Skip to Content

Nano Sorter

Getting the right nanotubes in the right places
January 1, 2007

Carbon nanotubes could provide the circuitry for the computers of the future. But they can be either semiconducting or metallic, and the difficulty of getting the right type of tube in the right place on a computer chip has so far prevented their commercial use.

The image above shows metallic nanotubes in green and semiconducting tubes in orange.

Now Northwestern University researchers have developed a way to separate nanotubes by electrical conductivity and by diameter, another property that’s important for applications in electronics.

In the test tube at left, metallic nanotubes are shown in green and semiconducting tubes in orange. To separate them, the researchers add surfactants–chemicals common in detergents–to solutions of nanotubes. The surfactants cluster around the nanotubes in different concentrations and arrangements, depending on the nanotubes’ sizes and electronic properties. The clusters have different densities, so spinning the solution at ultrafast speeds produces layers containing specific kinds of nanotubes. While the researchers expected to be able to sort nanotubes by diameter, the sorting by electronic type came as a surprise, says Mark Hersam, a professor of materials science and engineering at Northwestern. Richard Martel, a chemistry professor at the University of Montreal, calls the Northwestern researchers’ new approach “a breakthrough in the field.”

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.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

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.