Carbon Nanotube Transistors Finally Outperform Silicon

Photo: Stephanie Precourt/UW-Madison College of Engineering

Back in the 1990s, observers predicted that the single-walled carbon nanotube (SWCNT) would be the nanomaterial that pushed silicon aside and created a post-CMOS world where Moore’s Law could continue its march towards ever=smaller chip dimensions. All of that hope was swallowed up by inconsistencies between semiconducting and metallic SWCNTs and the vexing issue of trying to get them all to align on a wafer.

The introduction of graphene seemed to take the final bit of luster off of carbon nanotubes’ shine, but the material, which researchers have been using to make transistors for over 20 years, has experienced a renaissance of late.

Now, researchers at the University of Wisconsin-Madison (UW-Madison) have given SWCNTs a new boost in their resurgence by using them to make a transistor that outperforms state-of-the-art silicon transistors.

“This achievement has been a dream of nanotechnology for the last 20 years,” said Michael Arnold, a professor at UW-Madison, in a press release. “Making carbon nanotube transistors that are better than silicon transistors is a big milestone,” Arnold added. “[It’s] a critical advance toward exploiting carbon nanotubes in logic, high-speed communications, and other semiconductor electronics technologies.”

In research described in the journal Science Advances, the UW-Madison researchers were able to achieve a current that is 1.9 times as fast as that seen in silicon transistors. The measure of how rapidly the current that can travel through the channel between a transistor’s source and drain determines how fast the circuit is. The more current there is, the more quickly the gate of the next device in the circuit can be charged .

The key to getting the nanotubes to create such a fast transistor was a new process that employs polymers to sort between the metallic and semiconducting SWCNTs to create an ultra-high purity of solution.

“We’ve identified specific conditions in which you can get rid of nearly all metallic nanotubes, [leaving] less than 0.01 percent metallic nanotubes [in a sample],” said Arnold.

The researchers had already tackled the problem of aligning and placing the nanotubes on a wafer two years ago when they developed a process they dubbed “floating evaporative self-assembly.” That technique uses a hydrophobic substrate and partially submerges it in water. Then the SWCNTs are deposited on its surface and the substrate removed vertically from the water.

“In our research, we’ve shown that we can simultaneously overcome all of these challenges of working with nanotubes, and that has allowed us to create these groundbreaking carbon nanotube transistors that surpass silicon and gallium arsenide transistors,” said Arnold.

In the video below, Arnold provides a little primer on SWCNTs and what his group’s research with them could mean to the future of electronics.

In continuing research, the UW-Madison team will be aiming to replicate the manufacturability of silicon transistors. To date, they have managed to scale their alignment and deposition process to 1-inch-by-1-inch wafers; the longer-term goal is to bring this up to commercial scales.

Arnold added: “There has been a lot of hype about carbon nanotubes that hasn’t been realized, and that has kind of soured many people’s outlook. But we think the hype is deserved. It has just taken decades of work for the materials science to catch up and allow us to effectively harness these materials.”

ORIGINAL: IEEE

By Dexter Johnson

6 Sep 2016

Google says its quantum computer is more than 100 million times faster than a regular computer chip

Above: The D-Wave 2X quantum computer at NASA Ames Research Lab in Mountain View, California, on December 8.

Image Credit: Jordan Novet/VentureBeat

Google appears to be more confident about the technical capabilities of its D-Wave 2X quantum computer, which it operates alongside NASA at the U.S. space agency’s Ames Research Center in Mountain View, California.

D-Wave’s machines are the closest thing we have today to quantum computing, which works with quantum bits, or qubits — each of which can be zero or one or both — instead of more conventional bits. The superposition of these qubits enable machines to make great numbers of computations to simultaneously, making a quantum computer highly desirable for certain types of processes.

In two tests, the Google NASA Quantum Artificial Intelligence Lab today announced that it has found the D-Wave machine to be considerably faster than simulated annealing — a simulation of quantum computation on a classical computer chip.

Google director of engineering Hartmut Neven went over the results of the tests in a blog post today:

We found that for problem instances involving nearly 1,000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 108 times faster than simulated annealing running on a single core. We also compared the quantum hardware to another algorithm called Quantum Monte Carlo. This is a method designed to emulate the behavior of quantum systems, but it runs on conventional processors. While the scaling with size between these two methods is comparable, they are again separated by a large factor sometimes as high as 108.

Google has also published a paper on the findings.

If nothing else, this is a positive signal for venture-backed D-Wave, which has also sold quantum computers to Lockheed Martin and Los Alamos National Laboratory. At an event at NASA Ames today where reporters looked at the D-Wave machine, chief executive Vern Brownell sounded awfully pleased at the discovery. Without question, the number 100,000,000 is impressive. It’s certainly the kind of thing the startup can show when it attempts to woo IT buyers and show why its technology might well succeed in disrupting legacy chipmakers such as Intel.

But Google continues to work with NASA on quantum computing, and meanwhile Google also has its own quantum computing hardware lab. And in that initiative, Google is still in the early days.

“I would say building a quantum computer is really, really hard, so first of all, we’re just trying to get it to work and not worry about cost or size or whatever,” said John Martinis, the person leading up Google’s hardware program and a professor of physics at the University of California, Santa Barbara.

Commercial applications of this technology might not happen overnight, but it’s possible that eventually they could lead to speed-ups for things like image recognition, which is in place inside of many Google services. But the tool could also come in handy for a traditional thing like cleaning up dirty data. Outside of Google, quantum speed-ups could translate into improvements for planning and scheduling and air traffic management, said David Bell, director of the Universities Space Research Association’s Research Institute for Advanced Computer Science, which also works on the D-Wave machine at NASA Ames.

ORIGINAL: Venture Beat

JORDAN NOVET 

DECEMBER 8, 2015

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