Metrology of convex-shaped nanoparticles via soft classification machine learning of TEM images.

ABSTRACT: The shape of nanoparticles is a key performance parameter for many applications, ranging from nanophotonics to nanomedicines. However, the unavoidable shape variations, which occur even in precision-controlled laboratory synthesis, can significantly impact on the interpretation and reproducibility of nanoparticle performance. Here we have developed an unsupervised, soft classification machine learning method to perform metrology of convex-shaped nanoparticles from transmission electron microscopy images. Unlike the existing methods, which are based on hard classification, soft classification provides significantly greater flexibility in being able to classify both distinct shapes, as well as non-distinct shapes where hard classification fails to provide meaningful results. We demonstrate t

SUBMITTER: Wen H 

PROVIDER: S-EPMC9417281 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature