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
The dark secret behind those cute AI-generated animal images
Google Brain has revealed its own image-making AI, called Imagen. But don't expect to see anything that isn't wholesome.
The hype around DeepMind’s new AI model misses what’s actually cool about it
Some worry that the chatter about these tools is doing the whole field a disservice.
The walls are closing in on Clearview AI
The controversial face recognition company was just fined $10 million for scraping UK faces from the web. That might not be the end of it.
This horse-riding astronaut is a milestone in AI’s journey to make sense of the world
OpenAI’s latest picture-making AI is amazing—but raises questions about what we mean by intelligence.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.