Efficient curvilinear optical proximity correction using non-uniform B-spline curves

The curvilinear mask has received much attention in recent years due to its better lithography imaging fidelity than the Manhattan mask. As a significant part of computational lithography techniques, the curvilinear OPC optimally designs the mask contour represented by parametric curves to generate a curvilinear mask structure. However, the current curvilinear OPC process is computationally intensive and contains redundant data. In this paper, a curvilinear OPC method using the non-uniform B-spline curve, together with a knot removal process, is proposed to improve the optimization efficiency and reduce the mask file size. The non-uniform B-spline curve is used to characterize curvilinear mask structure without a complex splicing process, which can effectively reduce the computation complexity. To our best knowledge, knot removal theory is for the first time applied to solve the redundant data problem in curvilinear OPC. Simulations and comparisons verify the superior optimization efficiency and data reduction (DRON) rate of the proposed method.