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Automatic Alignment of an Orbital Angular Momentum Sorter in a Transmission Electron Microscope Using a Convolutional Neural Network

Published online by Cambridge University Press:  09 September 2022

Paolo Rosi Open the ORCID record for Paolo Rosi [Opens in a new window] ,
Alexander Clausen Open the ORCID record for Alexander Clausen [Opens in a new window] ,
Dieter Weber Open the ORCID record for Dieter Weber [Opens in a new window] ,
Amir H. Tavabi ,
Stefano Frabboni ,
Peter Tiemeijer ,
Rafal E. Dunin-Borkowski ,
Enzo Rotunno Open the ORCID record for Enzo Rotunno [Opens in a new window]  and
Vincenzo Grillo
Paolo Rosi
Affiliation:
Istituto Nanoscienze - CNR, via G. Campi 213/A, Modena 41125, Italy FIM Department, University of Modena and Reggio Emilia, via G. Campi 213/A, Modena 41125, Italy
Alexander Clausen
Affiliation:
Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Forschungszentrum Jülich, Jülich 52425, Germany
Dieter Weber
Affiliation:
Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Forschungszentrum Jülich, Jülich 52425, Germany
Amir H. Tavabi
Affiliation:
Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Forschungszentrum Jülich, Jülich 52425, Germany
Stefano Frabboni
Affiliation:
Istituto Nanoscienze - CNR, via G. Campi 213/A, Modena 41125, Italy FIM Department, University of Modena and Reggio Emilia, via G. Campi 213/A, Modena 41125, Italy
Peter Tiemeijer
Affiliation:
Thermo Fisher Scientific, PO Box 80066, 5600 KA Eindhoven, The Netherlands
Rafal E. Dunin-Borkowski
Affiliation:
Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Forschungszentrum Jülich, Jülich 52425, Germany
Enzo Rotunno*
Affiliation:
Istituto Nanoscienze - CNR, via G. Campi 213/A, Modena 41125, Italy
Vincenzo Grillo
Affiliation:
Istituto Nanoscienze - CNR, via G. Campi 213/A, Modena 41125, Italy
*
*Corresponding author: Enzo Rotunno, E-mail: enzo.rotunno@nano.cnr.it
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Abstract

We report on the automatic alignment of a transmission electron microscope equipped with an orbital angular momentum sorter using a convolutional neural network. The neural network is able to control all relevant parameters of both the electron-optical setup of the microscope and the external voltage source of the sorter without input from the user. It can compensate for mechanical and optical misalignments of the sorter, in order to optimize its spectral resolution. The alignment is completed over a few frames and can be kept stable by making use of the fast fitting time of the neural network.

Keywords

artificial intelligenceelectron beam shapingelectron vortex beamorbital angular momentum sortertransmission electron microscope
Type
Original Article
Information
Microscopy and Microanalysis , First View , pp. 1 - 9
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of the Microscopy Society of America

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