New AI model reveals powdered crystal’s structure; can help make batteries, magnets

Researchers at MIT have introduced a novel method to reveal the structures of crystalline materials such as metals, rocks, and ceramics. Earlier, scientists have been using X-ray crystallography to determine the structure of crystalline materials.

However, chemists at MIT have now introduced a new generative AI model that can make it much easier to determine the structures of these powdered crystals.

The prediction model could help researchers characterize materials for use in batteries, magnets, and many other applications.

Structure of crystalline materials key to know its superconductivity capacity

Danna Freedman, the Frederick George Keyes Professor of Chemistry at MIT , stated that structure is the first thing that you need to know for any material. It’s important for superconductivity, it’s important for magnets, it’s important for knowing what photovoltaic you created, according to Freedman.

“It’s important for any application that you can think of which is materials-centric.”

Crystalline materials, which include metals and most other inorganic solid materials , are made of lattices that consist of many identical, repeating units. These units can be thought of as “boxes” with a distinctive shape and size, with atoms arranged precisely within them, according to researchers at MIT.

Model breaks the process into several subtasks

The new model by MIT breaks the process of predicting structures into several subtasks.

Researchers maintained that first, it determines the size and shape of the lattice “box” and which atoms will go into it. Then, it predicts the arrangement of atoms within the box. For each diffraction pattern, the model generates several possible structures, which can be tested by feeding the structures into a model that determines diffraction patterns for a given structure.

“Our model is generative AI, meaning that it generates something that it hasn’t seen before, and that allows us to generate several different guesses,” said MIT graduate student Eric Riesel, in the press release.

“We can make a hundred guesses, and then we can predict what the powder pattern should look like for our guesses. And then if the input looks exactly like the output, then we know we got it right.”

Model tested on over 100 experimental diffraction patterns

Tested on several thousand simulated diffraction patterns from the Materials Project, researchers at MIT also tested the model on over 100 experimental diffraction patterns from the RRUFF database, which contains powdered X-ray diffraction data for nearly 14,000 natural crystalline minerals, that they had held out of the training data.

On these data, the model was accurate about 67 percent of the time. Then, they began testing the model on diffraction patterns that hadn’t been solved before.

This data came from the Powder Diffraction File, which contains diffraction data for more than 400,000 solved and unsolved materials, according to the research at MIT.

Approach can be used to generate new materials that have different crystal structures

More than 100 of unsolved patterns were solved using new model.

Researchers also used their model to discover structures for three materials that Freedman’s lab created by forcing elements that do not react at atmospheric pressure to form compounds under high pressure. This approach can be used to generate new materials that have radically different crystal structures and physical properties, even though their chemical composition is the same, according to the research at MIT.

Graphite and diamond — both made of pure carbon — are examples of such materials. The materials that Freedman has developed, which each contain bismuth and one other element, could be useful in the design of new materials for permanent magnets.

“We found a lot of new materials from existing data, and most importantly, solved three unknown structures from our lab that comprise the first new binary phases of those combinations of elements,” said Freedman in the press release.

The study is published in the Journal of the American Chemical Society .