For one thing, Williams says these memristors can be used as either digital switches or to build a new breed of analog devices.

For the former, Williams says scientists can now think about fabricating a new type of non-volatile random access memory (RAM) – or memory chips that don't forget what power state they were in when a computer is shut off.

That's the big problem with DRAM today, he says. "When you turn the power off on your PC, the DRAM forgets what was there. So the next time you turn the power on you've got to sit there and wait while all of this stuff that you need to run your computer is loaded into the DRAM from the hard disk."

With non-volatile RAM, that process would be instantaneous and your PC would be in the same state as when you turned it off.

Scientists also envision building other types of circuits in which the memristor would be used as an analog device.

Indeed, Leon himself noted the similarity between his own predictions of the properties for a memristor and what was then known about synapses in the brain. One of his suggestions was that you could perhaps do some type of neuronal computing using memristors. HP Labs thinks that's actually a very good idea.

"Building an analog computer in which you don't use 1s and 0s and instead use essentially all shades of gray in between is one of the things we're already working on," says Williams. These computers could do the types of things that digital computers aren't very good at –- like making decisions, determining that one thing is larger than another, or even learning.

While a lot of researchers are currently trying to write a computer code that simulates brain function on a standard machine, they have to use huge machines with enormous processing power to simulate only tiny portions of the brain.

Williams and his team say they can now take a different approach: "Instead of writing a computer program to simulate a brain or simulate some brain function, we're actually looking to build some hardware based upon memristors that emulates brain-like functions," says Williams.

Such hardware could be used to improve things like facial recognition technology, and enable an appliance to essentially learn from experience, he says. In principle, this should also be thousands or millions of times more efficient than running a program on a digital computer.

The results of HP Labs teams findings will be published in a paper in today's edition of Nature. As far as when we might see memristors actually being used in actual commercial devices, Williams says the limitations are more business oriented than technological.

Ultimately, the problem is going to be related to the time and effort involved in designing a memristor circuit, he says. "The money invested in circuit design is actually much larger than building fabs. In fact, you can use any fab to make these things right now, but somebody also has to design the circuits and there's currently no memristor model. The key is going to be getting the necessary tools out into the community and finding a niche application for memristors. How long this will take is more of a business decision than a technological one."

Image: An atomic force microscope image of a simple circuit with 17 memristors lined up in a row.  Each memristor has a bottom wire that contacts one side of the device and a top wire that contacts the opposite side.  The devices act as 'memory resistors', with the resistance of each device depending on the amount of charge that has moved through each one. The wires in this image are 50 nm wide, or about 150 atoms in total width.  Image courtesy of J. J. Yang, HP Labs.