14 June 1999 Model considerations, calibration issues, and metrology methods for resist-bias models
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Abstract
This paper explores the application of phenomenological models that take into account photoresist processing effects when simulating the predicted shapes of small structures in state-of-the-art microelectronic fabrication. This work extends some of the 1D model development reported in recent years to 2D structures. A brief overview of the assumptions and background of the relatively simple energy threshold model is given, followed by a more extensive discussion on proceeding beyond this point with more advanced resists 'bias' models. A number of subtle, but critical methodology and calibration issues are also discussed including (1) use of SEM top-down micrographs for extraction of measured shape information, (2) calibration of the pixel size associated with the SEM data, (3) use of the measured mask shapes for input to the simulator, (4) evaluation of the projection system focus offset and inclusion of it in the calibration of the model, and (5) the optimization of parameters in the resist-bias model. Typically we have found that after proper calibration of the resist bias model, agreement between predicted and measured shapes for full 2D structures of 3- (sigma) variation equal to 15 nm can be realized for 248-nm photolithography, for nominal 0.25 micrometers critical dimensions. Increasing to 0.5 micrometers defocus typically increases this 3-(sigma) variation to about 40 nm. Further improvements can certainly be expected. Clearly, such predictability can greatly aid in improving the process window for chip design. Some discussion is given on the anticipated pitfalls when extending this approach beyond its region of applicability.
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Edward W. Conrad, Daniel C. Cole, David P. Paul, Eytan Barouch, "Model considerations, calibration issues, and metrology methods for resist-bias models", Proc. SPIE 3677, Metrology, Inspection, and Process Control for Microlithography XIII, (14 June 1999); doi: 10.1117/12.350782; https://doi.org/10.1117/12.350782
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