A Statistical Evaluation of the Various Parameters Governing the Assembly of Solution-Based Nanoparticles on Polymer Substrates

Particle assembly on soft substrates has widely encountered applications in flexible optical and electronic systems. In this study, the various factors affecting nanoparticle deposition on a flexible substrate are examined experimentally. A PDMS substrate is prepared and mounted on the free end of a crank-slider mechanism whose settings determine the substrate's speed and position history as it is periodically immersed in and withdrawn from an aqueous solution of Silicon Dioxide (SiO2) nanoparticles. Different particle sizes and solution concentrations are used. At 7 time points within the 15-minute duration for each run, 12 square regions on the substrate are scanned at a high resolution with an optical microscope. Each square is then divided into a grid of 10x10 tiles that are individually analyzed for particle coverage. The resulting coverage data is aggregated and the effects of the particle size, concentration, and substrate's local assembly time, were statistically evaluated. The goal of this data-driven study is to infer the optimal combination of parameter settings that would yield the fastest and highest coverage performance under different constraints. Physical interpretations of the results are later proposed and discussed.