Early in 2012, Professor Michelle Simmons’ lab announced it had created 4-atom-wide nanowires. IBM demonstrated it could store a bit of information on only 12 atoms, compared with 1 million atoms for today’s most advanced hard drives. Then Prof. Simmons showed a working transistor made from a single atom. Meanwhile, Hewlett-Packard is planning to commercialize a mass-market flash memory device based on memristors, a new type of electronic device that stores information by manipulating the location of a few atoms.
EETimes – Williams said memristor research was essentially complete, adding: “If you know what you’re doing – and there’s a lot of intellectual property involved – literally any foundry could make memristors tomorrow.”
These breakthroughs show how, after more than a decade of research advances, scientists and technologists are learning to measure and manipulate matter to create fundamentally different electronic devices.
MICHELLE SIMMONS: Other groups had found that making nanowires thinner than 10nm wide tended to deactivate their dopants, the atoms added to the wire to make it conductive. We embedded our wire in crystalline silicon to isolate the dopant atoms from surfaces and interfaces that caused this deactivation. We predicted this would give us highly conductive wires, and this is what happened.
The key to making these wires was combining scanning tunneling microscopy, a technique to image and manipulate individual atoms, with molecular beam epitaxy, a way of growing perfect crystals. It gave us great precision in all three dimensions, and when combined with a high density of the dopant atoms, allowed us to create these highly conductive nanowires.
STAN WILLIAMS: We have such a long way to go. People talk about reaching the end of Moore’s Law, but really, it’s irrelevant. Transistors are not a rate-limiting factor in today’s computers. We could improve transistors by factor of one thousand and it would have no impact on the modern computer.
The rate-limiting parts are how you store and move information. These are visible targets and we know what we have to do to get there. We can continue to improve data centers and computers at Moore’s Law rates — doubling performance every 18 months — for at least another 20 years without getting into something like quantum or neuronal computing.
What makes using light on chips so desirable?
PAUL WEISS: Light is a much faster way to communicate along a device than electrons. But the wavelength of light is much larger than the semiconductor structures we make now. People are used to moving light around with large-scale mirrors or splitters, things we lay out on an optical table. Investigators have come up with very clever ways to do that with nanoscale structures. If we can cut down the size of these structures by one, two, or more orders of magnitude, things start getting exciting about the speed and amount of information we can move on a chip or between chips.
MICHELLE SIMMONS: One application of this involves light-matter interaction. We are looking at encoding quantum information in photons of light with the aim of eventually sending it by optical fiber across a continent or the globe. Optical losses down the fiber limit the distance we can transmit information. So we need a way to replenish the signal. We are looking at the interaction between light and matter to develop components like quantum repeaters, which take light in a photonic state, store it in a solid state, and then pass it on as photons so you can extend the secure communications distance. Research in this area is really starting to happen now.
STAN WILLIAMS: Yes. At the data center scale, any time you want to move data more than a few millimeters, you do that as a photon. Our model is that communication is done by photons, computation by electrons, and storage by ions. Each has its limits. Ultimately, they will all be integrated together on a chip.
PAUL WEISS: The hard part until now has been photons. Now we are shrinking it to the same scale as everything else we are doing.
Nanodevices in systems
We’ve been talking about nanodevices, like wires, transistors, and memristors. How do we put these devices together into systems? Where do we start?
STAN WILLIAMS: By the time you get into systems, people don’t publish. I see that myself. Our group publishes about our devices, but practically nothing at the systems level. There’s a good reason for that. Systems are where lots of know-how and differentiation come from. When things start to move into systems, it’s like a black hole, they just disappear from sight.
The other thing I learned is that even the most revolutionary new technology has to be introduced as evolutionary because the market doesn’t like disruption.
MICHELLE SIMMONS: What Stan just said makes perfect sense. In the field of quantum computing, there is a company called D-Wave that sold the first commercial quantum computer to Lockheed Martin last year. It’s very expensive and not everyone knows how it works. It will probably be a long time before you start seeing them sold in large numbers, but D-Wave is an example of a company that is trying to evolve them in the marketplace now.
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Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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