期刊
MICROSCOPY AND MICROANALYSIS
卷 28, 期 4, 页码 1437-1443出版社
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S1431927622000277
关键词
chromatic aberration; image simulation; low-voltage imaging; monochromation; scanning transmission electron microscope (STEM)
资金
- Advanced Microscopy Laboratory of the Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN)
- Provost's Project Award
- School of Physics
- Advanced Materials and BioEngineering Research (AMBER) Centre [17/RC-PhD/3477]
- School of Physics Summer Undergraduate Research Experience (SURE) scholarship
- SFI grant [19/FFP/6813]
- SFI/Royal Society Fellowship [URF/RI/191637]
- Science Foundation Ireland (SFI) [17/RC-PhD/3477] Funding Source: Science Foundation Ireland (SFI)
This study examines the factors affecting the image quality of gold nanoparticles imaged in a low-voltage transmission electron microscope, and proposes a methodology for selecting the optimum energy spread.
Low-voltage transmission electron microscopy (<= 80 kV) has many applications in imaging beam-sensitive samples, such as metallic nanoparticles, which may become damaged at higher voltages. To improve resolution, spherical aberration can be corrected for in a scanning transmission electron microscope (STEM); however, chromatic aberration may then dominate, limiting the ultimate resolution of the microscope. Using image simulations, we examine how a chromatic aberration corrector, different objective lenses, and different beam energy spreads each affect the image quality of a gold nanoparticle imaged at low voltages in a spherical aberration-corrected STEM. A quantitative analysis of the simulated examples can inform the choice of instrumentation for low-voltage imaging. We here demonstrate a methodology whereby the optimum energy spread to operate a specific STEM can be deduced. This methodology can then be adapted to the specific sample and instrument of the reader, enabling them to make an informed economical choice as to what would be most beneficial for their STEM in the cost-conscious landscape of scientific infrastructure.
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