cs.AIFeb 18, 2026

NeuDiff Agent: A Governed AI Workflow for Single-Crystal Neutron Crystallography

Authors: Zhongcan Xiao, Leyi Zhang, Guannan Zhang, Xiaoping Wang

Organizations: Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennesse USA · Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA · Department of Linguistics, University of Illinois Urbana-Champaign, Urbana, Illinois, USA · Department of Linguistics, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA · 

Abstract

Large-scale facilities increasingly face analysis and reporting latency as the limiting step in scientific throughput, particularly for structurally and magnetically complex samples that require iterative reduction, integration, refinement, and validation. To improve time-to-result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source that takes instrument data products through reduction, integration, refinement, and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent executes this established pipeline under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing, and controlled replay. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 minutes (manual) to 86.5(4.7) to 94.4(3.5) minutes (4.6-5.0x faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

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