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.

翻译：先进科学用户设施（如新一代X射线光源、纳米科学中心和中子设施）的升级正彻底改变我们对从生命科学到微电子学等物理科学领域材料的认知。然而，这些设施及仪器的升级伴随着复杂性的显著增加。受更高科学需求的驱动，仪器和实验每年都变得更加精密复杂。这种运行复杂性的提升使得领域科学家越来越难以设计出能有效利用这些先进仪器能力并操作其运行的实验。大语言模型（LLM）能够执行复杂信息检索、辅助跨应用的知识密集型任务，并提供工具使用指导。以X射线光源、领导级计算中心及纳米科学中心为例，我们描述了面向科学的“上下文感知语言模型”（CALMS）的初步实验，该模型旨在辅助科学家进行仪器操作和复杂实验。通过具备从设施文档中检索相关信息的能力，CALMS可解答关于科学能力及其他操作流程的简单问题。通过与软件工具和实验硬件交互，CALMS能以对话方式操作科学仪器。通过提升信息可访问性并响应用户需求，LLM有望扩大科学设施的用户群体与多样性，并加速科研成果产出。