Accurate nanoparticle size measurement by combining photometry and tracking analysis

Abstract

Accurate determination of nanoparticle size is paramount in various fields, including molecular imaging, food safety, drug delivery, and nanobiotechnology. Conventional methods face limitations in accurately resolving different size distributions. Here, we introduce an approach to measure size distribution by combining photometry and tracking analysis of single particles. Our approach is based on a plasmonic dark field imaging system to image and track individual nanoparticles. Scattering intensity, spot size, and diffusion coefficient are quantified and fed into the machine learning model to establish the relationship with particle sizes. Compared with conventional methods, our approach shows improved accuracy in size measurement. To verify the universality of our method, we further demonstrate the sizing capability at diverse and complex conditions, enabling us to discriminate particle size differences within 20 nm in polydisperse systems.