Room 1037 (Emerging Technology Building- ETB)
Dr. Frank Liu (IBM/ARL)
Optical lithography process in semiconductor manufacturing is lossy. Only low frequency components of the electromagnetic waves can pass the system, resulting the distortion of the printed features on the wafer. One method to compensate the distortion is to adjust the mask in order to compensate for the loss. In this talk, we present a novel inverse lithography method to solve the mask optimization problem. Recognizing that when formulated on a pixel-by-pixel basis with partially coherent optical models, the problem is a large-scale nonlinear optimization problem, we cast the optimization flow into a homotopy framework and apply an efficient numerical continuation technique. Another novel component of the method is a post-processing step to enhance mask manufactureability requirements by adjusting mask features. Compared to earlier pixel-based inverse lithography methods, our homotopy approach is not only more efficient, but also capable of naturally addressing the mask manufactureability problem. Experiment results in a state-of-the-art lithography environment show that our method generates high fidelity wafer images, and is 100x faster than previously reported inverse lithography method.
Bio: Frank Liu received his Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University in 1999. Prior to that he received a M.S. degree in Applied Mathematics from University of Minnesota. He has been with IBM Research Austin after a short period with IBM Microelectronics Division. His research interests include circuit simulation, model order reduction, design-for-manufactureability, inverse lithography, and other large scale numerical simulation/optimization problems. In recent years, he has been working on the dynamic simulation of large scale river networks. He is a senior member of IEEE.