Skip to Content
Uncategorized

The Trouble With Turning Graphite Into Diamond

Graphite and diamond have similar free energies but converting one into the other is famously hard. Now materials scientists think they know why

Converting graphite into diamond has been a long held dream of alchemists the world over. In the modern era, materials scientists have puzzled over this process because it’s hard to work out why the conversion is so hard.

Measure the free energy of graphite and diamond and you’ll find they are more or less the same. That implies that converting one into the other ought to be easy.

And yet in experiments, the conversion only works at temperatures well above 1700K and at pressures in excess of 12 GigaPascals. It’s no wonder, then, that diamond is so rare and valuable

But why should graphite be so reluctant to make the change? Today, Rustam Khaliullin at the Swiss Federal Institute of Technology Zurich and a few buddies say they think they know why. These guys have created a computer model of the process which has identified the reason why diamond is so reluctant to form.

Materials scientists have long believed that the conversion process must begin by nucleation of diamond in graphite followed by growth. It’s easy to imagine that such a process would be straightforward to model from first principles on a computer.

That has turned out not be the case. The surface energy of diamond is extremely high so small diamonds of only a few atoms cannot easily form (the surface energy is just too high).

That means the initial seed in diamond nucleation must consist of tens of thousands of carbon atoms. That’s too many for any standard computer simulation from first principles.

Khaliullin and pals take a different approach. They use a neural network to simulate the potential energy surface that exists throughout graphite sheets as they are flexed. This approach ignores the details of each carbon bond and focuses instead on the more general molecular structure.

In this way, the simulation can cope with the required tens or even hundreds of thousands of atoms. Khaliullin and co say this has allowed them “to perform the first atomistic study of homogeneous diamond nucleation from graphite”

The results are intriguing. To form diamond, the hexagonal rings in graphite first have to deform. There are essentially two ways a hexagonal ring can warp. Opposite ends of the hexagon can both flex upwards forming a boat-like shape; or one end of the hexagon can flex upwards and the other downwards forming a chair-like shape.

Khaliullin and co show that at low pressures, below 10GPa, the hexagonal rings in graphite tend to form the boat-shaped structure. When this happens, the graphite forms into a metastable allotrope of carbon called hexagonal diamond.

This, they say, is the reason why diamond is so difficult to make: carbon prefers to form into a different hexagonal structure.

In fact, this is exactly what happens in experiments when graphite is compressed and heated below the critical diamond-forming temperatures. Hexagonal diamond is also sometimes found in meteorites.

Khaliullin and co go on to show that at high pressures, the chair-shaped hexagons form and that these seed the formation of diamond. They also show that as the pressure increases, the size of the diamond seed needed to trigger nucleation also shrinks. That’s why diamond forms much more easily at 50 GPa than at 20 GPa.

That won’t make it any easier to turn coal into jewellry. But it does give materials scientists a new insight into one of the more interesting problems that have puzzled them in recent years.

Ref: arxiv.org/abs/1101.1406: Nucleation Mechanism For The Direct Graphite-To-Diamond Phase Transition

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.