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Large-language models (LLMs) such as GPT-4 caught the interest of manyscientists. Recent studies suggested that these models could be useful inchemistry and materials science. To explore these possibilities, we organized ahackathon.  This article chronicles the projects built as part of this hackathon.Participants employed LLMs for various applications, including predictingproperties of molecules and materials, designing novel interfaces for tools,extracting knowledge from unstructured data, and developing new educationalapplications.  The diverse topics and the fact that working prototypes could be generated inless than two days highlight that LLMs will profoundly impact the future of ourfields. The rich collection of ideas and projects also indicates that theapplications of LLMs are not limited to materials science and chemistry butoffer potential benefits to a wide range of scientific disciplines.

14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon