DMD maskless lithography optimization based on an improved genetic algorithm

Abstract

Abstract In this paper, we propose an effective method for optimizing mask design using an enhanced genetic algorithm (GA), significantly boosting digital micromirror device (DMD) maskless lithography performance. After a thorough evaluation of various optimization techniques, we determined that the simulated annealing-enhanced GA (SA-GA) offers superior improvements in lithography simulations, thus optimizing mask design more effectively. Our findings reveal that this method achieves up to 88% and 75% enhancement in simulation accuracy for circular and heart-shaped patterns, respectively, surpassing the results of conventional Hopkins lithography simulations. The remarkable effect of improved GA in enhancing the quality of DMD digital lithography shows that it will have great potential in micro-fabrication applications, and paves the way for the realization of high-fidelity and efficient DMD digital lithography technology, which has excellent versatility and adaptability in the field of microelectronics manufacturing.