Fast optical and process proximity correction algorithms for integrated circuit manufacturing

In this thesis, we first look at the Optical Proximity Correction (OPC) problem and define the goals, constraints, and techniques available. Then, a practical and general OPC framework is built up using concepts from linear systems, control theory, and computational geometry. A simulation-based, or model-based, OPC algorithm is developed which simulates the optics and processing steps of lithography for millions of locations. The key contributions to the OPC field made in this thesis work include: (1) formulation of OPC as a feedback control problem using an iterative solution, (2) an algorithm for edge movement during OPC with cost function criteria, (3) use of fast aerial image simulation for OPC, which truly enables full chip model-based OPC, and (4) the variable threshold resist (VTR) model for simplified prediction of CD based off aerial image. A major contribution of this thesis is the development of a fast aerial image simulator which is tailored to the problem of OPC. In OPC applications, it is best to compute intensity at sparse points. Therefore, our fast aerial image simulator is tailored to computing intensity at sparse points, rather than on a regular dense grid. The starting point for the fast simulation is an established decomposition of the Hopkins partially coherent imaging equations, originally proposed by Gamo (14). Within this thesis, the decomposition is called the Sum of Coherent Systems (SOCS) structure. The numerical implementation of this decomposition using Singular Value Decomposition (SVD) is described in detail. Another contribution of this thesis is the development of a variable threshold resist model (VTR). The model uses the aerial image peak intensity and image slope along a cutline to deduce the development point of the resist, and has two primary benefits: (1) it is fast, (2) it can be fit to empirical data. We combine the fast aerial image simulator and the VTR model in an iterative feedback loop to formulate OPC as a feedback control problem. (Abstract shortened by UMI.)