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Chapter 3 is a tutorial on optical lithography which encompasses the physics and theory of operation including issues associated with advanced processes, and corresponding solutions. It begins with a brief historical perspective, an introduction and simple imaging theory. Then it takes the reader through the challenges for the 100 nm nodes and beyond. This is followed by an overview of the significant process variations, the impact of low‐κ imaging on process sensitivities. A detailed discussion of low‐κ imaging follows, including its effect on depth of focus; exposure tolerance; mask error factor; sensitivity to aberrations; CD variation as a function of pitch; and corner rounding radius. The next topic covered is the state of the art resolution enhancement techniques which will extend the resolution of the current lithography down to a quarter of the wave‐length of the illumination used. This is followed by a discussion of the Physical Design Style Impact on RET and OPC Complexity. The chapter concludes with a look ahead into the future Lithography Technologies—the evolutionary as well as the revolutionary road maps.

As process technology scales down to very deep sub-micron (VDSM) in semiconductor manufacturing technology, intrinsic size becomes close to or even shorter than the wavelength used for optical lithography. Thus, some distortions and deformations are introduced by optical proximity effects (OPE) mainly caused by the diffraction and interference of exposure light when layout patterns on a mask are transcribed to a wafer, which influence on the yield and performance of IC circuit. In order to compensate for the deformations, optical proximity correction (OPC) is the most commonly used methodology. Presently, the OPC method is to use a unitary toleration on the whole chip layer, which makes the run time of OPC algorithm longer, causes the size of GDSII files to follow exponential growth, and results in the cost of making mask grow immensely. Firstly, this paper proposes a self-adaptation OPC method with preprocessing function of patterns classification. According to the need of the correction precision, the OPC system divides patterns corrected into two groups with different toleration: critical patterns and general patterns, which enhance the efficiency of the OPC approach. Secondly, a model-based OPC method is presented based on pattern subsection and classification, which keeps the precision of the correction as well as enhances the efficiency. We also propose a rule-based OPC method with general, concise and complete correction rules, and achieve automatic-built rules-based and its looking-up. Thirdly, we also implement an OPC system, called MR-OPC; the MR-OPC system integrates both rule-based OPC and model-based OPC into a whole, so it can solve the confliction between the efficiency and precision. Experimental results show that the MR-OPC system we suggested has advantages of the efficiency and expansibility.