Autonomous X-ray Scattering*

This talk will cover ongoing work to develop autonomous experimentation at a synchrotron x-ray scattering beamline. Deep learning (convolutional neural networks) is used to classify x-ray detector images, with performance improving when domain-specific data transformations are exploited ("physics-aware machine-learning"). These methods can be combining with customized data healing algorithms. To close the autonomous loop, we deploy a general-purpose algorithm that selects high-value experiments to conduct, attempting to minimize both uncertainty and experimental cost. Examples from recent autonomous experiments will be presented, including measuring nanoparticle ordering, combinatorial libraries of block copolymer materials, and realtime photo-thermal processing.