Skip to Content

Guiding the Evolution of Things

From engineered viruses, novel materials.
February 1, 2005

Could the tiniest organisms be the foundries of the future? Angela Belcher thinks so. The MIT materials scientist engineers viruses to manipu­late compounds at the molecular level. A 2004 MacArthur Fellowship (a.k.a. “genius grant”) winner, she’s also a cofounder of Cambridge, MA’s Cambrios Technologies, which applies her work to everything from lighting to microchip fabrication.

Technology Review: What do you do?

Angela Belcher: We look at how nature processes materials and then evolve organisms to make new types of materials.

TR: But you don’t like being called a nanotechnologist?

Belcher: I’m a materials chemist who works on nanosize materials.

TR: In fact you’re a materials chemist who’s engineering viruses to build computer chips. Are distinctions between conventional academic disciplines losing their meaning?

Belcher: You want to be an expert at some discipline of science or engineering. Then you integrate other things.

TR: The legend is that you began by wondering how sea shells were made, while walking on the beach as a grad student at UC Santa Barbara.

Belcher: It’s a nice story, but people have been studying the toughness and hardness of shells for fifty years.

TR: So do abalones do nanotech?

Belcher: They do. The hardness and luster is a function of the very, very uniform structure of calcium carbonate, deposited a molecule at a time. That’s also what makes pearls.

TR: Why jump from that to something as complex as microchips?

Belcher: Chips are the dream. We have roughly thirty other shorter-term projects – magnetic storage materials, [solar cells] for energy-efficient lighting, flexible batteries.

TR: The chip-making techniques you’re talking about promise features a tenth the size being achieved with conventional methods. How close are you to something that actually works?

Belcher: We’re making components right now, simple transistors. The next thing is to make useful architectures.

TR: Your company describes its business as “directed-evolution technology.” So the goal is something with potentially very broad application?

Belcher: It’s a platform technology, yes. The aim is to work our way through the whole periodic table and be able to design materials of all kinds in a controlled way. My biggest goal is to have a DNA sequence that can code for the synthesis of any useful material.

TR: But so far you have to use millions of viruses to find one or two that do something useful. Are there shortcuts?

Belcher: That’s what we’re working through now – what the rules are for how viruses interact with materials. But until we achieve that, we’re still making progress through trial and error and a lot more genetic manipulation.

TR: Presumably the answer is, design better organisms and you’ll get better materials.

Belcher: Exactly. And we’re not limited to viruses. We work on yeasts, too.

TR: So a wholly new organism could create a wholly new material?

Belcher: We’re working toward that, yes – new alloys, for instance.

TR: Nanotech meets genetic engineering: there’s a lot here to upset technophobes.

Belcher: We’re not making dangerous materials. In fact, we’re trying to reduce the amount of harmful materials going into the environment, not increase it.

TR: Some people find “self-assembly” worrisome.

Belcher: I don’t really understand why. So many things in the world self-assemble. Mix sodium and chlorine together, and it self-assembles to form a crystal. People often mix up “self-assembly” and “self-replication.” Things aren’t going to self-assemble out of control. It’s like worrying about your table salt replicating out of control. It just won’t happen.

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.

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.

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.

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.