Nonlinear Model Predictive Control for Roll-to-Roll Mechanical Transfer of Printed Electronics and 2D Materials

Roll-to-roll (R2R) mechanical transfer is an advanced technology that facilitates continuous, etchant-free transfer of printed electronics and two-dimensional (2D) materials on flexible substrates. It involves dry peeling of fabricated devices or material from a donor substrate and transferring them to a target substrate, both being flexible and known as webs. Achieving high-quality transfer requires precise regulation of the tensions in these webs, necessitating a controller that handles process nonlinearities, disturbances, and input constraints. To address these challenges, we propose a nonlinear model predictive control (MPC) approach for R2R mechanical peeling. However, current R2R peeling models are either too computationally expensive to use or lack the accuracy needed for real-time application. This study introduces a fast, accurate nonlinear model of R2R peeling and integrates it into an MPC framework. A case study on the dry transfer of chemical vapor deposition (CVD) graphene is used to demonstrate the effectiveness of this proposed nonlinear MPC approach.