Real-time estimation of growth rate and surface roughness in thin film growth using kinetic Monte-Carlo models

In this work, we present an approach for real-time estimation of surface roughness and growth rate in thin film growth using kinetic Monte-Carlo (MC) models. We use a multiscale model to describe the dynamics of gas phase and the evolution of film micro-structure of a thin film growth process in a stagnation flow geometry. A roughness and growth rate estimator is constructed that allows computing estimates of the surface roughness and growth rate at a time-scale comparable to the real-time evolution of the process. The estimator involves a kinetic MC simulator using multiple reduced-order lattice models, adaptive filters used to reduce stochastic fluctuations of the reduced-order lattice MC simulator outputs and measurement error compensators used to reduce the errors between the estimates and the measurements. The proposed estimator can be used within a real-time feedback control system to improve the control performance by providing estimates of surface roughness and growth rate at time instants in which the measurements of these variables are not available.