When will Low-Contrast Features be Visible in a STEM X-Ray Spectrum Image?

Area of Science:

• Materials Science
• Analytical Chemistry
• Microscopy

Background:

• Detecting small, low-contrast features in scanning transmission electron microscopy (STEM) X-ray maps is challenging.
• Existing methods for simulating X-ray maps can be computationally intensive.

Purpose of the Study:

• To develop a computationally inexpensive method for simulating X-ray maps and spectrum images (SIs).
• To establish a figure of merit for comparing feature detectability across different experimental conditions.

Main Methods:

• Simulated X-ray maps and SIs based on X-ray generation and detection equations.
• Utilized nanostructured ferritic alloy (NFA) with embedded precipitates as a model system.
• Proposed a figure of merit: electron dose multiplied by X-ray collection solid angle.

Main Results:

• Simulated data sets closely matched experimental NFA X-ray maps from three different STEM instruments.
• The simulation method is computationally inexpensive and produces physically realistic data.
• The proposed figure of merit effectively compares feature detectability.

Conclusions:

• The developed simulation method is a valuable tool for predicting and optimizing STEM X-ray map experiments.
• The method can guide experimental design for enhanced detection of small features.
• Potential applications include analyzing irradiated materials, nanoparticles, and solar cells.