Using Artificial Intelligence to Engineer Materials’ Properties
February 12, 2019 | MITEstimated reading time: 6 minutes
Diamond’s Potential
Diamond has great potential as a semiconductor material, though it’s still in its infancy compared to silicon technology. “It’s an extreme material, with high carrier mobility,” Li says, referring to the way negative and positive carriers of electric current move freely through diamond. Because of that, diamond could be ideal for some kinds of high-frequency electronic devices and for power electronics.
By some measures, Li says, diamond could potentially perform 100,000 times better than silicon. But it has other limitations, including the fact that nobody has yet figured out a good and scalable way to put diamond layers on a large substrate. The material is also difficult to “dope,” or introduce other atoms into, a key part of semiconductor manufacturing.
By mounting the material in a frame that can be adjusted to change the amount and orientation of the strain, Dao says, “we can have considerable flexibility” in altering its dopant behavior.
Whereas this study focused specifically on the effects of strain on the materials’ bandgap, “the method is generalizable” to other aspects, which affect not only electronic properties but also other properties such as photonic and magnetic behavior, Li says. From the 1% strain now being used in commercial chips, many new applications open up now that this team has shown that strains of nearly 10% are possible without fracturing. “When you get to more than 7% strain, you really change a lot in the material,” he says.
“This new method could potentially lead to the design of unprecedented material properties,” Li says. “But much further work will be needed to figure out how to impose the strain and how to scale up the process to do it on 100 million transistors on a chip [and ensure that] none of them can fail.”
“This innovative new work demonstrates potential to significantly accelerate the engineering of exotic electronic properties in ordinary materials via large elastic strains,” says Evan Reed, an associate professor of materials science and engineering at Stanford University, who was not involved in this research. “It sheds light on the opportunities and limitations that nature exhibits for such strain engineering, and it will be of interest to a broad spectrum of researchers working on important technologies.”
The work was supported by the MIT-Skoltech program and Nanyang Technological University.
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