Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy

We introduce a machine learning approach to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). Our method is data-centric, leveraging data collected on a STEM. The data samp...

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Bibliographische Detailangaben

Hauptverfasser:	Schwarzer, Max, Farebrother, Jesse, Greaves, Joshua, Cubuk, Ekin Dogus, Agarwal, Rishabh, Courville, Aaron, Bellemare, Marc G, Kalinin, Sergei, Mordatch, Igor, Castro, Pablo Samuel, Roccapriore, Kevin M
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Physics - Materials Science Physics - Mesoscale and Nanoscale Physics
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