The evolution of AI from image interpretation toward scientific inference in nanoparticle electron microscopy
Artificial intelligence (AI) is transforming electron microscopy by enabling quantitative analysis of increasingly large and complex datasets for nanoparticle characterization. Recent advances in machine learning (ML) and deep learning (DL) have expanded microscopy from a descriptive imaging technique into a data-driven platform for structural interpretation, dynamic analysis, and scientific inference. This review examines AI methodologies for nanoparticle electron microscopy, focusing on transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), scanning transmission electron microscopy (STEM), and in situ TEM. The discussion is organized around the...
| Authors | Evropi Toulkeridou, Jiafei Li, Leonardo Lari et al. |
|---|---|
| Primary category | cond-mat.mtrl-sci |
| Published | 11 July 2026 |
| Last updated at source | 11 July 2026 |
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