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Upgrades to advanced scientific user facilities such as next-generation x-raylight sources, nanoscience centers, and neutron facilities are revolutionizingour understanding of materials across the spectrum of the physical sciences,from life sciences to microelectronics. However, these facility and instrumentupgrades come with a significant increase in complexity. Driven by moreexacting scientific needs, instruments and experiments become more intricateeach year. This increased operational complexity makes it ever more challengingfor domain scientists to design experiments that effectively leverage thecapabilities of and operate on these advanced instruments. Large languagemodels (LLMs) can perform complex information retrieval, assist inknowledge-intensive tasks across applications, and provide guidance on toolusage. Using x-ray light sources, leadership computing, and nanoscience centersas representative examples, we describe preliminary experiments with aContext-Aware Language Model for Science (CALMS) to assist scientists withinstrument operations and complex experimentation. With the ability to retrieverelevant information from facility documentation, CALMS can answer simplequestions on scientific capabilities and other operational procedures. With theability to interface with software tools and experimental hardware, CALMS canconversationally operate scientific instruments. By making information moreaccessible and acting on user needs, LLMs could expand and diversify scientificfacilities' users and accelerate scientific output.

Opportunities for Retrieval and Tool Augmented Large Language Models in Scientific Facilities