Quantitative Analysis of Nanorod Aggregation and Morphology from Scanning Electron Micrographs Using SEMseg

Area of Science:

• Materials Science
• Nanotechnology
• Image Analysis

Background:

• Nanoparticle aggregation impacts materials, environmental, and biological systems.
• Scanning Electron Microscopy (SEM) offers an accessible method for nanoparticle imaging but faces challenges in image quality and analysis.
• Improved methods are needed for detailed physical insight into nanoparticle assembly.

Purpose of the Study:

• To develop a robust segmentation algorithm for analyzing nanoparticle aggregation in SEM images.
• To enhance the characterization of both dispersed nanoparticles and complex aggregates.
• To provide quantitative image processing tools for high-throughput analysis.

Main Methods:

• Development of a novel segmentation algorithm, SEMseg, specifically designed for SEM micrograph challenges.
• Comparative analysis of SEMseg against existing methods, such as those in ImageJ.
• Introduction of a new order parameter to quantify nanoparticle arrangement within aggregates.

Main Results:

• SEMseg demonstrates superior segmentation of nanoparticle aggregates compared to conventional software.
• The algorithm accurately analyzes nanoparticle size for both dispersed particles and those within aggregates.
• New physical insights into nanoparticle aggregation structures are revealed.

Conclusions:

• SEMseg provides a powerful, user-friendly tool for quantitative analysis of nanoparticles in SEM.
• The algorithm overcomes common limitations of SEM image analysis, enabling deeper understanding of nanoparticle assembly.
• Open-source availability facilitates widespread adoption and advancement in nanoparticle research.