A simple algorithm for measuring particle size distributions on an uneven background from TEM images.

Area of Science:

• Materials Science
• Nanotechnology
• Image Analysis

Background:

• Nanoparticles are crucial in various scientific and technological fields.
• Accurate measurement of nanoparticle size distribution is essential for their application.
• Conventional methods like global thresholding struggle with uneven backgrounds in images.

Purpose of the Study:

• To develop a simple computer algorithm for precise nanoparticle size measurement.
• To address the challenge of analyzing nanoparticle images with uneven backgrounds.
• To improve the accuracy of particle size distribution analysis from transmission electron microscopy (TEM) images.

Main Methods:

• Development of a computer algorithm based on adaptive thresholding.
• Utilizing local threshold values that vary with spatial coordinates.
• Application of the algorithm to analyze images of heterogeneous catalysts.

Main Results:

• The algorithm accurately detects and characterizes nanoparticles.
• Adaptive thresholding enhances accuracy compared to global thresholding methods.
• Successful application demonstrated on heterogeneous catalyst images.

Conclusions:

• The developed algorithm offers a more accurate approach to nanoparticle size analysis.
• Adaptive thresholding is effective for handling uneven backgrounds in TEM images.
• This method provides a valuable tool for characterizing nanoparticles in materials science.