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Updated: May 9, 2026

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Studying Dynamic Processes of Nano-sized Objects in Liquid using Scanning Transmission Electron Microscopy
Published on: February 5, 2017
Simulating realistic imaging conditions for in situ liquid microscopy.
David A Welch1, Roland Faller, James E Evans
1Department of Chemical Engineering and Materials Science, University of California, Davis, CA, USA.
Ultramicroscopy
|July 23, 2013
Summary
New virtual electron microscopy simulates fluid-stage systems, aiding interpretation of imaging conditions for biological samples and nanoparticles. This technique improves understanding of factors affecting image quality in transmission electron microscopy.
Area of Science:
- Materials Science
- Biophysics
- Microscopy
Background:
- In situ transmission electron microscopy (TEM) allows imaging of samples in near-native states.
- Interpreting contrast features and optimizing imaging conditions in TEM remain challenging.
Purpose of the Study:
- To develop a virtual technique for simulating fluid-stage high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM).
- To improve the interpretation of image contrast and predict optimal imaging parameters for fluid-stage systems.
Main Methods:
- A multislice method was employed to create a virtual imaging technique.
- The technique simulates fluid-stage systems composed of millions of atoms.
- Simulations were performed for lead sulfide (PbS) nanoparticles under various imaging conditions.
Main Results:
- The virtual technique successfully simulated images of PbS nanoparticles.
- Simulation results showed good agreement with previous experimental findings.
- The study provides insights into how fluid path length, membrane thickness, nanoparticle position, and defocus affect image quality.
Conclusions:
- The developed virtual HAADF-STEM technique enables the simulation of complex fluid-stage systems.
- This computational approach aids in understanding and optimizing in situ TEM imaging.
- The findings contribute to improved image interpretation and prediction of imaging parameters for nanoscale systems.
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