A physics-based statistical model for nanoparticle deposition

In this study, a general theoretical framework is proposed to analyze particle deposition on a substrate, based on statistical and physical considerations. A model is developed in the context of the proposed framework to quantitatively predict the particle deposition on the substrate in terms of coverage evolution. Its validity was then verified by a dip coating experiment, where a polydimethylsiloxane substrate was periodically immersed in a sonicated graphene solution. An extension of the model was subsequently developed to describe the growth of the deposition thickness. The proposed framework's general applicability in any situation where particle deposition is taking place is expected to spur future endeavors in systematically characterizing film coating, drug delivery, and other processes involving particle deposition.

Automated summary

The study proposed a general theoretical framework for analyzing particle deposition on a substrate, and developed a model to quantitatively predict the deposition. The validity of the model was verified through a dip coating experiment, and an extension of the model was developed to describe the growth of deposition thickness. The general applicability of the proposed framework is expected to facilitate systematic characterization of processes involving particle deposition.