Proposed Framework for Lithography Process Control Using Prolith and Full-Profile Metrology*

Paul Friedberg
(Professor Costas J. Spanos)
Small Feature Reproducibility Program

In DUV photolithography, mask patterns and processes are increasing in complexity, while IC critical dimensions continue to shrink at a rapid pace. As a result, the proportional variability of the process will increase to unacceptable levels unless a means of more advanced process control is introduced. Previously standard offline pilot-lot experiments now prove to be too costly and difficult. One attractive and potentially highly viable alternative is simulation-based advanced process control. [1,2] The proposed control framework exploits scatterometry, which provides in-situ, full-profile metrology [3]. The major obstacle to implementing scatterometry in a process control setting is profile inversion—deriving estimated input conditions from the measured profile. In this work, a first-principle-based process simulator (Prolith [4]) is used to simulate the lithography process and create a library of profile-to-input-conditions pairs. These profiles are then used to generate simulated diffraction responses, resulting in a library of diffraction-responses-to-input-conditions pairs. Finally, the empirically measured diffraction response will be matched to a simulated diffraction response in this library, whose accompanying set of input conditions should estimate the actual input conditions well. Preliminary, simulation-only results suggest that the framework has the potential to be successful, particularly if approximate values of the input conditions are provided during the matching step. However, it is expected that the success of the framework in reality will hinge on how well Prolith models the actual lithography process, the levels of measurement noise, and the method of constructing the simulated library. The current focus of effort in this research is determining how to build a library with balanced sensitivity across all input parameters, as well as diagnosing the empirical performance of the framework.

[1]
C. Gould, “Advanced Process Control: Basic Functionality Requirements for Lithography,” SPIE, Vol. 4434, 2001.
[2]
A. Zeidler, K. Veenstra, and T. Zavecz, “Advanced Statistical Process Control: Coltrolling Sum-0.18 µm Lithography and Other Processes,” SPIE, Vol. 4434, 2001.
[3]
X. Niu, N. Jakatdar, J. Bao, C. J. Spanos, and S. Yedur, “Specular Spectroscopic Scatterometry in DUV Lithography,” SPIE, Vol. 3677, 1999.
[4]
C. Mack, “PROLITH: A Comprehensive Optical Lithography Model,” SPIE, Vol. 538, 1985.

Send mail to the author : (pfriedbe@eecs.berkeley.edu)


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