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Self-driving Multimodal Studies at User Facilities



Bruce D. Ravel, Phillip Michael Maffettone, Daniel Allan, Stuart Campbell, Matthew Carbone, Brian DeCost, Howie Joress, Dmitri Gavrilov, Marcus Hanwell, Joshua Lynch, Stuart Wilkins, Jakub Wlodek, Daniel Olds


Multimodal characterization is commonly required for understanding materials. User facilities possess the infrastructure to perform these measurements, albeit in serial over days to months. In this paper, we describe a unified multimodal measurement of a single sample library at distant instruments, driven by a concert of distributed agents that use analysis from each modality to inform the direction of the other in real time. Powered by the Bluesky project at the National Synchrotron Light Source II, this experiment is a world's first for beamline science, and provides a blueprint for future approaches to multimodal and multifidelity experiments at user facilities.


Machine learning, user facilities


Ravel, B. , Maffettone, P. , Allan, D. , Campbell, S. , Carbone, M. , DeCost, B. , Joress, H. , Gavrilov, D. , Hanwell, M. , Lynch, J. , Wilkins, S. , Wlodek, J. and Olds, D. (2023), Self-driving Multimodal Studies at User Facilities, arXiv, [online],,, (Accessed July 13, 2024)


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Created January 22, 2023, Updated January 26, 2023