Scientists from the University of Reading and University College London have created CrystaLLM, an Artificial Intelligence (AI) model that predicts how atoms form crystals. This could speed up finding new materials for tech like solar panels or chips.

CrystaLLM learns like AI chatbots based on large language models (LLMs) do, by studying the “language” of crystals. It reads millions of crystal structures to understand patterns. This method avoids the slow, energy-intensive simulations that usually predict crystal arrangements.

“Predicting crystal structures is like solving a complex, multidimensional puzzle where the pieces are hidden,” says research leader Luis Antunes in a press release issued by the University of Reading. “Crystal structure prediction requires massive computing power to test countless possible arrangements of atoms.”

“CrystaLLM offers a breakthrough by studying millions of known crystal structures to understand patterns and predict new ones, much like an expert puzzle solver who recognises winning patterns rather than trying every possible move,” he adds.

The scientists have described the methods that they have used to develop CrystalLLM, and some preliminary results, in a paper published in Nature Communications.

CrystaLLM guesses the next part of a crystal’s structure as it reads, learning without explicit physics or chemistry lessons.

Instead, it reads Crystallographic Information Files, standard crystal descriptions, and learns from them. It can then predict new, unseen crystal structures based on patterns it discovers.

Free CrystaLLM website

The team shared CrystaLLM with scientists through a free website. The CrystalLLM website includes an open access preprint published in arXiv, titled “Crystal Structure Generation with Autoregressive Large Language Modeling.” It also includes information on an application programming interface (API) for CrystalLLM.

This tool could help engineers quickly develop new materials for batteries, solar cells, and more, by integrating into existing prediction methods.

CrystalLLM also shows that the AI technology used in LLMs has applications that could go much beyond human language.

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