A physics-based statistical model for nanoparticle deposition

Abstract

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.

Wafer-Scale Full-Coverage Self-Limiting Assembly of Particles on Flexible Substrates

“…Another striking particle is much more likely to bounce off an already assembled monolayer due to both the hard collision and the acoustic field maintaining dispersion. The time evolution of the substrate’s covered fraction, δ­( t ) = 1 – e –α C 0 a p t , depends on the single particle’s occupied area on the substrate, a p , the particles’ mass concentration C 0 , and , where m is the single particle mass. Figure g shows representative fitting results of the equation for δ­( t ) for a particle size of 761 nm at different concentrations, while Figure h shows the same analysis, as the one illustrated in Figure g, but for different particle sizes.…”