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

Ultramicroscopy. 2023 Nov 11;256:113881. doi: 10.1016/j.ultramic.2023.113881. Online ahead of print.ABSTRACTNovel 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.PMID:37976972 | DOI:10.1016/j.ultramic.2023.113881

Source: Ultramicroscopy - November 17, 2023 Category: Laboratory Medicine Authors: Alexander Schr öder Christopher Rathje Leon van Velzen Maurits Kelder Sascha Sch äfer Source Type: research