Share Email Print

Proceedings Paper

Process window enhancement using advanced RET techniques for 20nm contact layer
Author(s): Yang Ping; Sarah McGowan; Ying Gong; Yee Mei Foong; Jian Liu; Jianhong Qiu; Vincent Shu; Bo Yan; Jun Ye; Pengcheng Li; Hui Zhou; Taksh Pandey; Jiao Liang; Chris Aquino; Stanislas Baron; Sanjay Kapasi
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

At the 20nm technology node, it is challenging for simple resolution enhancements techniques (RET) to achieve sufficient process margin due to significant coupling effects for dense features. Advanced computational lithography techniques including Source Mask Optimization (SMO), thick mask modeling (M3D), Model Based Sub Resolution Assist Features (MB-SRAF) and Process Window Solver (PW Solver) methods are now required in the mask correction processes to achieve optimal lithographic goals. An OPC solution must not only converge to a nominal condition with high fidelity, but also provide this fidelity over an acceptable process window condition. The solution must also be sufficiently robust to account for potential scanner or OPC model tuning. In many cases, it is observed that with even a small change in OPC parameters, the mask correction could have a big change, therefore making OPC optimization quite challenging. On top of this, different patterns may have significantly different optimum source maps and different optimum OPC solution paths. Consequently, the need for finding a globally optimal OPC solution becomes important. In this work, we introduce a holistic solution including source and mask optimization (SMO), MB-SRAF, conventional OPC and Co-Optimization OPC, in which each technique plays a unique role in process window enhancement: SMO optimizes the source to find the best source solution for all critical patterns; Co-Optimization provides the optimized location and size of scattering bars and guides the optimized OPC solution; MB-SRAF and MB-OPC then utilizes all information from advanced solvers and performs a globally optimized production solution.

Paper Details

Date Published: 31 March 2014
PDF: 10 pages
Proc. SPIE 9052, Optical Microlithography XXVII, 90521N (31 March 2014); doi: 10.1117/12.2048513
Show Author Affiliations
Yang Ping, GLOBALFOUNDRIES Inc. (United States)
Sarah McGowan, GLOBALFOUNDRIES Inc. (United States)
Ying Gong, GLOBALFOUNDRIES Singapore (Singapore)
Yee Mei Foong, GLOBALFOUNDRIES Singapore (Singapore)
Jian Liu, GLOBALFOUNDRIES Inc. (United States)
Jianhong Qiu, ASML Brion (United States)
Vincent Shu, ASML Brion (United States)
Bo Yan, ASML Brion (United States)
Jun Ye, ASML Brion (United States)
Pengcheng Li, ASML Brion (United States)
Hui Zhou, ASML Brion (United States)
Taksh Pandey, ASML Brion (United States)
Jiao Liang, ASML Brion (United States)
Chris Aquino, ASML Brion (United States)
Stanislas Baron, ASML Brion (United States)
Sanjay Kapasi, ASML Brion (United States)

Published in SPIE Proceedings Vol. 9052:
Optical Microlithography XXVII
Kafai Lai; Andreas Erdmann, Editor(s)

© SPIE. Terms of Use
Back to Top