Improving the temporal resolution of event-based electron detectors using neural network cluster analysis.

Autor: Schröder A; Institute of Physics, University of Oldenburg, Oldenburg, Germany; Department of Physics, University of Regensburg, Regensburg, Germany., Rathje C; Institute of Physics, University of Oldenburg, Oldenburg, Germany., van Velzen L; Amsterdam Scientific Instruments (ASI), Amsterdam, the Netherlands., Kelder M; Amsterdam Scientific Instruments (ASI), Amsterdam, the Netherlands., Schäfer S; Institute of Physics, University of Oldenburg, Oldenburg, Germany; Department of Physics, University of Regensburg, Regensburg, Germany; Regensburg Center for Ultrafast Nanoscopy, University of Regensburg, Regensburg, Germany. Electronic address: Sascha.schaefer@physik.uni-regensburg.de.
Jazyk: angličtina
Zdroj: Ultramicroscopy [Ultramicroscopy] 2024 Feb; Vol. 256, pp. 113881. Date of Electronic Publication: 2023 Nov 11.
DOI: 10.1016/j.ultramic.2023.113881
Abstrakt: Novel event-based electron detector platforms provide an avenue to extend the temporal resolution of electron microscopy into the ultrafast domain. Here, we characterize the timing accuracy of a detector based on a TimePix3 architecture using femtosecond electron pulse trains as a reference. With a large dataset of event clusters triggered by individual incident electrons, a neural network is trained to predict the electron arrival time. Corrected timings of event clusters show a temporal resolution of 2 ns, a 1.6-fold improvement over cluster-averaged timings. This method is applicable to other fast electron detectors down to sub-nanosecond temporal resolutions, offering a promising solution to enhance the precision of electron timing for various electron microscopy applications.
Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests Maurits Kelder, Leon van Velzen reports a relationship with Amsterdam Scientific Instruments (ASI) that includes: employment.
(Copyright © 2023. Published by Elsevier B.V.)
Databáze: MEDLINE
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