Giving AI a “crystal clear” view of the materials world
In principle, artificial intelligence could make finding the right material for an application as simple as ordering dinner: Scientists would tell a large language model what they want, and it would serve them a perfectly designed crystal for the job.
Unfortunately, that approach doesn’t work well yet, and the problem comes down to data: Most materials consist of crystals, which are 3D periodic arrangements of atoms whose structures are stored in specialized formats, not the text streams that today’s large language models are trained on. The experimental literature is also heavily biased toward a few popular classes of crystals, making AI outputs skew toward those materials.
Now MIT researchers have created a multimodal AI model that tackles these problems. The model combines 3D atomic structures with natural language descriptions to create rich linguistic descriptions about the structures from experimental research papers and first-principles computational databases. The unified description outlines not...
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