A convolutional neural network is used to align an orbital angular momentum sorter in a transmission electron microscope. The method is demonstrated using simulations and experiments. As a result of its accuracy and speed, it offers the possibility of real-time tuning of other electron optical devices and electron beam shaping configurations.
Alignment of electron optical beam shaping elements using a convolutional neural network / Rotunno, E.; Tavabi, A. H.; Rosi, P.; Frabboni, S.; Tiemeijer, P.; Dunin-Borkowski, R. E.; Grillo, V.. - In: ULTRAMICROSCOPY. - ISSN 0304-3991. - 228:(2021), pp. 1-7. [10.1016/j.ultramic.2021.113338]
Alignment of electron optical beam shaping elements using a convolutional neural network
Frabboni S.;
2021
Abstract
A convolutional neural network is used to align an orbital angular momentum sorter in a transmission electron microscope. The method is demonstrated using simulations and experiments. As a result of its accuracy and speed, it offers the possibility of real-time tuning of other electron optical devices and electron beam shaping configurations.
| File | Dimensione | Formato | |
|---|---|---|---|
|
1-s2.0-S0304399121001224-main.pdf
Open access
Tipologia:
Versione pubblicata dall'editore
Dimensione
6.63 MB
Formato
Adobe PDF
|
6.63 MB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris
