JOURNAL ARTICLE
Development of a femtosecond analytical electron microscopy based on a Schottky field emission transmission electron microscope.
Published In: Review of Scientific Instruments, 2025, v. 96, n. 3. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Ji, Shaozheng; Guo, Jiangteng; Li, Zefang; Tong, Ling; Guo, Junqing; Liu, Jingchao; Deng, Ying; Liu, Can; Sun, Zepeng; Chen, Xiang; Gao, Cuntao; Liu, Fang; Feng, Min; Fu, Xuewen 3 of 3
Abstract
This article focuses on the development and performance evaluation of an ultrafast transmission electron microscopy (UTEM) system based on a laser-driven Schottky field emitter integrated into a Thermo Fisher Scientific Talos200i transmission electron microscope. The study details the optimization of brightness, temporal resolution (~200 femtoseconds), energy dispersion (0.7 eV), and stability in the ultrafast photoemission mode, alongside beam size characterization in scanning transmission electron microscopy (STEM) mode achieving ~1.4 nm resolution. Application examples include ultrafast electron diffraction studies of photoinduced structural dynamics in polycrystalline gold films and MoS2 thin flakes, as well as polarization-dependent optical interference mapping in focused ion beam-prepared silicon thin films using photoinduced near-field electron microscopy (PINEM). These results demonstrate the UTEM’s capabilities for high spatiotemporal resolution investigations and provide insights for further advancements in ultrafast electron microscopy technology.
Additional Information
- Source:Review of Scientific Instruments. 2025/03, Vol. 96, Issue 3, p1
- Document Type:Article
- Subject Area:Science
- Publication Date:2025
- ISSN:0034-6748
- DOI:10.1063/5.0226913
- Accession Number:184175704
- Copyright Statement:Copyright of Review of Scientific Instruments is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.