Transforming Single Crystal Neutron Diffraction with Agentic AI

Single-crystal neutron diffraction is an indispensable, yet highly specialized technique for accurate molecular and magnetic structure determination. This work introduces an agentic system designed to fundamentally transform the specialized and labor-intensive workflow of single-crystal neutron diffraction experiments. The core of the application is an AI agent powered by a Large Language Model, which interprets natural language goals and generates optimized strategy and instructions for experiment execution, effectively assisting experiment steering. This system employs a client-server architecture to provide real-time guidance across various experiment stages, integrating with instrument control, live data streaming, and data reduction to ensure optimized data coverage, continuous quality checks, adaptive control, and efficient use of neutron beam time. These are realized via a real-time adaptive control engine that utilizes regression models for live data analysis and prioritizes measurements in regions of interest, coupled with machine learning algorithms for robust data quality enhancement and treatment of background noises with quantified error estimates.