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Opportunities for retrieval and tool augmented large language models in scientific facilities 被引量:3

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摘要 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.
出处 《npj Computational Materials》 CSCD 2024年第1期588-595,共8页 计算材料学(英文)
基金 supported by the U.S.DOE,Office of Basic Energy Sciences,under Contract No.DE-AC02-06CH11357 supported by the U.S.DOE Office of Science-Advanced Scientific Computing Research Program,under Contract No.DE-AC02-06CH11357.
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