Character Projection Mask Set Optimization for Enhancing Throughput of MCC Projection Systems

Abstract

Character projection (CP) lithography is utilized for maskless lithography and is a potential for the future photomask manufacture because it can project ICs much faster than point beam projection or variable-shaped beam (VSB) projection. In this paper, we first present a projection mask set development methodology for multi-column-cell (MCC) systems, in which column-cells can project patterns in parallel with the CP and VSB lithographies. Next, we present an INLP (integer nonlinear programming) model as well as an ILP (integer linear programming) model for optimizing a CP mask set of an MCC projection system so that projection time is reduced. The experimental results show that our optimization has achieved 33.4% less projection time in the best case than a naive CP mask development approach. The experimental results indicate that our CP mask set optimization method has virtually increased cell pattern objects on CP masks and has decreased VSB projection so that it has achieved higher projection throughput than just parallelizing two column-cells with conventional CP masks.