We build on our prior work on electrostatically directed nanoparticle assembly on a field-generating substrate (Tsai et al 2005 Nanotechnology 16 1856–62). In this paper we develop a data set for particle size-resolved deposition, from which a Brownian dynamics model for the process can be evaluated. We have developed a trajectory model applied to positioning metal nanoparticles from the gas phase onto electrostatic patterns generated by biasing p–n junction substrates. Brownian motion and fluid convection of nanoparticles, as well as the interactions between the charged nanoparticles and the patterned substrate, including electrostatic force, image force and van der Waals force, are accounted for in the simulation. Using both experiment and simulation we have investigated the effects of the particle size, electric field intensity, and the convective flow on coverage selectivity. Coverage selectivity is most sensitive to electric field, which is controlled by the applied reverse bias voltage across the p–n junction. A non-dimensional analysis of the competition between the electrostatic and diffusion force is found to provide a means to collapse a wide range of process operating conditions and is an effective indicator of process performance.