Optimization of lithographic masks using genetic algorithms
Due to its cost effectiveness and reliability, wet-chemical etching of silicon is still one of the key technologies for producing bulk-silicon microstructures. In this paper we present an approach for the design of advanced mask sets for anisotropic, wet-chemical etching of silicon. The optimization method of genetic algorithms is used to derive suitable masks for cases where geometrically calculated compensation structures fail. The underlying etch simulation is described as well as the optimization algorithm itself. Design tasks of current research projects are used as examples to illustrate the advantage of using the presented tool.
genetic algorithms lithography anisotropic etching bulk-micro-machining tactile sensor