Upgrades to advanced scientific user facilities such as next-generation x-ray light sources, nanoscience centers, and neutron facilities are revolutionizing our understanding of materials across the spectrum of the physical sciences, from life sciences to microelectronics. However, these facility and instrument upgrades come with a significant increase in complexity. Driven by more exacting scientific needs, instruments and experiments become more intricate each year. This increased operational complexity makes it ever more challenging for domain scientists to design experiments that effectively leverage the capabilities of and operate on these advanced instruments. Large language models (LLMs) can perform complex information retrieval, assist in knowledge-intensive tasks across applications, and provide guidance on tool usage. Using x-ray light sources, leadership computing, and nanoscience centers as representative examples, we describe preliminary experiments with a Context-Aware Language Model for Science (CALMS) to assist scientists with instrument operations and complex experimentation. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can conversationally operate scientific instruments. By making information more accessible and acting on user needs, LLMs could expand and diversify scientific facilities’ users and accelerate scientific output.

对高级科学用户设施的升级，如下一代 X 射线光源、纳米科学中心和中子设施，正在彻底改变我们对物理科学（从生命科学到微电子学）材料的理解。然而，这些设施和仪器升级的复杂性显著增加。在更严格的科学需求的推动下，仪器和实验每年都变得更加复杂。这种增加的操作复杂性使得领域科学家设计能够有效利用这些先进仪器的功能并在这些先进仪器上运行的实验变得越来越具有挑战性。大型语言模型 （LLMs） 可以执行复杂的信息检索，协助跨应用程序执行知识密集型任务，并提供有关工具使用的指导。以 X 射线光源、领导力计算和纳米科学中心为代表示例，我们描述了使用科学上下文感知语言模型 （CALMS） 的初步实验，以协助科学家进行仪器操作和复杂实验。CALMS 能够从设施文件中检索相关信息，可以回答有关科学能力和其他操作程序的简单问题。CALMS 能够与软件工具和实验硬件连接，可以对话方式操作科学仪器。通过使信息更易于访问并根据用户需求采取行动，LLMs 可以扩大和多样化科学设施的用户，并加速科学产出。