This award will support research in dynamic systems and control of a manufacturing process, contributing to fundamental science and emerging domestic industries. Roll-to-Roll (R2R) dry transfer is a critical process in manufacturing flexible electronics, hydrogen fuel cells, organic solar cells, and two-dimensional (2D) materials. The goal of R2R manufacturing is to enable faster production of better products and to benefit from economies of scale. Although it is expected to be the future production method for a variety of next-generation products, R2R manufacturing suffers from technical challenges that prevent it from being widely adopted in industry. These challenges include control of roller dynamics, mechanics of delamination, on-line monitoring, diagnosis, and quality control. The goal of this research is to establish a modeling and control framework for R2R manufacturing, specifically focusing on an R2R dry transfer process, to achieve optimal system performance in real-time operation. The research will enable the design and manufacturing of complex printed electronic products and improve the quality of large-scale transferred 2D material. The research will be multidisciplinary, involving dynamic system modeling, control theory, advanced manufacturing, and materials science. It will help broaden participation of underrepresented groups in research and contribute to maintaining US leadership in advanced manufacturing through technology advancement and STEM workforce development.

The research will investigate dry peeling mechanics and a reversible system convexification method for real-time process control. A new convex model predictive control methodology will be developed to enable reversible convexification, a property that is critical for evaluating control design and conducting informed system reconfiguration. The R2R dry transfer process is a high-order switched system. Research on the stability and optimal performance of such a system will lead to important advancements in switched-system control theory. Control algorithms developed in this research will be able to handle the complexity of the system and be simple enough for real-time implementation. The research will significantly advance the state of the art of R2R manufacturing and enable a low-cost and high-throughput production method for flexible electronics and 2D materials. The methodologies to be developed in this research will find a wide range of applications in manufacturing processes and other complex engineering systems that involve nonlinearity and high-order switched-system dynamics.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2021-01-01
Budget End
2023-12-31
Support Year
Fiscal Year
2020
Total Cost
$447,197
Indirect Cost
Name
University of Texas Austin
Department
Type
DUNS #
City
Austin
State
TX
Country
United States
Zip Code
78759