CFN Colloquium (Virtual)

"Using Machine-Learning to Enable Autonomous X-ray Scattering"

Presented by Kevin Yager, Brookhaven National Lab, Center for Functional Nanomaterials

Thursday, July 2, 2020, 4:00 pm — Meeting URL:

Autonomous experimentation holds the promise of revolutionizing scientific studies and accelerating materials discovery, through instruments that can explore scientific problems without human intervention. This talk will introduce basic machine-learning concepts, and describe our ongoing development of autonomous experimentation at synchrotron x-ray scattering beamlines. Deep learning (convolutional neural networks) are used to classify x-ray detector images, with performance improving when "physics awareness" is included. 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.

Hosted by: Deyu Lu

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