Skip to Content

Atom-Thick Silicon Makes Crazy-Fast Transistors

An exotic form of silicon, called silicene, could enable a new generation of faster computers.

An exotic but tricky-to-use new form of silicon is being eyed as a way to build much faster computer chips. And now, those who see its potential can claim a minor victory by making the first transistors out of the stuff.

detail view of silicene
A scanning tunneling microscope image of silicene.

The material in question, called silicene, comes in layers of silicon just one-atom thick. This structure gives the material fantastic electrical properties, but it also means it’s devilishly tricky to produce and work with. Even testing its basic properties in the lab has proved difficult.

Now Deji Akinwande, a computer engineer at the University of Texas at Austin, has figured out how to work with the stubborn material well enough to make the first silicene transistors. His first-of-their-kind devices are described today in the journal Nature Nanotechnology, and they live up to silicene’s promise by switching with extraordinary speed.

Another atom-thick material, graphene, which is made from carbon, has gained attention in recent years for its own electrical properties. The appeal of silicene, says Akinwande, is that it’s made from the stuff Silicon Valley was built on. In theory, it should be easier for chipmakers to work with than some new material. “If we can get good properties out of it, it can be translated immediately by the semiconductor industry,” Akinwande says.

In 2007, Lok Lew Yan Voon, a physicist at Citadel Military College of South Carolina, who published some of the first theoretical work on silicene, calculated that the material’s electrical properties should be similar to those of graphene. In theory, electrons can cruise through both graphene and silicene without encountering as many obstacles, enabling very speedy circuits.

Unlike graphene, however, silicene doesn’t occur naturally. It has to be grown in the lab on a sheet of silver. Carbon is also more stable in its two-dimensional form, whereas silicon atoms are under strain in this form. To date, only a handful of groups have succeeded in making silicene in the lab. One group, in France, grew a nanoscale ribbon of the stuff in 2010. A few others succeeded in fabricating the material in 2012.

Once silicene is made, its instability means it must be protected, and that makes it difficult to work with. Akinwande found a way around this problem by growing silicene on a thin film of silver capped with aluminum oxide. The whole thing is then peeled off, and then placed on a silicon dioxide wafer with the silver side up. Finally, the silver is patterned to make the electrical contacts for a transistor. Once the device is finished, it is stable under vacuum conditions.

That might not turn out to be commercially practical, but it’s an important first demonstration, says Lok. The performance of the transistors also lines up with theoretical predictions about silicene’s speedy highway for electrons. “They managed to do what many people have been trying to do,” he says.

This demonstration is especially important because there has been skepticism about silicene’s potential, says Patrick Vogt, a researcher at the Technische Universität Berlin and one of a handful of researchers who have succeeded in growing the material. Vogt is currently working on new methods for making it.

Fengnian Xia, an electrical engineer at Yale University who is developing electronics based on graphene, phosphorene, and other two-dimensional materials, might be counted as one of the skeptics. He says the transistor results reported by the Texas group look good and represent a big scientific advance. But as for silicene’s commercial potential, Xia says he’s not convinced that it would be easier to commercialize than graphene, or that it can do anything graphene can’t.

Vogt says silicene probably won’t replace silicon entirely, but it might add new functionality to today’s chips. “This shows you can actually do something with silicene,” he says.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.