MIT Associate Professor Heather Kulik discusses using machine learning models to discover novel materials and successfully validating the computational designs in laboratory experiments.
“So we were able to screen with artificial intelligence a set of 1010 of thousands of materials where each individual experiment, if it were done in the lab, would have taken months to years. And through AI, we uncovered this sort of unexpected chemical phenomenon that led to a emergent property in, in what's known as a polymer network, so plastics that would make the polymer about four times tougher, and when we showed the design that AI had come up with to the experimentalists, they were really surprised. They would have never come on this on their own and then we were able to convince them to make it in the lab, and in fact, it was this tougher material”
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AssertionNot checkable as stated
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AssertionNot checkable as stated
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AssertionNot checkable as stated
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