Machine Learning for grouping nano-objects based on their morphological parameters obtained from SEM analysis.

Nanoparticles have unique properties that make them useful in a variety of applications, but their potential toxicity raises concerns about their safety. Accurate characterization of nanoparticles is essential for understanding their behavior and potential risks. In this study, we employed machine learning algorithms to automatically identify nanoparticles based on their morphological parameters, achieving high classification accuracy. Our results demonstrate the effectiveness of machine learning for nanoparticle identification and highlight the need for more precise characterization methods to ensure their safe use in various applications.