Model Predictive Control of Spray Coating of Perovskite Quantum Dots for Application in Perovskite Solar Cells

Recently, spray coating of perovskite quantum dots (QDs) have received significant attention as it provides a fast-scalable manufacturing alternative to problem-strike spin coating of QDs for production of high efficiency perovskite solar cells (PSCs). However, optimal design of a spray coating process for QDs requires an an accurate model that can consider the various macroscopic and surface-level phenomena. To this end, a multiscale model was developed to describe the spray coating dynamics. Specifically, a discrete element method (DEM)-based multiscale model was developed to accurately describe the interplay between the macroscopic (i.e., heat and mass transfer) phenomenon, and the microscopic molecular interactions. Also, the proposed model was integrated with a model predictive controller (MPC) framework to ensure adequate set-point (i.e., film thickness and roughness) tracking performance. Specifically, the deposition rate and the angle of the spray cone were manipulated to achieve the desired film characteristics. Overall, the simulation results (a) describe evaporation of spray droplets on the substrate surface; (b) the effect of microscopic interactions on particle aggregation; and (c) demonstrate minimization of film roughness while achieving a desired film thickness using a MPC framework.