Date: Thursday, May 8, 2025 Time: 11:00 a.m. EST | 8:00 a.m. PST Presenter: Liam Spillane, Analytical Application Scientist, Gatan, Inc.
Multi-frame spectrum image (SI) summation has been proposed and successfully demonstrated as a means of improving both scanning transmission electron microscopy (STEM) spectrum image resolution and signal-to-noise ratio (SNR) [1]. Scintillator-based CMOS and CCD detectors are inadequate for multi-frame electron energy loss spectroscopy (EELS) SI at low-dose and high speeds due to the detrimental effects of read noise. However, single-electron direct detection, counting cameras are capable of nearly noise-free readout, making them ideal for multi-frame EELS SI acquisition at low dose rate, as well as low total dose [2].
In this webinar, we demonstrate the capabilities of Gatan electron counting cameras, and eaSI™ technology, which together enable SI data capture at rates of up to 9,000 pixels/s. The near-zero read noise afforded by these cameras enables these ultra-high spectral rates to be utilized effectively, meaning a multi-frame acquisition approach is typically highly advantageous for all experimental workflows. Large field of view single SI passes can be acquired in just a few seconds, which gives the benefits of reduced dose rate data capture and high-frequency drift correction. Compromised data can be discarded post-acquisition, allowing “dose tuning” to be performed after the fact – ideal when you don’t know the critical damage dose ahead of time for total-dose sensitive samples.
A broad range of application examples using this methodology are presented, including elemental mapping in frozen cell sections (STEM cryo-EELS), electron energy loss near-edge structure (ELNES) mapping of transition metal K-edges (ultra-high energy-loss EELS), as well as atomic resolution EELS mapping of beam-sensitive oxides at low temperature (HR-STEM, Cryo-EELS).
[1] Jones, L., et al., Microscopy 67. Suppl 1 (2018):i98-i113 [2] Goodge, B. H. et al., https://doi.org/10.48550/arXiv.2007.09747
Please fill in all data fields to register for the webinar.
Comments
The information you provide will be used in accordance with the terms of the Gatan privacy policy.
By submitting this form, I agree to the privacy policy agreement.