Scanner performance predictor and optimizer in further low-k1 lithography

Abstract

Due to the importance of errors in lithography scanners, masks, and computational lithography in low-k1 lithography, application software is used to simultaneously reduce them. We have developed "Masters" application software, which is all-inclusive term of critical dimension uniformity (CDU), optical proximity effect (OPE), overlay (OVL), lens control (LNS), tool maintenance (MNT) and source optimization for wide process window (SO), for compensation of the issues on imaging and overlay.In this paper, we describe the more accurate and comprehensive solution of OPE-Master, LNS-Master and SO-Master with functions of analysis, prediction and optimization. Since OPE-Master employed a rigorous simulation, a root cause of error in OPE matching was found out. From the analysis, we had developed an additional knob and evaluated a proofof-concept for the improvement. Influence of thermal issues on projection optics is evaluated with a heating prediction, and an optimization with scanner knobs on an optimized source taken into account mask 3D effect for obtaining usable process window. Furthermore, we discuss a possibility of correction for reticle expansion by heating comparing calculation and measurement.

Parity decomposition theory of full wavefront aberration measurement using the intensity differences of aerial images in microlithography

“…The typical controllable parameters for this measurement include the illumination pupils, one-dimensional measurement patterns, and orientations of measurement patterns. To enhance the imaging quality of the latest ArF exposure apparatus, the illumination pupil consists of more than 10,000 deg of freedom, which are known as intelligent illuminator units by the Nikon Corporation [19][20][21][22][23]. Thus, the free-form shape of nonsymmetric illumination is available for this design.…”

“…(23) and (24) to Hopkins's imaging formula in Eq. (9), the image intensity is classified using the two types of parity and the perturbation order of aberration:…”

“…(9), the TCC terms in Eqs. (23) and (24) can be reduced to two-variable functions with regard to ξ 1 and ξ 2 by substituting η 1 η 2 0. All of the TCC terms in Eqs.…”

“…All of the TCC terms in Eqs. (23) and (24) are classified by parity with regard to the two inversion operations:…”

“…The kernel function K ξ 1 ; ξ 2 is assumed to be any term appearing in the TCC expansion in Eqs. (23) and (24). The integral F x is proved to be a real function with the specific properties in Eqs.…”