able to run bigger and better simulations for climate science, for space exploration, for Wall Street," he said. "To get there, we can’t rely on silicon transistors anymore."

The silicon in Microprocessors has limited processing speeds to the 3 to 4 gigahertz range since 2005. The team thinks they have the answer to this limitation problem, by replacing the silicon with graphene. The transistor was created by the team first unzipping a thin folded graphene sheet known as a carbon nanotube. The team then applied a magnetic field to this ribbon which opened up the possibility of controlling the resistance of the flowing current. By using more nanotubes adjacent to the first, they could create a magnetic field that could control current. The resulting graphene transistors improved the speed of microprocessors by 1,000 times, while only using a hundredth of the power that is required to power a silicon based transistor. 

The resulting graphene transistors improved the speed of microprocessors by 1,000 times, while only using a hundredth of the power that is required to power a silicon based transistor. The new transistors can also be made much smaller than the traditional version. This could allow for a smaller device to become more powerful.

 Joseph S. Friedman, another co-author of the paper from UT Dallas, says that for the meantime an all carbon based computer system is still some time away, but prototypes of the transistors are underway. He states, "The exceptional material properties of carbon materials permit Terahertz operation and two orders of magnitude decrease in power-delay product compared to cutting-edge microprocessors. We hope to inspire the fabrication of these cascaded logic circuits to stimulate a transformative generation of energy-efficient computing."

Via: WEF, Nature

 

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