Related Experiment Video
Updated: Jul 16, 2025
08:04
Preparation and Observation of Thick Biological Samples by Scanning Transmission Electron Tomography
Published on: March 12, 2017
9.3K
Advanced techniques in automated high-resolution scanning transmission electron microscopy.
Alexander J Pattison1, Cassio C S Pedroso1, Bruce E Cohen1,2
1Molecular Foundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, United States of America.
Nanotechnology
|September 13, 2023
Summary
Scanning transmission electron microscopy (STEM) now enables high-throughput atomic structure imaging. A new pipeline system with an all-piezo stage automates data acquisition for large-scale nanoparticle analysis.
Area of Science:
- Materials Science
- Nanotechnology
- Microscopy
Background:
- Scanning transmission electron microscopy (STEM) is crucial for atomic-level material analysis.
- Current STEM workflows are labor-intensive and limited to small sample areas.
- Multimodal data acquisition in STEM offers rich, simultaneous information channels.
Purpose of the Study:
- To develop a flexible, automated system for high-throughput atomic-resolution structural data acquisition.
- To enable large-scale imaging of nanoparticles using STEM.
- To facilitate multimodal data acquisition in advanced microscopy.
Main Methods:
- Implementation of a pipeline-based system for automated experimental control.
- Integration of an all-piezo sample stage for precise, high-throughput movement.
- Application to scanning transmission electron microscopy for atomic-resolution imaging.
Main Results:
- Demonstrated high-throughput acquisition of atomic-resolution structural data.
- Successfully applied the system to large-scale imaging of nanoparticles.
- Enabled simultaneous multimodal data acquisition, enhancing analytical capabilities.
Conclusions:
- The developed pipeline system significantly enhances STEM efficiency and throughput.
- Automated, large-scale imaging of nanoparticles is now feasible with atomic resolution.
- The system advances multimodal data acquisition for materials characterization.
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