Bulletin of the American Physical Society
2023 APS March Meeting
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session M36: Machine Learning in Scanning Probe Microscopy
8:00 AM–11:00 AM,
Wednesday, March 8, 2023
Room: Room 236
Sponsoring
Unit:
GIMS
Chair: Yulia Maximenko, National Institute of Standards and Tech
Abstract: M36.00003 : AI-driven atomic manipulation and characterization in the STEM*
9:12 AM–9:48 AM
Presenter:
Kevin M Roccapriore
(Oak Ridge National Lab)
Authors:
Kevin M Roccapriore
(Oak Ridge National Lab)
Maxim Ziatdinov
(Oak Ridge National Lab)
Matthew Boebinger
(Oak Ridge National Laboratory)
Ondrej Dyck
(Oak Ridge National Laboratory)
Ayana Ghosh
(Oak Ridge National Lab)
Raymond Unocic
(Oak Ridge National Laboratory)
Sergei V Kalinin
(University of Tennessee)
It will be discussed how artificial intelligence can be leveraged to guide the microscope in a variety of styles. In terms of atomic fabrication, the atomic coordinates must be extracted from image data as soon as possible. To overcome this and ensure robust predictability, deep ensembles are used, which simultaneously handle the issues - also encountered in self-driving vehicles - of so-called “out of distribution” shifts.
With fast and reliable extraction of atomic coordinates, one can begin to experiment with beam-induced effects precisely at the single-defect level. We show that different strategies can realize structures – in both graphene and MoS2 - that cannot be fabricated by any other means. It is also discussed how one can autonomously measure and discover different phenomena by utilizing deep kernel learning in both EELS and 4D-STEM modalities.
*This research is sponsored by the INTERSECT Initiative as part of the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This research used resources of the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.
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