Brookhaven AIMS Series: Machine Learning for Beamline Operations Control and Data Collection


The Brookhaven AI/ML  Seminar (AIMS) series is about showcasing research at Brookhaven National Laboratory (BNL) and elsewhere that uses AI and Machine Learning to enhance scientific discovery and that uses domain science questions to motivate new AI developments. 


    • 12:00 PM 1:00 PM
      Towards Autonomous Synchrotron Radiation Beamline 1h

      Abstract: Synchrotron radiation facility is a vast research facility that enables users to carry out research in various fields, such as clean energy, biology, energy storage, energy conversion, microelectronics, environmental/geo science, material science, condensed matter physics, and more. The synchrotron radiation beamline serves as the endpoint for conducting experiments in the synchrotron radiation facility. The length of the beamline is normally tens - hundreds of meters, consisting of multiple optical components, apertures, slits, stages, etc. It is a complicated work to operate a synchrotron radiation beamline. The idea of autonomous beamline is to find a proper way to enable the beamline to run ex-situ experiment automatically and safely, significantly increasing the operation efficiency of the beamline.

      Speaker: Yonghua Du (Brookhaven National Laboratory (NSLS II))